Technology, Knowledge and the Firm Implications for Strategy and Industrial Change PHẦN 8 doc

Due to the small numbers of DBFs they are omittedfrom these ratios.As indicators referring to problem definition we calculate average numbers of assigned patents per inventor host organi

and configured in the 180 patents These roles are brought out when the fivevariables in rows a–e in Table 8.3 are calculated into various ratios ( pre-sented in rows h–l) Due to the small numbers of DBFs they are omittedfrom these ratios.

As indicators referring to problem definition we calculate average

numbers of assigned patents per inventor host organization (h) and perorganizational participation (i) All three large firms have high scores onboth ratios, indicating their advantages in defining and initiating high

volumes of innovation projects Unilever’s score of 1.9 (i) indicates an tional strength in initiating – or spotting – commercially relevant research

addi-in which they do not directly participate Universities addi-in particular have lowscores on both indicators Other firms and GRIs perform at a medium level,with each host organization on the average having 2.8 and 1.4 assignmentsrespectively

On indicators referring to problem solving universities top the list.

University organizations supply problem solving to patents 5.5 times morefrequently than they receive assignments (j), and the level of their partici-pations is 13.2 times higher than their number of assignments (k) Thelatter ratio is 4.9 for GRI, indicating their proclivity for contributing toproblem solving clearly above their level of own assignments

Since the j-ratio for the three large firms by definition is 1 it is left out ofTable 8.3 For ‘other firms’ this ratio drops to 0.6 reflecting the fact that theseassignee firms in many cases have no in-house scientists actively participat-ing in inventor teams, indicating their weakness in problem solvingcompared to any of the other actors The three large firms tend to haveassignments associated with each of their participations (ratios around 1 inratio k), but differences in their self reliance as problem solvers are broughtout by the last ratio Only Nestlé has own inventor participations in virtuallyall patents in which it is an assignee For Chr Hansen the ratio is 0.8 whileUnilever only has own inventors participating in half of its assigned patents,giving them a position of only medium strength in this respect when com-pared to Nestlé

To summarize:

1 LAB biotech R&D requires heterogeneity and recently developed skillsbeyond what most single inventor organizations can handle internally,rendering distributed innovation the predominant organizational modefor this R&D

2 Unlike the US style of pharma-related innovations, DBFs are onlymarginally present in LAB biotech, and the profile of their limitedinvolvement emphasizes contributions to problem solving above

problem definition.

3 Instead universities are the most preferred type of external partner, and

their contribution is focused almost exclusively on contributing

solu-tions to R&D problems that are defined, orchestrated and

appropri-ated by other organizations In problem solving the role of universities

is essential, while in problem definition it is negligible,

4 In this respect GRIs are different Their overall participation in

problem solving is substantial, though not quite as prevalent as that of

universities, and it reflects a more balanced potential also for problem

definition

5 All three large firms reveal strength in problem definition In problem

solving Nestlé stands out as the most self reliant organization, while

Unilever and Chr Hansen in this respect are at a medium level

6 The group of other firms are weak in terms of problem solving, but

have medium strength in problem definition

Table 8.6 recapitulates the strength of each actor as revealed by its share

of activities and scoring on the five ratios

The revealed roles in distributed innovation uncovered above are

inter-preted in this subsection on the basis of additional information on each of

the main actors This information comes out of documentary sources and

in some cases out of interviews conducted with researchers in industry and

in corporate labs

The vertical structure of the food industry gives rise to a particular

dis-tribution of R&D across its subsectors and also across different institutions

in public science Each of the subsectors in food processing uses as inputs

not only raw materials that are specific for its final products It also sources

a complex mix of ingredients that are essential in process regulation and in

modifying tastes, structures and other product functions Producers of ingredients deliver these inputs based on quite intensive R&D into process

and product technology issues across a broad scope of downstream foodproducts On this basis, the ingredients sector has come to play a growingrole in advancing the knowledge frontier in food technologies (Cheetham,1999; Jeffcoat, 1999)

The Chr Hansen Group in Denmark is a niche multinational pany, specializing in ingredients for producers of milk-based products allover the world, and is a world leader in cheese ingredients For more than

com-100 years LAB has been a crucial microorganism in Chr Hansen’s dients and services To maintain that position, from the mid 1990s thecompany successfully pursued biotechnological opportunities for furtherrefinement of their ingredients, and today they rank third among com-panies in the world in terms of numbers of LAB patents based onbiotechnology Chr Hansen’s R&D department is a plentiful point ofconfluence of information and opportunities, much of which originatesfrom the clients’ process problems (Valentin, 2000) However, this infor-mation translates into interesting innovation targets only when broughttogether with Chr Hansen’s own biological understanding of possibilitiesfor modifying LAB functionalities, giving problem definition a nonde-composable quality

ingre-A useful example of what low decomposability of problem definitionmeans in this context came out of the case studies we undertook to under-stand the research behind LAB patents Based on its long experience withsupplying ingredients to cheese manufacturers, Chr Hansen is aware notonly of the economies to be gained from reduction in cheese maturationtime They also know that the process will benefit from and be susceptible

to acceleration only at certain stages They have a deep understanding ofthe maturation process as a degeneration of milk proteins handled by a set

of enzymes, the numbers and functions of which could be controlled bypromoters This confluence of experience and insight allowed Chr Hansen

to identify effective management of precisely these promoters as a highlyrelevant target for biotech research, and it led to a problem definition thatcould not have evolved from separate deliberations of its constituent com-ponents of knowledge and information Once the problem was properlydefined, however, Chr Hansen pursued swift problem solving though dis-tributed innovation involving not only their own researchers, but also theexpertise of several public research partners Collaboratively they devel-oped (1) a method for identification of the promoters and (2) enablingtools by which the function of the promoters may be controlled (source:own interviews)

In this case problem solving obviously had a level of decomposability

allowing it to be successfully pursued in a collaborative research project

Problem definition, however, was the result of a nondecomposable process.

This pattern in Chr Hansen’s processing of innovation problems gives it

a strong position in problem definition While it undertakes more R&Dthan the average food company, it still has a considerably smaller volumecompared to Nestlé, which accounts for its medium level strength inbiotech-based problem solution observed in Table 8.5

As very large MNCs Nestlé and Unilever have sizeable internal R&Dresources at their disposal This allowed them to enter early into biotechapplications within their product lines, and they also have the sophistica-tion and volume of R&D to undertake large scale external research col-laboration However, their exact specialization differs in ways that alsotranslate into dissimilar R&D agendas in biotech For more than a centuryNestlé has specialized in milk-based products, and over the last decadesits competitive profile has increasingly emphasized nutritional qualities,backed by advanced internal R&D (Boutellier et al., 1999) Nestlé has astrong presence in biotech associated with these issues, making it muchless dependent on external R&D collaboration In a previous analysis ofthis data set (Valentin and Jensen, 2004) we demonstrated that up untilthe mid 1990s Nestlé carried out their LAB biotech R&D as internalresearch only Its shift to distributed innovation seems to be associatedwith an increasing attention to the emerging agenda for pharma-relatedapplications of LAB biotechnology (Pridmore et al., 2000) In this novelagenda Nestlé’s interest in nutritional research appears to offer a new set

of advantages, but of a kind that are additionally enhanced by externalcollaboration

Unilever in the 1930s arose as a merger of British production of soapswith Dutch activities in margarine The product line has since diversifiedfurther into a variety of frozen and canned foods (ice cream, fish products,precooked meals, etc.), and home and personal care products Unilever’sR&D is correspondingly diverse, organized along major product types(Unilever home page, 2003) Within each of these R&D specializations theemphasis on product and market focus builds strong positions in prob-lem definition But concentration of R&D on diverse applications makesUnilever more dependent on contributions from external research into ahighly heterogeneous array of biotech applications, accounting for itsmedium level strength in problem solving observed in Table 8.3

Firms in food processing are traditionally based on specific raw materials

(diary products, meat products etc.) and undertake R&D on a limited scale,often narrowly focused on particular parameters of quality, variability orhygiene of raw materials and final products (Senker, 1987) In most cases

this R&D profile prevents them from building in-house expertise capable offollowing and exploiting the advances of biotechnology (Kvistgaard, 1990).

As a consequence, in problem solving their position tends to be weak,making them quite dependent on outside expertise in collaborative arrange-ments Their deep experience in integrated product process issues offersopportunities for problem definition, but only in areas pertaining to theirspecialization in products and raw materials In this respect they are alsoconstrained by their narrow R&D focus, accounting for their revealed level

of medium strength in problem definition

Government Research Institutes (GRIs) and universities represent twoquite distinct profiles in LAB food biotech with implications for their posi-tions in problem definition and solution Prior to World War I most coun-tries established GRIs that specialized in food safety and quality Due to itsimplications for public health, in particular tuberculosis, its handling andprocessing of milk in agriculture and dairies also ranked high on the agenda

of these GRIs Furthermore, their science was needed to back the tion of standards and regulations to handle complex interdependencies inthe value chain of milk comprising farms, transport, processing, distribu-tion and consumption (Rosenberg, 1985) This mandate required then – andstill does today – ongoing research into industrial process product interde-pendencies to an extent found in very few other areas of public science(Leisner, 2002) This gives GRIs a strong role in LAB-related problem solu-tion, but also some standing in problem definition, reflected in their posi-tion at a revealed medium level in the latter

formula-Universities are the major source of researchers capable of translating

recent advances in global molecular biology into problem solving skillsand experience This makes them highly useful collaboration partners inproblem solving in biotech innovation Their remoteness from food productand process issues creates obvious disadvantages when it to comes toproblem definition However, in areas where LAB biotech research diversi-fies into issues where information on opportunities and targets flow indecomposed forms in the public domain, universities could come to play

an increasing role also in problem definition That is precisely what acterizes the issues now emerging in pharma-related applications of LABbiotech (cf Figure 8.7) The decomposability of problem definition associ-ated with these new issues gives university research possibilities for a moreaggressive role in problem definition, quite different from the weak position

char-in problem defchar-inition until now (as revealed char-in Table 8.5)

To conclude, information from documentary sources and case interviewsfrom each of the main actors produce profiles of their R&D that areconsistent with their revealed roles as problem definers and problem solvers

in LAB biotech R&D as summarized in Table 8.6

6.4 Timing

From the above presentation of findings it cannot be ruled out that the

main actors might have shifted their roles in distributed innovation over the

two decades covered by our time frame in ways that could affect the mainhypothesis of this chapter Could it be, for instance, that GRIs, universities

or DBFs in the initial breakthrough phase had a higher level of cance, which disappears when data from early years are collapsed with data

signifi-on the much higher volume of activity in later stages?

Higher significance for these organizations in the early phases would bringthis field of innovations closer into conformity with standard argumentsfrom the technology cycle literature that the weight of activity shifts fromsmall entrepreneurial units to larger firms as the cycle unfolds (Tushman

et al., 1997; Utterback, 1994) It would also make the LAB biotech casemore similar to observations on pharma-related biotechnology where suc-cessive waves of incoming new DBFs have restructured and redistributedtasks in discovery-oriented R&D (Orsenigo et al., 2001) It would weakenthe main argument of this chapter, that different levels of decomposability

of problem definition and problem solving have assigned roles in distributedinnovation for all main actors since biotechnology entered this field of R&D

in the early 1980s

To examine the patterns across time, Figure 8.10 plots patent tions by years for a categorization of actors similar to the one used inTable 8.5 To bring out underlying trends more clearly, five year movingaverages are applied

applica-Table 8.5 showed an overall 3–3–2 proportion of assignments for the lowing three groups: (1) the three top patenting companies, (2) other com-panies and (3) PROs Figure 8.9 shows that these proportions by and largeprevail over the two decades, but it also uncovers some differences in timing

fol-of activities for the three large companies: Unilever begins an increase inpatenting activity in the late 1980s Nestlé begins to increase in the early1990s with activities still expanding in the late 1990s (in fact at that timeoutgrowing Unilever’s level of patenting) Chr Hansen does not becomeactive until the mid 1990s

A different angle on the growth of patent producing R&D is presented

in Figure 8.10, which distinguishes first participation for any of the 118

inventor host organizations from contributions from organizations withreoccurring participation in LAB patent inventor teams

Throughout the 1990s the increasing volume of LAB patents is basedprimarily on reoccurring participations Each year 15–20 organizationswith previous LAB patenting experience reoccur as co-inventors in newpatents About ten organizations have their first participation

The breakdown by organizational types shows for the 1990s an inflow oftwo to four new companies every year, rising slowly through the decade.From the previous section we know that firms invariably enter as assignees.And from previous examination of the data (Valentin and Jensen, 2004) weknow that they tend to bring their ‘own’ university partners with them in acollaborative arrangement, explaining most of the elevated level of univer-sity entries observed through the 1990s During certain intervals the inflow

All other companies Unilever Chr Hansen PRO Nestlé

organizations, five year moving averages

All participations by reoccurring organizations

University first participation

Company first participation

GRI first participation

first vs reoccurring participation, two year moving averages

of new university participations becomes particularly pronounced, e.g (1)when the LAB biotech agenda opened in the early 1980s; (2) when it shiftedinto an increased activity level towards the end of the decade, and (3) again

in the mid 1990s

To summarize the patterns across time, the unfolding agenda of LABbiotech brings no dramatic shifts in the proportion of activities observedfor different types of actors Their proportion of activities remains largelythe same across the two decades Incumbents – large and small – expand

in parallel growth patterns Entry of new firms is moderate, takes placethroughout the two decades, but has a higher level in the 1990s compared

to the 1980s To conclude, the pattern is entirely inconsistent with – and

in some respects the opposite from – the model from the technology cycleliterature

We may assume, therefore, that the roles in problem definition andproblem solving identified earlier in this section have largely remained thesame across the two decades

For reasons presented below the emergent pharma-related R&D themeshave problem definition of higher decomposability compared to themes infood applications Therefore the main argument of this chapter will be sup-ported (1) if actors advantaged in problem solving transfer these advan-

tages into problem definition within the new pharma-themes, and (2) if

these are the same types of actors who specifically were prevented fromundertaking the same transfer in the nondecomposable space of foodR&D These are the issues examined in this subsection

The keyword map (Figure 8.3) identified a set of R&D themes signallingnew relationships between food- and pharma-related R&D The area from

1 to 4 o’clock in the map comprises a set of R&D themes referring toapplications in probiotics, pharmaceutical carriers, and intestinal infec-tions Positioned between these applications we find enabling innovationsrelating to cell walls and their significance for immune response Thesethemes represent a crossover from food to pharmaceutical research themes,and they have all been subject to rising attention from 1995 onwards(Figures 8.7 and 8.8)

Pharma-related innovation builds on problem identification of a moredecomposable quality compared to foods In pharmaceutical R&D clinicalresearch accumulates into a highly articulated structure of information andknowledge concerning effects and side effects of drugs A search architecture

in the public knowledge domain (cf competitor intelligence service ucts like IDdb3 (the Investigational Drugs Database (IDdb), 2003) gives

prod-pharmaceutical research highly effective access to knowledge on alities, although pharmaceutical firms, of course, guard their specific

function-insights on new targets in the pipeline.

If our main argument holds, these differences in problem definition inpharma and food biotech innovations translate into different patterns ofdistributed innovation Specifically, universities should be better positioned

to define pharma-related innovation problems as reflected in a higher share

of patent assignment We also would expect them to exploit those tunities in the areas of their particular advantage, i.e in innovation ofenablers and not in specific applications

oppor-Furthermore, we would expect food companies to be disadvantaged bythe novelty which pharma-related applications would represent to them.The one exception would be Nestlé given their clear priorities in nutritionaland health-related food research

We examine these propositions using standardized keyword scores acterizing the affiliation of each patent with each of the 12 R&D themes(presented in Appendix III, Table A8.1) First, ANOVA procedures wereapplied to test differences between assignee groups in their average keywordscores on each R&D theme Table 8.7 shows that the few patents that areassigned to universities differ starkly from those assigned to all other groupsprecisely by being significantly more strongly affiliated with the theme of cellwall-related enablers Patents assigned to Nestlé have significantly stronger

char-affiliation with the themes of probiotics and pharmaceutical carriers.Second, we test if patents affiliated with the new pharma-related themesare distinguished by particular compositions of their inventor teams Shares

of inventors coming from each of the five groups (universities, GRIs,Nestlé, Unilever, and other companies) were calculated for each patent.These relative measures were correlated with keyword scores for each of the

assignee organizations (no of organizations)

Notes:

ANOVA test: p < 0.01.

Keyword scores for R&D themes are standardized to values 0–1.

Asterisks indicating significance levels from Gabriel’s multiple comparison procedure.

pharma-related themes for the period from 1995 onwards, i.e the pointfrom which they receive increasing attention in LAB biotech R&D.The findings reported in Table 8.8 confirm a particular involvement

of universities and of Nestlé in three out of these four pharma-relatedR&D themes No other groups showed any systematic affiliation with thesethemes, indicating that Nestlé and universities play a key role in opening thecrossover from food- to pharma-related R&D themes observed from 1995onwards

To summarize: the emergence of a pharma-related research agenda in LABbiotech permits us to examine if the higher decomposability of problem def-inition in this new field brings modifications to the organization of distributedinnovation observed for food application Findings confirm that universityscientists exploit the opportunities of a more decomposed space for problemidentification by undertaking their own orchestration of collaborativeresearch Findings also confirm that firms and GRIs cannot transfer theiradvantage in the nondecomposable problem space of food to the new problemspace of pharma-applications The notable exception is Nestlé due to theirlong research tradition which has prepared them precisely for this crossover

This chapter has reported on the organization of distributed innovationshaped by the major discontinuity in the life sciences and their associatedtechnologies that has unfolded over the past three decades While moststudies have focused on its effects on pharmaceutical R&D, this chapterstudies food processing technologies, taking biotech exploitation ofthe ubiquitous microorganism of Lactic Acid Bacteria as its example.Comprehensive recording of all 180 innovations patented in this field allows

us to build a complete map of contributions from research organizations tothese innovations, from which we may reconstruct their pattern of collabo-ration and its evolution Using textmining methodologies on patent titlesand abstracts we identify the major R&D themes and their evolutionthrough the 1990s A partial fusion of food R&D with nutraceutical andpharma-related issues emerges towards the end of the decade.

Throughout their adjustment to this discontinuity incumbents largelymaintain positions and proportional shares of activity Twenty-six firms infood processing (dairy products in particular) each take out a few patentableinnovations based on their own active involvement in R&D Large incum-bents like Unilever and Nestlé patent at a level tenfold higher More than

100 research organizations – most of them university departments – becomeinvolved in the collaborative R&D behind the 180 patents But the patents

to which they supply critical skills and experience are rarely assigned tothem The few cases of university assignments are virtually all in the recentlyemerging pharma-related R&D agenda GRIs, however, are much morefrequently assigned patents to which they contribute R&D DBFs play anegligible role

To explain the organizational characteristics of this distributed

innov-ation we suggest a distinction between definition and solution of innovinnov-ation

problems While the latter in food biotech innovations has high Simoneandecomposability the former has not, giving incumbents considerable advan-tages in opportunities for recognizing and assessing the economic prospects

of using biotechnology to augment food technologies University scientistsmay contribute critical problem solving skills, but are by themselves unable

to identify valuable innovation targets Only the pharma-related R&Dthemes emerging from the mid 1990s offer to university scientists spaces forproblem definition of sufficient decomposability to allow them the role ofR&D orchestrators That precisely becomes the R&D agenda in which theyprovide the cognitive ordering of collaborative projects that make themassignees of resultant patents The research mandate of GRIs in this field,

on the other hand, allows them to share much of the combinatorial tive advantages of food firms, and they orchestrate and appropriate theirown R&D accordingly

Different types of results – empirical, methodological and theoretical – aregenerated in this chapter Empirically we demonstrate how an industry andits incumbents largely maintain structure and positions while a technolog-ical transformation unfolds in their underlying knowledge bases It offers aclear exemplification of Pavitt’s reminder to us that technological and

industrial/corporate transformations are two very different phenomena(Pavitt, 1998) Precisely the multitechnological nature of firms (Granstrand

et al., 1997) allows them to absorb new technologies gradually and informs permitting them at the same time to capitalize on strengths in othercapabilities

The subtle interrelationships between technological and corporate formations in no way detract from the importance of understanding dis-

trans-continuous innovations But it has the important methodological implication

that technological change may be observed through the lens of corporatechange only if we accept considerable levels of noise and distortions Thestudy of innovations therefore needs methodologies for mapping of singletechnologies and their evolution, decoupled from their corporate frame-works Without offering a complete decoupling, patent data in this regardtake us a valuable step forward In this respect the present chapter suggestsmethodologies for extending patent data with identification of their inven-tors and their host organizations and with text mining of their R&D issues.Theoretically the distinction introduced in the chapter between problem

decomposability as referring separately to their definition and their solution

has implications not only for the analysis above but also more generally forunderstanding competence enhancement The literature is not always clear

on whether enhancement of firms’ competencies in innovation refers to theirrelation to complementary assets, and hence essentially to their appropri-ability (Teece, 1986), or refers to the innovation process proper In thisrespect the present chapter submits a theoretical argument on decompos-ability of definition of innovation problems as an attribute of the innov-ation process proper, not of its forward linkages to complementary assets.This decomposability argument in turn specifies conditions under whichfirms may remain favourably positioned to extract knowledge and skills –potential value – from a widely distributed network in subsequent problemsolving

Distributed forms of innovation materialize in response to strong ing forces Increasing costs and commercial risks of R&D, the demand onfirms to master a broadening range of diverse technologies, increasing com-plexity and multidisciplinarity of technologies, and shortening product lifecycles all render distributed innovation increasingly significant as an organ-izational vehicle for technological and economic progress (Coombs andMetcalfe, 2000)

underly-For that reason it is important to understand what shapes the division oftasks between the key actors of distributed innovation such as producers of

goods and services (firms), suppliers of abstract knowledge (universities),translators of knowledge into new fields of applications (DBFs and GRIs)and providers of capital.

The business press tends to see a particular rendering of the US modelfor distributed innovation as the ideal framework for high tech growth.This model emphasizes market-based formation of small science-basedfirms (DBFs), backed by venture capital and strong basic science Theinference is quickly drawn that other countries, to get their share of hightech growth, must emulate the US model The reservation that this modeloperates for some US high tech sectors, but not for others, is neglected, as

is the fact that even within technologies new entry firms may be critical for

certain types of US high tech growth, while they are immaterial for others(Cockburn et al., 1999)

The findings of the present chapter suggest that the US package ofscientist–entrepreneurs and competent venture capital offers powerfulcomparative advantages only to certain types of high tech activities For all

we know, other types of high tech may thrive better under different tions That seems to be the case for the area of food biotech examined inthis chapter The theoretical argument on decomposability suggested hereindicates some of the attributes in the institutional framework that most

condi-likely would benefit this exploitation of the biotech discontinuity.

Low decomposability of problem definition in this field leaves little roomfor science-based start-ups specialized in innovative research At the sametime, problem solving requires confluence of heterogeneous fields ofresearch, all of which are continuously affected by steep progress in thescience frontier they are part of With these conditions for innovations,commercial food biotechnology will benefit less from policies promotingformation of DBFs, and will thrive on access to the benefits of strong,

responsive and multifaceted public science To deliver those benefits public

science would need the heterogeneity represented in our data by the

different mandates differentiating universities from GRIs; and it wouldneed incentives and institutional differentiation conducive to the balanced

role of public scientists of being committed both to scientific progress and

to responsiveness to technological and commercial challenges

APPENDICES

Lactic Acid Bacteria (LAB) was one of the first organisms used by man tomodify foodstuff (Konings et al., 2000), achieving preservation, safety and

variety of food, and inhibiting invasion of other pathogen microorganismscausing food-borne illnesses or spoilage (Adams, 1999).

To yield cheese, yoghurt and other dairy products LAB ferments milk bydecomposing lactose (the main saccharine in milk) to generate a carbonsource and to get energy Rather than breaking down lactose completelyLAB leave lactic acids as one of many by-products Lactic acid reduces pH

in milk, leading it to sour and to form the familiar thick texture of milk and yoghurt Following acidification the process of adding flavour andaroma is started by adding a starter culture composed of a variety of LABstrains The production of cheese begins with an identical procedure ofacidification, but then adds an enzyme treatment of the milk protein casein

butter-to generate a creamy lump (curd), which forms the basis for the subsequentprocesses

LAB plays a crucial role in modern production of fermented dairy ucts, vegetables and meat, as well as in the processing of wine products.Over the last decade scientific understanding of LAB (e.g its metabolismand functions) has expanded considerably, opening up the way for morereliable process control in production and for an increasing range of indus-trial applications, including its use in food as additives

Expanding applications also include explorations of LAB in dairy ucts enhancing probiotic functions (i.e favourably affecting the microbio-logical flora in the gastrointestinal tract of humans or animals) Probiotic

prod-effects of different members of the LAB family, for instance lactobacillus,have been shown to appear not only in intestinal microflora (Berg, 1998;Dugas et al., 1999; Roberfroid, 2000; Saarela et al., 2000; Tannock, 1997)but also in the immune system (Reid, 1999; Wagner et al., 1997) These newfields of application of lactic acid bacteria are promising targets for futureresearch, which will gain further momentum from the growing under-standing of the genomics of the gram-positive bacteria

Fermentation of yoghurt and hard ‘cooked’ cheese products likeEmmenthal, Parmigiano, Grana etc requires incubation of milk or curd attemperatures above 45C, under which conditions normal versions of LABare unable to survive (Delcour et al., 2000) Specific strains of the bacteriawith thermophilic characteristics can survive at this elevated temperature.Compared to other areas of LAB research, thermophilic strains havereceived less attention, until a steep increase in efforts over the last few yearsfocused on genetics, metabolism and physiology gave notable results interms of molecular tools and knowledge Particular attention has beengiven to research on bacteriophages, stress response and polysaccharidesexported to the culture medium (the fermented milk product) Research inthermophilic bacteriophages has special significance because they are keydrivers of instability and costs in the dairy industry