Standardisation and particularisation in services: evidence from Germany

Research Policy 30 (2001) 1115–1138

Standardisation and particularisation in services: evidence from Germany Bruce S. Tether a,∗ , Christiane Hipp b,c , Ian Miles d a

d

ESRC Centre for Research on Innovation & Competition (CRIC), University of Manchester and UMIST, Tom Lupton Suite, Precinct Centre, Oxford Road, Manchester, M13 9QH, UK b Mannesmann Pilotentwicklung, Chiemgaustr. 116, 81549 Munich, Germany c Department of Technology and Innovation Management, Technical University of Hamburg Harburg, Schwarzenbergstr. 95, 21073 Hamburg, Germany CRIC and PREST, University of Manchester, Mathematics Building, Oxford Road, Manchester, M12 9PL, UK Received 16 September 1999; received in revised form 10 September 2000; accepted 12 September 2000

Abstract Services have been widely neglected by economists and analysts of innovation, who have instead focused on manufacturing. One of the widely supposed features of services outputs is that they are often highly tailored to their clients. In practice, however, services are sometimes mass-produced and sometimes customised versions of standard products, but can also be produced on a one-off basis. This paper examines the pattern of service activities using German evidence with respect to the structure of service firms’ income from ‘standardised’, ‘partially customised’ and ‘bespoke’ services. The analysis then relates the revealed patterns of ‘standardisation–particularisation’ in the output of the firms to their size and broad sector of activity, and considers the relationship with innovation. Our analysis lends support to previous theoretical studies which provide useful taxonomies of service activities and innovation processes in services. However, our analysis also confirms that services are tremendously diverse both between and within sectors. Mapping and understanding this diversity is a major challenge for future research on service firms and their (innovative) activities. © 2001 Elsevier Science B.V. All rights reserved. Keywords: Standardisation; Particularisation; Services; Innovation

1. Introduction It is well known that in the advanced economies of the OECD services account for roughly two-thirds of GDP and employment (Eurostat, 1999), and that these shares are increasing, whereas those of manufacturing are in decline. In 1970, services accounted for half the ∗

Corresponding author. Tel.: +44-161-275-7376; fax: +44-161-275-7361. E-mail addresses: [email protected] (B.S. Tether), [email protected] (C. Hipp), [email protected] (I. Miles).

European Union’s GDP and less than half (46%) of its total employment, whilst by 1997 ‘market services’ alone accounted for 46% of employment in the EU and 52% its GDP. ‘Non-market services’ accounted for a further 21% of employment and 15% of GDP (Eurostat, 1999). Thus, in 27 years services have increased their share of total employment in the European Union by 21 percentage points; they are the only broad sector of the economy that has expanded in terms of employment, and this trend will undoubtedly continue into the foreseeable future. Even in Germany, a country famous for its manufactured products, services account for a significantly larger share of GDP than manufacturing

0048-7333/01/$ – see front matter © 2001 Elsevier Science B.V. All rights reserved. PII: S 0 0 4 8 - 7 3 3 3 ( 0 0 ) 0 0 1 3 3 - 5

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Table 1 The service sector in the West German economy in 1994

All services Services surveyeda Other servicesb Manufacturing

Percentage of the workforce (%)

Growth since 1981 (%)

Percentage of firms (%)

57 32 25 33

2.0 1.9 2.1 −0.8

70 42 28 17

a Wholesaling, retailing, transport and communications, banking and insurance, technical services, software and other business oriented services. b Public administration, education, health care, hotels and catering, services to households, other non-business oriented services. Source: Licht et al. (1995).

(68% versus 31% in 1996 — OECD, 1998), and the same is true of employment, as Table 1 shows. Yet, despite their economic importance, services have received relatively little attention from economists (whether orthodox or Schumpeterian) or from other analysts of innovation, particularly at the micro level. At the macro level the growing importance of services is often related to the alleged productivity slowdown, and the ‘productivity paradox’ (e.g. Roach, 1988, 1991), but whether this slowdown is real, or the result of mis-measurement, is contentious (Grilliches, 1992). The poor state of statistical data on services in many countries underlies this debate — there are grounds for thinking that output and productivity gains in services may be underrepresented in existing statistics. But these measurement problems reflect, in turn, an inadequate understanding of the nature of service activities, and limited efforts to measure innovation, productivity, and indeed many other features of services. The neglect of services, and innovation in services, relates to the widely held view that services are undynamic, even moribund. Arguably, this itself reflects a strong tradition within economics and innovation studies that privileges scientific and technological knowledge, particularly R&D and the development of new tangible artefacts, over other forms of knowledge or change — for example, organisational innovations or changes in routines and procedures — and which therefore sees manufacturing as the key driving sector. Because most services do not undertake R&D and are not producers of new or technically improved tangible

artefacts, 1 analysts have had difficulty in applying the received understanding of innovation to services, and much of the literature is concerned with services as adopters and users of new technologies, particularly information and communication technologies (ICTs), rather than as creative innovators in their own right. Until recently, the only substantial evidence for dynamic activities in services came from case study work. But in the 1990s considerable efforts have been made, through the use of wide-scale surveys and broad research programs, to gain a fuller understanding of the nature of service activities, and a handle on innovation in services. This paper explores some results derived from one such pioneering effort — the 1995 survey of innovation in German service companies. This survey was one of the first large-scale surveys of services, and innovation in services. 2 In this paper we consider the relationships between the classic variables of firm size and sector of activity, together with the issue of the standardisation or particularisation of the firms’ outputs, which is especially relevant to services. We also discuss innovation, although briefly. In a second paper (Hipp et al., 2000), we discuss innovation in services at greater length. In presenting this analysis, we emphasise two things. Firstly, the theoretical understanding of services and especially the extent to which service outputs are subject to standardisation or particularisation (that is whether they are undifferentiated between customers, or are adapted to particular customer needs) is still relatively immature, as is the wider understanding of innovation in services. Secondly, the empirical assessment of the extent of standardisation or particularisation in services, and indeed innovation, is also 1 Services are so diverse that practically any generalisation about them will come up against numerous exceptions. Rapid prototyping services, dentistry, and the ‘hushkitting’ of aircraft are all examples of activities classified as services which may well produce improved technological artefacts. 2 Similar surveys, have been carried out in Denmark (Sundbo, 2000), Finland (Marklund, 2000), Italy (Evangelista and Savona, 1998; Sirilli and Evangelista, 1998) and the Netherlands (Brouwer and Kleinknecht, 1995). More recently, 13 European Union countries included some market services in the second round of the Community Innovation Survey (CIS-2), results from which should be available in due course. Unfortunately CIS-2 did not address the issue of standardisation–particularisation that we assess here, nor does it provide information on the structure of employment by qualifications.

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relatively undeveloped. In the main, research tools developed through studies of manufacturing have simply been adapted to services. A debate continues as to how appropriate or adequate these tools are for assessing service activities. Our aim in this paper is to provide some insights into the extent and pattern of standardisation and particularisation in services, and to relate these to innovation activities. On occasion, due to the stage of development of this field of study, our interpretation of the empirical results will be tentative. We begin the paper with a brief review of the literature concerning standardisation and particularisation in services (Section 2), before introducing the empirical evidence (Section 3). The empirical analysis begins with a discussion of the size and (broad) sector characteristics of the surveyed firms. Section 4 then focuses on the standardisation–particularisation of the firms’ outputs. Section 5 provides some further evidence on the structure of employment by qualifications in the surveyed firms, their propensities to innovate, and the propensities of the innovating firms to undertake R&D. The paper ends with a concluding discussion. 3 2. A brief review of the literature We begin with a brief review of the literature on standardisation, variation, specialisation and innovation in services. In particular, we discuss two sets of models: firstly, life-cycle models which relate to the standardisation and destandardisation of service outputs, and secondly, some taxonomic models which broadly relate the nature of the service activities to the extent to which their outputs are standardised or particularised and, less directly, to sector and firm size. 2.1. Life cycle models — standardisation and innovation in services For our purposes, life cycle models are of interest because they relate service activities, and innovation 3

A second paper (Hipp et al., 2000) builds upon this analysis to consider the interaction between the characteristics of the firms which are examined in this paper and their reported innovation activities, and to consider the effects of the innovations on their producers, on the service(s) provided, and on the service users.

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in service activities, to the standardisation or particularisation of service outputs. Barras (1986, 1990) saw such models as particularly relevant to services, and related innovation in services to a reverse product life cycle model. 4 In the conventional industry or product life cycle (PLC) model, the first period of activity of the industry is characterised by entry and variety, with a large number of (mainly small) producers providing various offerings to the market (see Klepper, 1996, for a discussion of the PLC model). Competition is in large part focused on the ability to supply superior product designs, with suppliers coming to understand user requirements whilst users grow accustomed to the features and capabilities of the product offerings. During this phase the firms in the industry may supply standardised outputs, although generally in small volumes; they may customise their outputs, adapting them to the requirements of individual customers; at the extreme each output may be individually designed, i.e. bespoke. During this early phase, the emphasis is on product innovation, both within individual firms and in the industry as a whole. Whilst most firms active in the new industry will be small, this picture is confused if large firms from other industries enter the market. The second phase of the PLC is characterised by a convergence on a dominant design, such that variety, in terms of product offerings, declines, standardisation of output increases, and a relatively small number of dominant producers emerge after a period of ‘shake-out’. Not enough is known about the processes by which dominant designs emerge, but, within individual firms, the dominant producers tend to standardise their outputs, and concentrate particularly on process rather than product innovation, whilst fringe producers might also standardise their outputs — producing them in low volumes for niche markets. Alternatively, fringe producers may adapt their outputs to suit niche markets or individual needs. Competition becomes more focused on price, with suppliers seeking to produce the established product types by cheaper methods than their rivals. The latter 4

In this paper we consider standardisation–particularisation to be the result of strategic choices made by the management of the firms in relation to their outputs. Standardisation may also occur because of cultural norms, or may be imposed through legislation, but these are not discussed in this paper.

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stages of the PLC are generally characterised by the dominance of a few large producers providing generally standardised products, although some commentators stress the scope for product differentiation, or for ‘dematuration’, following changes in underlying technologies or changes in market environments. Although a useful starting point, the PLC model is more controversial than its widespread adoption by analysts of industrial dynamics might suggest. 5 Even within manufacturing there are doubts about its generalisability and it has been suggested that the model may be particularly applicable to mass-production and is less valid in the ‘Post-Fordist’ era of ‘flexible specialisation’ (Piore and Sabel, 1984). One particular problem concerns the issue of how the industry/product life cycle relates to the life cycle, if such a thing exists, of the underlying technology or production platform upon which each product is based. Barras (1986) adapted the standard PLC model in an attempt to theorise the evolution of services, and thus innovation in services. Barras suggested that innovation in services has largely been driven by the adoption of technological innovations, particularly information and communication technologies (ICTs), developed in the manufacturing sector. He proposed a three-stage model of services evolution. First services adopt, for their own use, technologies developed elsewhere (especially in manufacturing). Innovation in this phase is largely process orientated, and centred on improving the efficiency of service production or delivery, because outputs are essentially standardised (i.e. undifferentiated between customers, with rival firms providing readily comparable services). In the second phase service providers develop new produc5 Teece (1986) contends that the model is most suited to mass markets where consumer tastes are homogeneous, and several authors (e.g. Abernathy, 1978; Pavitt and Rothwell, 1976; Porter, 1983) have also argued that the model does not hold for industries in which there are not rich opportunities for both product and process innovation. Su`arez and Utterback (1995) emphasise that the model may only hold for assembled manufactured goods, and it is clear that the definition of an industry is central to the model. Su`arez and Utterback (1995, footnote 2) admit that ‘the notion of an “industry” is somewhat obscure, for its limits are difficult to define.. . . We think of an industry as composed by a product class, i.e. a group of similar products that serve the same market need and thus compete directly in the market place’. Klepper (1996) subscribes to the same view, making several references to ‘the (industry’s) product’.

tion systems, focused on improving the quality of the services provided — a greater variety of service offerings are provided by each firm, and competition between firms turns to quality rather than just price. Eventually, in the third phase, many new services are produced, so that there is more emphasis on product innovation than on process innovation — thus the reverse product cycle. This last phase is also associated with the entry of new entrepreneurial firms, which adds to the diversity of service offerings to the market. Standardisation of outputs across the industry consequently declines and it becomes more difficult to make direct comparisons between the service offerings of different firms. Within individual service firms the services provided are increasingly tailored to individual clients or niche markets, although for larger niches standardised outputs are still provided. Barras developed his theoretical ideas in the course of empirical investigations, primarily in the banking sector and other information-based services. The reverse life cycle model has been widely criticised (see for example, Buzzacchi et al., 1995, and especially Uchupalanan, 1998, 2000). One reason for caution in accepting the model is that it effectively generalises from a limited set of case studies mainly in one sector to all service activities, but another is that it is focused on just one period in the evolution of services — that associated with the adoption and use of ICTs. 6 Beyond this, it also accords almost no role for strategy and differences between firms, implying that all firms in a sector adopt basically the same strategy, for technologically determinist reasons. Non-technological innovation is also overlooked (Gallouj, 2000; Sundbo, 2000). Despite these criticisms, there are some features of life cycle models that are worth noting for our own analysis. The first is the relationship between (average) firm size, variety and standardisation. Standardised outputs tend to be associated with large firms, due to scale economies, and from this perspective it is notable that service firms tend to be small, or very small, both 6 Arguably, Barras’ model is more robust as a model of technology adoption than of innovation — it has marked resemblance to classic accounts of the technology transfer process — although even here it may be rather specific to a particular era and set of technologies, rather than forming a general model of technology adoption in services.

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in absolute terms and relative to manufacturing firms (Eurostat, 1999). There are of course several important exceptions, notably in banking and finance, transport and communications, and to some extent, retailing, but the preponderance of small firms would lead us to expect a relatively high level of heterogeneity in service outputs. This said, there are several reasons for qualifying this statement. Firstly, the predominance of small firms is in part a reflection of services traditionally supplying very local markets and the need to physically locate in close proximity to the customer base. Telecommunications are being used to break down this relationship, particularly where standardised services are concerned. Traditionally, relatively few of the small firms were suppliers of highly specialised niche services. The dominance of small firms in services may also reflect the prevailing appropriation conditions for ‘product innovation’ in services, in that it may be more difficult to protect these from imitation, compared with product or process innovations in manufacturing, or process innovations within the service sector. More generally, this problem of copying may mean that firm growth on the basis of service (as opposed to process) innovation may be relatively rare in service activities. 7 Arguably, this also relates to the nature of product life-cycles in services, for a service standard may emerge, but it is less clear that a small number of firms will dominate the market (unless scale economies and process innovation are important and lead to the ‘selection’ of the most efficient producers). 2.2. Taxonomic models of specialisation and innovation in services The second theoretical approach to understanding services and innovation in services we consider is that of the various taxonomic models. In contrast to the life cycle models, these taxonomic models tend to consider the extent of specialisation rather than the extent of standardisation in services, although these issues are clearly related. In his celebrated 1984 paper, Pavitt argued that sectors have different patterns of (product and process) innovation, and develop technologies for different reasons. Reflecting this, he provided a fourfold 7 See Miles et al. (2000) for discussion of this position and the weak support it receives from survey studies.

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classification of ‘sectoral technological trajectories’: ‘supplier dominated’, ‘scale intensive’, ‘specialist suppliers’, and ‘science based’. Within this classification, Pavitt described (market) services as ‘supplier dominated’, and thus essentially as recipients of (embodied) technologies developed elsewhere, rather than as producers of new technologies. Amongst supplier-dominated firms, competition tends to be based on the skills of the workforce and price, rather than on technological advantages. This description would apply to firms in the first stage — or yet to embark on — Barras’ reverse product cycle. In a later development, and inspired by the work of Barras (1986) amongst others, Pavitt (Pavitt et al., 1989) added a new classification of ‘information intensive’ to his model. 8 This classification emphasised the importance of ICTs in an innovation trajectory based on information processing and providing related products, and it is notable that this classification related particularly to two service sectors — financial services and (large scale) retailing. Not long after, and inspired by Pavitt’s (1984) classification, Soete and Miozzo (1989, see also Miozzo and Soete, 2000) considered the innovative styles of service activities more directly. In particular, they identified four types of service business: 1. Supplier dominated sectors. For example, public and social services, such as education and administration, and personal services, together with the retail trade. These remain subject to the limitations of Pavitt’s original characterisation of services as ‘backward’ adopters of technologies developed by manufacturers. 2. Production-intensive, scale-intensive and network services. These services, in contrast, involve considerable divisions of labour with the simplification (and co-ordination) of production (and/or delivery) tasks, and the substitution of (skilled) labour by machines. The application of this organisational logic, and technological innovation, encourages the standardisation of service outputs, or, in more sophisticated systems, the adaptation (through customisation) of standard services to

8 Barras’ subsequent work (Barras, 1990) was in turn influenced by Pavitt (1984).

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particular user needs. Within this group, two types of services can be distinguished: 2.1. Network services, which are dependent on ICT networks (e.g. banks, insurance and telecommunication services). The development of ICTs has facilitated improvements in the complexity, precision and quality of the services offered by these providers; they have especially facilitated customisation, but have also had an important role in setting standards in many service activities. 2.2. Scale-intensive services. These are dependent on physical networks (e.g. transport and travel services, wholesale trades and distribution), which are less flexible than ICTs in terms of facilitating customisation, but do provide economies of scale and of scope. In these services there is also a heavy dependence on hardware technologies developed in the manufacturing sector. 3. Specialised technology suppliers and science-based services (e.g. software and specialised business services). The main source of technology here is the innovative activities of the services themselves, which are geared to the provision of outputs designed to suit the needs of particular users, or groups of users. Soete and Miozzo emphasise that sectors, as conventionally conceived, can reside in more than one of their categories. They cite the communications sector, which is both a large scale-intensive sector and a science-based, specialist supplier sector. Another example is retail trade: whilst small independent shops are largely supplier dominated, the retail multiples are much less so. Large retailers tend to use both physical and information networks to achieve economies of scale and scope. The strength of the Pavitt and Soete–Miozzo typologies is that they emphasise diversity, both in relation to the activities of firms, and in relation to the nature and purpose of their innovation activities. This diversity is also associated with different patterns of innovation with respect to firm size. Supplier-dominated and specialist supplier firms tend to be relatively small, whereas scale-intensive, information-intensive and network services tend to be large-scale operations.

Because of this diversity it is difficult to generalise about competitive strategies, and the role of innovation in competitive strategies. In routine services, or services amenable to high levels of standardisation, cost has often been the basis of competitiveness, and thus cost reduction has often been the primary motivation for innovation. 9 However, there are many service activities which emphasise quality, and customer satisfaction, over price competition (Tether and Hipp, 2000). Frequently, achieving advantages in terms of quality and customer satisfaction requires close interactions with the service user, and an increase in the variety of services provided. Perhaps the most significant weakness of the Pavitt and Soete–Miozzo taxonomies in relation to services is their heavy emphasis on technology (and technological innovation) in a narrow sense. Non-technological change is overlooked. This leads to a privileged role for information communication technologies (ICTs) — in Pavitt’s ‘information intensive category’ and in Soete–Miozzo’s network services — similar to the privileged position Barras (1986, 1990) gave these technologies. This is understandable, given the wave of ICT introduction into services in the 1980s and 1990s, and the excitement that this generated amongst managers and industry commentators. But there is a danger that services and their dynamics will become so closely associated with the application of ICTs that other forms of change, and strategic choices, become overlooked. 10 More generally, Gallouj (2000) presents a strong case against approaches that focus exclusively on technological dynamics in services, stressing the intertwining of technical and organisational changes in service innovation and in process innovation within services. Not all researchers privilege technology (and technological innovation) in considering service activities. 9 In services, cost reduction can take many forms, such as reducing rents by re-locating ‘back office’ functions to cheaper locations, or reducing labour costs by replacing expert labour with expert systems, or exerting greater control (or order) over the production process by standardising procedures and thereby attempting to eliminate inefficiencies. 10 The focus on ICTs in services is reminiscent of the focus on R&D within studies of (technological) innovation in manufacturing. It is now widely appreciated that R&D is only one of several inputs to innovation in manufacturing (Rothwell, 1992), and it should be recognised that innovation in services extends well beyond the adoption of ICTs.

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Some have differentiated service activities by the nature of their activities, particularly in relation to how they interact with clients/customers. For example, Silvestrou et al. (1992) define two extreme categories of service organisations: (1) Professional service organisations which have relatively few, highly customised, process-oriented transactions, with relatively long client contact times associated with applying considerable judgements to meeting customer needs, and (2) Mass service organisations which have many customer transactions that typically involve short client contact times, little client specific judgement and little customisation. (A third category, that of service shops, is described as falling between these two extremes in terms of the features described above.) In a related approach, de Jong (1994) distinguished between: infrastructure services; value added services; pre-specified services and ad hoc services. Infrastructure services include telecommunications and transport services, which make use of fixed network facilities and provide standardised services. Value added services include accountancy and are highly specialised but are used by different types of businesses. Pre-specified services are services that use a standard approach or method in order to satisfy a general demand, such as repair, maintenance and cleaning services, whilst ‘ad hoc’ services include management and engineering consultancy services and are called upon for specific, one-off problems. De Jong considers that the potential for pursuing economies of scale and scope can be represented in terms of the (potential) degree of standardisation or variety in the services offered. Consequently, it is likely that innovation dynamics will differ across these types of services — perhaps with opposing tendencies toward standardisation and flexibility. Another contribution, from Sundbo and Gallouj (2000), looks at the organisation of services, and the relationship between this and the patterns of innovation in services. Sundbo and Gallouj distinguish between several patterns of organisation and innovation in services: (1) the classic R&D pattern of large firms producing standardised mass information or mass material services; (2) professional organisations which depend heavily on the knowledge and expertise of their personnel to solve customer specific problems; (3) the managerial model (or ‘the organised strategic innovation pattern’) common to most (large) service

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firms, which is based on the identification of markets and the production of reproducible products; (4) the entrepreneurial pattern based around introducing radical innovations; (5) the artisanal pattern of (generally small) craft based organisations which lack any clear innovation strategy; and (6) the network pattern where enterprises join together to form an association or separate company dedicated to seeking innovations for the network. Thus, Sundbo and Galouj highlight the variety of service organisations and their patterns or approaches to innovation. They also point out, as Uchupalanan (2000) demonstrates for the banking sector, that an individual firm may select different innovation patterns for different aspects of its activities. Yet, Sundbo and Gallouj (2000) still stress the specificities of services innovation — in particular, the way in which the service relationship between provider and customer is a major influence on service activities and innovation in services (see also Gallouj and Weinstein, 1997). What all of these typological approaches stress is the diversity that exists amongst services. This diversity relates to what they do, that is, to what is transformed (Miles, 1996), the tangibility or intangibility of their transformation processes and, of particular interest here, to the extent to which their outputs are standardised and the nature and intensity of their relations with customers or clients. We should note that the firm will often make choices about its interactions with its clients/customers both on a long term, strategic basis (for example, in terms of what broad set of services to provide), and on a short-run tactical or operational basis (for example, in terms of whether or not the general service should be adapted to suit a particular user’s request). To some extent, this provides a conceptual difference between the provision of variety and genuine innovation, and in relation to the former, we end this section with a consideration of when firms are likely to adapt their services to fulfil the requirements of particular customers. 2.3. Variety generation and the question of whether or not to adapt services In considering whether a firm will provide a specific service in relation to a customer’s request, it is useful to distinguish between the variant requested or produced and the generic service (which is itself based

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on a set of more or less flexible production routines) on which it is based. Thus, here we consider the case where a customer requests sαβ , a possible variant of the generic service gα , and where, although the firm provides other specific variants of gα (such as sα 1 ), it does not currently provide sαβ . Under what conditions might the firm be expected to provide sαβ ? Clearly, whether the firm is prepared to provide sαβ will depend partially on its willingness and capabilities to do so (and thus on organisational attitudes and long term strategic decisions about the development of flexible capabilities), but also on more conventional economic criteria, particularly as these apply to the short-run operational decision as to whether or not to provide the service. It is also worth noting that the long run decision as to whether or not to provide the variant may differ from the short run decision. However, the (short run) economic criteria are likely to include the cost of adapting and supplying the service, the income expected from the ‘new’ service (price × volume), the extent to which the provision of the new service might undermine the firm’s existing markets (especially if it is a low price service and a possible substitute for existing services), the expected profitability of the ‘new’ service (vis-à-vis existing and other possible service variants), the importance of pleasing and maintaining the customer(s) requesting it, the perceived importance of the market segment, the legality and regulatory context of provision, and the expected reaction of competitors. Not all of these will be fully known, particularly in the short-run and especially if the firm has to react quickly without taking all of the factors into consideration. Moreover, if the firm is prepared to provide sαβ , but only at a premium price, the customer will have to decide the extent to which it values sαβ over existing variants (to justify the price premium), and the extent to which it might expect to find another, lower price, provider of sαβ . Again, this decision is likely to be made with limited rather than full information. Decisions may also be made on ‘irrational’ bases, associated more with social practices or behavioural norms, than with rational economic behaviour. From a (rational) provider’s perspective, it is perhaps easier to conceptualise the conditions under which the firm is unlikely to provide sαβ rather than the conditions under which it will be provided. These are when the cost of provision is high, the profitability low or negative, and/or the customer and market

segment is considered unimportant. Finally, we note that when the cost of adapting a service is high, and customers are in general price sensitive, this will encourage standardisation.

3. The survey data and sample characteristics In this section we introduce the data set used for the empirical analysis and the basic categories we employ. We also begin the empirical analysis, investigating the size and sector characteristics of the surveyed firms, and the interaction between these. The data set we use is the response to the 1995 survey of innovation in German services companies. 11 Only commercial service firms were included in the survey. The sectors included were wholesaling, retailing, transport and communications, banking and insurance, scientific and technical services, software and other business oriented services. Amongst the service sectors excluded were public administration, education, health care, hotels and catering, personal services, and other non-business oriented services. There is thus a possibility that the more (technologically) dynamic service sectors have been surveyed. The sampling also excluded micro-businesses. More than 11,000 service companies were sent the questionnaire, and 2900 responded (see Licht et al., 1995 for a detailed discussion of the sample). Thus, the overall response rate was 26%, which is reasonable for a voluntary postal questionnaire survey to companies in Germany. The response rate was slightly higher than average amongst banking and insurance, technical services and software firms (at around 30%), and below average amongst trade services firms (24%). Participation also increased (slightly) with firm size, and thus there is some bias towards larger firms, and firms operating in the more (technologically) innovative sectors. In the analyses that follow, no attempt has been made to weight the sample of responses to reflect the population of ser11 The survey was carried out by the Centre for European Economic Research (ZEW), the Fraunhofer Institute for Systems and Innovation Research (FhG-ISI) and the Institute for Applied Social Research (INFAS), on behalf of the German Ministry for Research and Technology. CREDITREFORM, the largest credit-rating agency in Germany, provided the database which provided both the sampling frame and background information on the companies.

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Fig. 1. The size distribution of the sampled firms by sector.

vice firms or their employment in Germany. We feel the sample is too small, and the theoretical and empirical state of the subject matter too embryonic to permit the heroic assumption that the pattern of response in the sample was representative of service firms in Germany. Instead, the analyses simply reflect the response to the survey. In the analyses which follow, the firms are classified into eight sectors: trade (including retailing and wholesaling); transport and communications (T&C); banking and insurance (B&I); other financial services (OFS); software; (scientific and) technical services (Technical); other business services (OBS); and an ‘other’ group of otherwise unclassified companies. 12 This grouping reflects the usual classification of services by statistical agencies, but bears some relation to the different types of service activities

12 Other business services includes services such as accountants, advertising agencies and consultants. The ‘other’ group includes cleaning and waste disposal, publishing, rental services, and real estate services.

suggested by de Jong, Miles, Pavitt, Silvestrou et al. and Soete–Miozzo. 13 Based on those accounts, we might expect that small trade and transport and communications firms tend to be ‘supplier dominated’, whilst the larger firms in those sectors tend to be ‘information intensive’ and/or ‘network based’ (Pavitt, 1984; Soete and Miozzo, 1989). Banking and insurance tend to be large-scale, mass service activities (Silvestrou et al., 1992), based on scale and network/infrastructural economies (Pavitt, 1984; Soete and Miozzo, 1989; de Jong, 1994). Fig. 1 and Table 2 show that these firms do indeed tend to be large. Other financial services, software and technical services, on the other hand, tend to be micro and small, in keeping with their characterisation as ‘specialist suppliers’ by Soete and Miozzo (1989) or as ‘professional service organisations’ by Silvestrou et al. (1992). They also include what de Jong (1994) classifies as ‘value added’ and ‘ad hoc’ service providers. However, it 13 We also had to be mindful that the number of firms in each category was adequately large for quantitative analysis.

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Table 2 Sampled distribution of firms by size and sector Number Retail and wholesale trade services (Trade) Transport and communications (T&C) Banking and insurance (B&I) Other financial services (OFS) Software Technical services Other business services (OBS) ‘Other’ services Full sample

% of sample

Median employment

Mean employment

740 394 262 135 144 291 302 616

26 14 9 5 5 10 10 21

32 39 118 10 26 23 47 55

642 1709 1001 52 89 149 450 619

2885

100

40

690

is important to note that all sectors include both micro and large-scale operations, and that while the mean and median size of firms varies across sectors, each sector contains considerable internal diversity. Such diversity is repeatedly encountered in the analyses below. Simple classifications tend to emphasise homogeneity within groups, but the reality is diversity within sectoral (and other) groupings. Overall, a fifth of the firms were classified as ‘Micro’ operations (with fewer than 10 employees), 14 a third were ‘Small’ (10–49 employees), a quarter were ‘Medium sized’ (50–249 employees), and a fifth were ‘Large’ (250 or more employees). 4. Standardisation and particularisation The survey approached the ‘standardisation’ or ‘particularisation’ of the firms’ outputs by asking the companies to divide their sales (in 1994) into three components: (1) that earned from ‘standard services’ (i.e. ‘those without customer specific changes’), (2) that earned from ‘partially customised services’, and (3) that earned from ‘bespoke (i.e. one-off, custom-made) services’. This is an interesting question, given the supposed characteristics of services, particularly in terms of how service firms are assumed to interact with their customers to produce bespoke or customised services. Of the 2900 firms, 2151 answered this question (74%). The distribution of firms by the percentage distributions of their sales is shown in Fig. 2 (which 14 Firms with fewer than five employees were not supposed to be included in the survey.

treats all firms equally, and does not weight them by their sales). The distribution is striking. The proportion of firms indicating all of their sales were due to ‘standardised services’ (i.e. their output involved no customer-specific changes) was substantial, at 24%. But the proportion which declared all of their sales were due to ‘partially customised services’ was small, at 4%, whilst not a single firm declared all of its sales were due to ‘bespoke services’. Moreover, less than a fifth (17%) of the firms indicated that a high proportion (i.e. more than two-thirds) of their output by sales was in the form of ‘bespoke’ and/or ‘partially customised’ services. This is remarkable, for a quite different distribution might have been anticipated, with large proportions of the firms indicting that all (or the larger part) of their sales were due to ‘bespoke’ or ‘partially customised’ services. Instead, the firms tended to emphasise the standardised nature of most of their output (as reflected in the distribution of their sales income). In addition to the 24% of firms which said all of their sales were due to ‘standardised services’, another 42% declared that at least two-thirds (but less than all) of their sales were due to ‘standardised services’, and only 17% said ‘standardised services’ accounted for less than one third of their output by sales. 15 4.1. The definition of standardised, partially customised and bespoke services Unfortunately, the survey did not define standardised, partially customised or bespoke services further, 15 Including the 4% that said none of their output was ‘standardised’.

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Fig. 2. Standardised, Customised and Bespoke Services. The distribution of the firms by the composition of their sales.

and the question used in the survey is admittedly open to some interpretation. An initial logical distinction can be made between bespoke and standardised services such that services which are produced only once can be considered bespoke, whilst those that are produced more than once can be considered standardised. Interestingly, it is possible for bespoke services to dominate in terms of the number of services provided by the firm whilst (at the same time) standardised services dominate in terms of income to the firm (because income is dominated by a few, standardised, services). Because of the nature of the question, the analysis here has to focus on the income from the different types of services, rather than the number of services provided, or the effort put into them. Customisation introduces a new dimension. For customisation requires attention is paid to the firm’s production base as well as its revenue generation. Adaptation is the essence of customisation. By affirming that it provides some customised services, a firm is implicitly recognising a distinction between at least two levels of service provision — the generic and the specific (which relates back to the discussion above). Through customisation, (actual and potential) specific services are derived from a set of generic services, each of

which is based on a ‘production platform’ of skills, routines and/or equipment. Thus, the firms’ ‘production platforms’ or aspects of them can be shared across many of their specific services; specific services being the actual forms in which the generic services are being provided. For example, a retail chemist (i.e. pharmacist) might provide three generic services: (1) selling over the counter remedies, (2) preparing prescriptions, and (3) providing a photograph development service. Within each of these generic services, it may offer one or more specific services. For example, within the generic photo-development service it may develop photographs, make enlargements, and offer a framing service. 16 Since three quarters of the firms responding to the questionnaire claimed that some proportion of their income was due to ‘partially customised’ services, three-quarters of the respondents implicitly recognised this distinction between the production platform 16 Clearly, each of these services could potentially be disaggregated further. For example, the chemist may be able to develop photographs to different sizes (15 cm × 10 cm; 17.5 cm × 12.5 cm, etc.). It is because the level of aggregation is not always clear that division between generic and specific services is a matter of interpretation.

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(or generic service) and the specific services provided. Whilst beneficial for this reason, the presence of customisation in the classification also confuses the simple distinction between standardised and bespoke services. It is, for example, particularly difficult to maintain a clear and logical distinction between services that are ‘partially customised’ and those that are ‘bespoke’, and whilst it is possible to develop logical rules to divide a firm’s sales into that from ‘standardised’, ‘partially customised’ and ‘bespoke’ services, there is no guarantee that the firms followed this logic. Thus, the division of a firm’s income into these categories is to some extent arbitrary, 17 and two identical firms might classify their outputs in different ways. Arguably, the classification of income into these categories is particularly difficult for small firms, in which the number of times a service (or a service variant) is produced (within a given period) tends to be small relative to that in large firms. Despite the problems of the indicator, and the arbitrary elements of the underlying classification, the distinction between these different types of services does help us consider, both conceptually and empirically, the nature and extent of variation in service provision. Standardisation implies high production volumes and relatively distant relations with the customer (since little information is required from the consumer to specify the product). Bespoke service provision (and to a lesser extent customisation) implies low production volumes and close relations with the customer. It is likely that standardised services tend to arise in price sensitive markets where there are economies of scale, and where production is routine, with high costs of adaptation, and which involve standard or inflexible technologies and a relatively low cost labour force (which is likely to be a labour force with a relatively low level of educational attainment). Services to households, and the most routine or frequently purchased business services might be expected to exhibit high levels of standardisation. Bespoke services, by contrast, tend to be more expensive, often depend on highly educated employees 17

For example, the chemist discussed above might consider its routine preparation of prescriptions to be either a standardised or partially customised service; while infrequent services, such as the preparation of rare enlargements or of unusual prescriptions might be considered either partially customised or bespoke services.

with considerable ‘knowledge capital’ (rather than on machines, i.e. embodied capital), and appeal to less price sensitive (business) markets. Customised services are more ambiguous. Their provision will depend on, amongst other things, economies of scope and the costs associated with customisation (and the existence and use of flexible technologies to reduce these), as well as the extent to which customers are prepared to pay (or can be persuaded to pay) different amounts for different variants. This permits discriminatory pricing. Consequently, when there are significant economies of scope, the cost of customisation is low and where customers are prepared to pay different amounts for the similar service variants, customised services will in general be provided. By contrast, if the cost of customisation is high, and customers are not prepared to pay the price differentials due to customisation, then irregular variants are only likely to be provided to those whose custom is especially valued by the service provider. We should note that both the cost of customisation and customers preparedness to pay different amounts for similar services are not necessarily fixed, and firms can put a great deal of effort into changing these circumstances with a view to providing customised services which tend to have lower unit production costs than bespoke services but earn higher unit profits than standardised services. 4.2. Income related to ‘standardisation– particularisation’: sectoral analysis The problem of classification discussed above at the micro level creates problems of interpretation at the industry level. An industry composed of a large number of small firms, each producing what for them are standardised services, but which differ one from another, may exhibit as much variety as an industry dominated by large firms providing relatively high levels of what they describe as partially customised or bespoke services. On the other hand, variety will be minimised in an industry providing a relatively small number of distinct services, especially if this is associated with a relatively small number of (generally large) firms providing ‘standardised’ outputs. Fig. 3 reports the distribution by sector of the income received by the firms, according to their own classification of this income, into that for ‘standardised’, ‘partially customised’ and ‘bespoke’

B.S. Tether et al. / Research Policy 30 (2001) 1115–1138

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Fig. 3. The composition of sales by sector.

services. These distributions are displayed in two ways: first according to the mean proportions across all firms in the sector, and second in terms of the sum of the incomes in the three categories amongst the firms in each sector (which is equivalent to the mean proportion weighted by the sales of the firms). 18 With few exceptions, it was surprising how close these proportions were. Across the full sample, the simple mean distribution of income was 70% ‘standardised’, 21% ‘partially customised’ and 9% ‘bespoke’ — the
n 18 The first set of proportion are, s¯ = i=1 (Si /Yi )/n, c¯ =
n
n ¯ (C /Y )/n, and b = (B /Y )/n, where Yi is the total i i i i i=1 i=1 income of the firm i (i = 1, . . . , n), which is composed of income from ‘standardised services’ (Si ), ‘partially customised services’ (Ci ) and ‘bespoke services’ (Bi ), (i.e Yi = Si + Ci + Bi ). n is the number of firms in the sample — here analysed
by the individual
sectors. The second set of proportions are: sˆ = ni=1 Si / ni=1 Yi ,
n
n
n
n cˆ = i=1 Ci / i=1 Yi and bˆ = i=1 Bi / i=1 Yi where the symbols are as before. While the second distribution is strictly more accurate in displaying the breakdown of each sector’s income, it is vulnerable to distortion by the classification of income amongst the largest firms (as these dominate the weightings). The simple means, which treat all firms equally regardless of size, are less affected by the classifications of the largest firms, but may not give a sense of the extent of standardisation–particularisation of income in each sector of activity.

corresponding weighted proportions being 67, 25 and 8%. Fig. 3 ranks the sectors, from left to right, according to how much they earned from ‘standardised services’. Perhaps unsurprisingly, trade services tend to be most standardised, followed by transport and communications, banking and insurance and other business services. In all four of these sectors, ‘standardised services’ accounted for 70% or more of income, and two-thirds or more of the income of the average firm. ‘Partially customised services’ accounted for between 11 and 27% of the income to these sectors, whilst ‘bespoke services’ accounted for 10% or less of their income, and (unsurprisingly) just 1% of income in the transport and communications sector. By contrast, in technical services and other financial services just over half of total income was due to ‘standardised services’, whilst 25–30% was due to ‘partially customised services’ and the remaining 16–18% was due to ‘bespoke services’. These relatively high rates of particularisation could be expected in such sectors, characterised by Soete and Miozzo (1989) as ‘specialist suppliers’. Meanwhile, in software 76% of the income was due to ‘standardised services’, with 15% from

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Fig. 4. The distribution of the firms by the ‘standardisation–particularisation’ classification.

‘partially customised services’ and 9% from ‘specialised services’, a distribution similar to that of the first four sectors. But in terms of the distribution of income in the average software firm, the distribution was 52% standardised, 30% partially customised and 19% bespoke. This difference is due to different distributions of income amongst small and large software firms: larger firms tend to earn more from ‘standardised services’, at the expense of ‘partially customised’ and ‘bespoke services’. 19 The case of software illustrates how the division of income from ‘standardised’, ‘partially customised’ and ‘bespoke’ services can vary within sectors across the firm size distribution. In the next sub-section, we divide the sample of firms into four categories based on their response to the standardisation–particularisation question, before analysing the relationship between firm size, sector of activity and ‘standardisation– particularisation’. 19 Amongst the miscellaneous ‘other’ category the opposite occurs — as firms in this category become larger their provision of partially customised services tends to increase at the expense of standardised services.

4.3. Income related to ‘standardisation– particularisation’: a categorisation of firms While accepting the problems of interpreting the question concerning the distribution of the firms’ incomes from ‘standardised’, ‘partially customised’ and ‘bespoke services’, the indicator can be applied usefully to classify the firms into four simple groups. The first, which we call the ‘Wholly Standardised’ (WS) service providers, was composed of those firms that declared all of their sales were due to ‘standardised services’. The second, denoted ‘Largely Standardised’ (LS) service providers, was composed of the firms which declared at least two-thirds, but less than all of their sales were due to standardised services. The third group, of ‘Bespoke’ (BS) service providers, was composed of the firms that declared more than a third of their sales were due to ‘bespoke (i.e. one-off, custom-made) services’. Lastly, we classified the remainder, which were mainly firms with relatively high proportions of their income from ‘partially customised’ services, as ‘Customised’ (CU) service providers. The distribution of firms according to this categorisation is shown in Fig. 4.

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This classification has of course some arbitrary elements. Not only does the position of the firms reflect the perception of the respondent, as discussed above, rather than the application of a standard measure, but the ‘cut-off’ points chosen for the categories other than the ‘Wholly Standardised’ group could also have been different. Nevertheless, the analysis that follows demonstrates that the classification, however crude, has some value for empirical investigation. Table 3 assesses the distribution of firms by size and by broad sector of activity in terms of this ‘standardisation–particularisation’ classification. Some notable patterns emerge from these classifications. Perhaps curiously, the proportion of ‘Wholly Standardised’ service providers in each size classification did not vary significantly across the size distribution. Meanwhile, the likelihood of a firm being classed as ‘Largely Standardised’ increased with firm size, and the likelihood of a firm being classed as a ‘Customised’ or a ‘Bespoke’ service provider declined with firm size. Compared with large firms, micro firms were twice as likely to be classified as ‘Bespoke’ service providers. Generally, this is in keeping with expectations. We would expect that large firms would seek scale economies through the standardisation of their outputs, although often using ‘flexible’ production technologies (including ICTs) to

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facilitate partial customisation. Alternatively, many firms that become large do so through the provision of standardised services. As mentioned earlier, the interpretation of the position of the small firms is more problematic, because, from their perspective, the classification of low volume outputs as ‘standardised’, ‘partially customised’ or ‘bespoke’ is more debatable than for large firms. Turning to the sector of activity, the first notable feature is that all of the sectors had at least a few firms in each of the classes, although the proportions in each varied. In Table 3 the sectors are ranked, from highest to lowest, according to their proportion of ‘Wholly Standardised’ firms. The trade sector and ‘other’ group of firms both had relatively large proportions of ‘Wholly Standardised’ firms, whereas firms in the software, other financial service and technical service sectors were significantly more likely to be ‘Bespoke service providers’. Trade services especially, but also banking and insurance, and transport and communications, might be expected to be largely volume based and price sensitive, and thus more oriented to ‘standardisation’. Another reason for standardisation in these ‘mass service’ sectors is regulation, with respect to non-discrimination between insurance customers or safety in transport, for example. By contrast, other business services, other financial services and

Table 3 Firm size, sector and standardisation–particularisationa Size and sector (row percentages)

Standardised

Customised (%)

Bespoke (%)

Number

Wholly (%)

Largely (%)

1–9 employees 10–49 employees 50–249 employees 250 + employees

27 24 22 26

34↓↓ 39↓ 48↑↑ 46↑

30↑ 28 24↓ 24

10↑ 8 7 5↓↓

387 747 588 423

Trade Transport and communications Banking and insurance Other business services Other financial services Technical services Software

29↑↑ 26 24 18↓↓ 14↓↓ 11↓↓ 6↓↓

44 44 49↑ 45 22↓↓ 35↓ 33↓↓

21↓↓ 27 23 28 46↑↑ 28 44↑↑

5↓ 2↓↓ 4↓ 10 18↑↑ 27↑↑ 18↑↑

602 314 189 204 100 149 110

All firms

24

42

26

7

a

2150

The arrow symbols indicate significant differences between the observed proportions and those ‘expected’ if there were no difference between sectors or firm sizes in the ‘standardisation — particularisation’ distribution of firms. Upwards arrows (↑) indicate the observed proportion is significantly greater than that ‘expected’, whilst downward arrows (↓) indicate the observed proportion is significantly smaller. Single arrows indicate significance between 10 and 5%, and double arrows indicate significance below 5%.

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technical services tend to be low volume with higher levels of customisation and bespoke service provision. Software deserves special note. For, whilst software is generally associated in the popular mind with standard packages (the market dominated by Microsoft), much of the software industry in Europe is concerned with undertaking bespoke projects for specific clients or adapting (i.e. customising) standard packages for particular users. Generally, our findings with respect to the sectors are in line with the taxonomic suggestions of Soete–Miozzo and others, but in order to investigate the relationship between firm size, sector of activity and ‘standardisation–particularisation’ more fully, we undertook logistic regressions. These were four logistic regressions (see Table 4), with each of the ‘standardisation–particularisation’ classifications being, in turn, the dependent variable, and with size and sector as the independent variables. The analysis addressed whether, in each sector, the probability of a firm being in each of the categories varied with firm size. This found that in the trade sector the probability of a firm being ‘Largely

Standardised’ increased with firm size, whilst its probability of being a ‘Customised’ or a ‘Bespoke’ service provider declined with size. In the transport and communications sector the probability of a firm being a ‘Wholly Standardised’ or a ‘Bespoke’ service provider declined with firm size, whilst the probability that it was ‘Largely Standardised’ increased with size. In banking and insurance the probability that a firm was a ‘Bespoke’ service provider declined with size, whilst amongst the other financial service firms and the ‘other’ firms the probability of being ‘Wholly Standardised’ declined with size. Amongst other business services the probability of a firm being a ‘Largely Standardised’ service provider increased (weakly) with size. In software the probability of a firm being a ‘Customised’ service provider declined with size, whilst that of being a ‘Largely Standardised’ service provider increased (weakly) with size. One interpretation of this pattern is that small software firms tend to be concerned with adapting (i.e. customising) standard packages for their clients’ particular

Table 4 Logistic regressions — ‘standardisation–particularisation’ by sector and firm size Wholly Standardised (WS = 1) Trade (dummy = 1) T&C (dummy = 1) B&I (dummy = 1) OFS (dummy = 1) Software (dummy = 1) Technical (dummy = 1) OBS (dummy = 1)

−0.316 −0.568∗∗ −0.136 −0.818∗∗∗ −0.604 −2.535∗∗∗ −2.927∗∗∗ −1.224∗∗∗

Trade × ln(Emp) T&C × ln(Emp) B&I × ln(Emp) OFS × ln(Emp) Software × ln(Emp) Technical × ln(Emp) OBS × ln(Emp) ‘Other’ × ln(Emp)

× −0.145∗∗ × −0.370 (13%) × 0.294∗ × −0.116∗∗

Constanta

N Model χ 2 (d.f.) −2 log likelihood Nagelkerke R2

2146 91.6 (11) 2296.3 0.062

Largely Standardised (LS = 1) −0.339∗∗∗

−0.350∗ −0.298 0.286∗ −0.927∗∗∗ −1.165∗ −0.285 (14%) −0.358 0.119∗∗∗ 0.096∗ × × 0.226 (16%) × 0.112 (12%) × 2148 44.9 (11) 2875.6 0.028

Customised (CU = 1) 0.462∗ 0.177 −0.041 0.991∗∗∗ 2.143∗∗∗ 0.183 0.204

−3.311∗∗∗ 0.896∗ 1.165 (17%) 1.915∗∗ 1.795∗∗∗ 1.807∗∗∗ 2.309∗∗∗ 1.092∗∗∗

−0.163∗∗∗ × × × −0.371∗∗ × × ×

−0.155 (18%) −0.427∗ −0.443∗ × × × × ×

2149 56.1 (9) 2422.0 0.038

‘Other’ is the base category; ln(Emp): natural log of employment; ×: denotes deleted variable. Significant at 10%. ∗∗ Significant at 5%. ∗∗∗ Significant at 1%. a

∗

Bespoke (BS = 1)

−1.152∗∗∗

2147 126.7 (10) 1006.9 0.140

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requirements (or producing bespoke software), whilst larger software firms tend to be the suppliers of standardised packaged software (although some still specialise in providing bespoke software). Amongst the technical service firms the probability of being a Wholly Standardised firm increased with size. This is exceptional, and perhaps indicates the larger technical service firms were more likely than their smaller counterparts to be engaged in routine ‘standards checking’ rather than in consultancy activities. Overall, however, the effect of size on the ‘standardisation–particularisation’ categorisations of the firms tended to be weak, and it is tempting to conclude from this that sector rather than size is the more important determinant of the distribution of firms into the different ‘standardisation–particularisation’ classes. There are two caveats to such a conclusion. Firstly, it is important to remember that the sectors had different firm-size distributions in the first place. In particular, the software, technical service and other financial service sectors all had larger proportions of ‘Bespoke’ service providers and fewer ‘Wholly Standardised’ firms than the other sectors, whilst the firms in these sectors also tended to be smaller. By contrast, trade and ‘other’ enterprises were more likely than enterprises in the other sectors to be large and ‘Wholly Standardised’. Secondly, it is apparent that overall these regressions explain only a little of the total variation in the data. Thus, whilst sector, and to some extent size, have an influence, there are other factors that we have not been able to include in the regressions — an obvious example being firm strategy — which are likely to be at least as significant as size and sector. This emphasises the fact that firms can compete through different routes (as represented by the extent of standardisation or particularisation of their outputs) despite having similar positions in terms of size and sector.

5. Employment by qualifications, innovation and R&D activity

the firms, their innovation activity and (amongst innovators) their conduct of R&D. If the division between Wholly Standardised, Largely Standardised, Customised and Bespoke service providers has validity, we would hypothesise that: 1. The proportion of highly skilled employees should tend to increase with the level to which the firm particularises its outputs. Using university graduates as a proxy for high skilled employees, we hypothesise that university graduates as a proportion of all employees will be highest in the Bespoke and Customised firms, lower in Largely Standardised firms, and lowest in Wholly Standardised firms. 2. Secondly, in relation to innovation, we expect that innovation, and especially service innovation, will be more common amongst the firms that particularise a high proportion of their outputs. Process innovation, on the other hand, may be more common amongst the firms that provide wholly or mainly standardised outputs. 3. Thirdly, (amongst innovators — unfortunately the survey only asked this question of innovators) research and development activities should be more common amongst the firms that particularise a large proportion of their outputs. Thus, we hypothesise that the Wholly Standardised firms will be the least likely to conduct R&D, whilst the Bespoke and Customised firms will be the most likely to do so. 5.1. Employment structure The structure of employment by qualifications was addressed by the questionnaire, which asked firms to divide their employment between: those with university degrees, those with college degrees, those who had completed vocational training apprenticeships, and other employees. 20 Fig. 5 confirms that, as anticipated and across all the sectors combined, the proportion of highly qualified employees does tend to increase with the in20

Having explored the pattern of response in relation to the ‘standardisation–particularisation’ of service outputs, we now turn briefly to relate this classification of firms to some of their other features. In particular, we consider the employment structure of

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In assessing the proportional distribution of employment by qualifications, there are again two approaches — the simple or the weighted mean distributions. In fact, the average proportions found by the two measures differed only slightly, and the trends in the data were also very similar. For simplicity, we therefore present results derived by taking a simple average of these two proportions.

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Fig. 5. The structure of employment by qualifications.

B.S. Tether et al. / Research Policy 30 (2001) 1115–1138

creased particularisation of the firms’ outputs. About 9% of employees in the Wholly Standardised service providers were university graduates, compared with 13% of employees in the Largely Standardised service providers, 18% in the Customised service providers, and 28% in the Bespoke service providers. Fig. 5 also shows the proportional distributions of employment by qualifications in the different types of firms in the different sectors. (Because of the small number of observations in some sectors it has been necessary to combine some of the classes.) It can clearly be seen that, in five of the sectors (banking and insurance, other financial services, software, technical services and other business services), the anticipated pattern was discovered; the proportion of university graduates (and indeed graduates more generally) tended to increase with the increased particularisation of the firms’ outputs. Ignoring the miscellaneous ‘other’ classification, the two sectors in which the proportion of university graduates did not increase with particularisation were trade services and transport and communications. Amongst trade services, the proportion of university graduates was higher amongst the Customised firms, but not amongst the Bespoke service providers. This may be a spurious result, since ‘Bespoke’ firms represented only a small proportion of all trade firms. The Customised and Bespoke service providers amongst the transport and communications firms had similar proportions of university graduates to the Wholly Standardised service providers in that sector, but the Largely Standardised service providers had a significantly higher proportion of university graduates. This may be due to the presence of certain higher technology firms, particularly telecommunications firms, within the Largely Standardised group. Apart from the variation within most sectors, it is also notable from Fig. 5 that the proportion of graduates in the workforce varied widely between sectors. Amongst trade services university graduates accounted for just 7% of employees, but in software and technical services university graduates accounted for 40% of employees. Generally, and as expected, employment of university graduates tended to be higher in the specialist supplier/science-based sectors, and lower in the scale-intensive sectors (Pavitt, 1984; Soete and Miozzo, 1989). Considerable variation existed amongst the firms in each of the classes, which Fig. 5 does not depict.

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In general, however, the results concerning the proportional distribution of employment by qualifications support our initial hypothesis that the proportion of highly skilled employees will in general increase with the increasing particularisation of the firms’ outputs. Although we do not regard this as a complete explanation for the skills mix within the sectors, this evidence does support our classification scheme using the survey indicators. Additionally, this analysis demonstrates substantial variation between sectors in the structure of the firms’ and sectors’ employment. 5.2. Innovation and standardisation– particularisation We address the relationship between innovation and standardisation–particularisation at length in another paper (Hipp et al., 2000). Here, we merely summarise some of the findings from that analysis. We emphasise that the relationship between innovation and standardisation–particularisation is not simple. While it is tempting to describe any firm which declared that less than all of its output to be standardised as an innovator, there is, we contend, an important distinction between variety of output and innovation. For example, a garage which repairs cars provides, by definition, a customised (or bespoke) service, and therefore a variety of service activities. But such variety would not normally be described as innovation. Innovation requires more than the provision of variety, particularly if that variety is routine. Firms that customise their outputs, or even those that provide bespoke outputs, are not necessarily innovative. The ‘standardisation–particularisation’ classification did, however, relate empirically to the firms’ propensities to innovate (see Table 5). In particular, the ‘Wholly Standardised’ service providers were significantly less likely to innovate, both in general, and in either services or processes, than firms in the sample as a whole. No other significant differences were found between the three other groups of firms in either their general propensities to innovate, or their propensities to introduce each of the individual types of innovation. Yet, understanding the innovation dynamics of Wholly Standardised service providers poses problems. Are these firms Wholly Standardised because they are unimaginative and moribund, or are they

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Table 5 Standardisation–particularisation, innovation and R&Da Number of firms

Innovators of any type (%)

Service innovatorsb (%)

Process innovatorsb (%)

R&D performers amongst innovators (%)

2150 525 900 567 159

73 56 79 77 81

40 26 44 46 43

53 39 60 54 61

21 13 20 25 36

176 268 129 29

53 72 67 69

21 39 33 31

41 54 45 59

10 18 22 30

T&C — WS T&C — LS T&C — CU/BS

82 138 94

57 78 81

23 33 41

37 59 70

9 14 16

B&I — WS B&I — LS B&I — CU/BS

46 92 51

87 93 84

63 61 57

61 76 69

20 27 23

OFS — WS/LS OFS — CU/BS

36 64

61 75

42 50

44 39

9 13

Software — WS/LS Software — CU/BS

42 68

90 87

52 59

74 65

37 44

Technical — WS/LS Technical — CU Technical — BS

68 41 40

72 78 83

47 56 38

51 46 73

24 34 58

OBS — WS OBS — LS OBS — CU/BS

36 91 77

50 85 82

19 44 47

42 65 55

17 22 27

149 200 133

53 76 77

26 43 46

34 55 50

14 17 26

All All All All All

— — — —

Trade Trade Trade Trade

WS LS CU BS — — — —

WS LS CU BS

‘Other’ — WS ‘Other’ — LS ‘Other’ — CU/BS a b

WS: Wholly Standardised; LS: Largely Standardised; CU: Customised; BS: Bespoke. Hipp’s classification — see Hipp et al. (2000) for details.

successful service firms who have hit upon a successful formula that they are now exploiting (e.g. McDonalds)? One explanation for the lower propensity of Wholly Standardised firms to innovate might be that their service life cycles are longer, reducing the frequency of replacement and thus service innovation. But whilst this might explain the lower incidence of service innovation amongst these firms, it does not explain their lower incidence of process innovation, unless the ‘production platforms’ of skills, equipment and routines used to produce the services are also more stable amongst these firms. Another problem is that even if Wholly Standardised firms innovate less

frequently than those in the other groups, their innovations may be, on average, of greater commercial significance, affecting a wider range of clients. Unfortunately, the available data provide no information on these matters. What we can say is that the propensity to innovate does appear to be less amongst the Wholly Standardised service providers, although the reasons for this are unclear. The relationship between standardisation–particularisation is complicated further when firm size and sector of activity are controlled for, but overall the Wholly Standardised firms were still less likely to innovate than the firms in the

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other categories. In general, however, Bespoke and Customised service providers are not more likely to innovate than Largely Standardised firms, even when size is controlled for. 5.3. R&D activities, standardisation– particularisation and sector of activity With regard to R&D activities (amongst the innovating firms — as mentioned earlier this question was only asked of the firms which declared themselves to be innovators), the hypothesis was simply that the proportion of firms reporting undertaking R&D activities would increase with the increased particularisation of the firms’ activities. Table 5 shows that this expectation was confirmed. Only 13% of the innovating Wholly Standardised service providers claimed to be undertaking R&D activities, compared with 20% of the innovating Largely Standardised service providers, 25% of the innovating Customised firms and 36% of the innovating Bespoke service providers. To examine the conduct of R&D in more detail, we assessed the propensity to undertake R&D by sector as well as by standardisation–particularisation. These results are also provided in Table 5. (Again, some of the classifications have been combined because of small number problems.) This analysis shows that in most sectors the proportion of innovating firms undertaking R&D increased with the extent to which income was due to particularised services, with only banking and insurance defying this trend. In that sector the propensity to conduct R&D amongst the innovating firms was quite evenly distributed across the ‘standardisation–particularisation’ categories. A second notable feature of this distribution is that the probability of conducting R&D varies between sectors amongst innovating firms in the same ‘standardisation–particularisation’ categories. For example, whilst 10% and 9% of the innovating Wholly Standardised trade and transport and communications firms, respectively, conducted R&D, 20% of the innovating Wholly Standardised banking and insurance firms did the same. Amongst the Bespoke service providers, the proportion of innovating trade firms conducting R&D was 30%, but 58% amongst the technical service firms. In general, and not surprisingly, innovating firms in the sectors with higher levels of technological intensity appear to be more

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likely to conduct R&D than innovating firms in the less technologically orientated sectors. A third point is that, within each of the sub-sectors, there was considerable diversity in behaviour. For example, innovating bespoke technical service providers were the most likely group of firms to conduct R&D, yet a large proportion (42%) of these firms did not undertake R&D. This points to the heterogeneity that exists within all of the classifications. In summary, the analysis of the proportion of innovating firms undertaking R&D supports our initial hypothesis that the probability that a firm will undertake R&D increases with the extent to which its services are particularised to different users’ requirements. Again, it validates the usefulness of the classification and the indicators on which it is based. Beyond this, however, it has also underlined both differences between sectors, and variations within the individual ‘standardisation–particularisation’ classifications of each sector. Thus, considerable variation exists that remains beyond the scope of the present analysis.

6. Conclusions This paper has analysed the pattern of service activities using German evidence on the structure of their income from ‘standardised’, ‘partially customised’ and ‘bespoke’ services. We have also examined the patterns of ‘standardisation–particularisation’ with respect to the size of the firms, their broad sector of activity, their employment structures by educational attainment, propensities to innovate and (amongst innovators) to conduct R&D. Our analysis lends support to those, such as Pavitt, Soete–Miozzo, Silvestrou et al., de Jong and Gallouj and Sundbo who have sought to provide ‘combined’ taxonomies of service activities, based partially on the nature of their technological underpinnings, and partially on the nature of the markets they serve. For example, we found the generally ‘scale-intensive’ sectors of trade, transport and communications and banking and insurance to be largely oriented towards the provision of standardised services. These sectors also tend to have relatively low proportions of highly qualified employees. By contrast, in the ‘specialist supplier’ sectors of technical services and other financial services, university graduates constitute a much

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larger proportion of total employment, and firms in these sectors tend to earn a larger than average proportion of their income from bespoke and partially customised services. Table 6 provides a summary of the results for each of the broad sectors concerning: the distribution of firms by size; the structure of income by ‘standardisation–particularisation’; the structure of employment by qualifications; the propensity to innovate; and — amongst innovators — the propensity to conduct R&D. There is tremendous variation amongst service firms, and if the product/industry life cycle approach

portrays the life cycle as a generic force which largely determines the structure of industries and the pattern of firms’ activities, then its scope is too restrictive. However, another interpretation of the life cycle approach has more value. Recall that Barras (1986) identified three stages in his model of service innovation: first, firms concentrate on process innovation and the efficient provision of standardised services; second, largely through the introduction of ICTs, firms become more flexible and focus more on quality; and third, new entrepreneurial firms enter the market and there is a shift to ‘product’ innovation. Whilst

Table 6 Summary of findings with respect to firm size, sector and standardisation–particularisation Sector

Comment

Trade

Firms are more likely to be Wholly Standardised and less likely to be Customised or Bespoke service providers. As firms become larger they become more likely to be Largely Standardised and less likely to be Customised. The sector employs a relatively small proportion of highly educated people, and firms are slightly less likely than average to innovate. Relatively few innovating firms conduct R&D, although this increases with particularisation Includes a few very large firms, but also many small and medium sized enterprises. There are very few Bespoke service providers, whilst firms are more likely to be Largely Standardised (and less likely to be Wholly Standardised) with increasing size. The sector employs a relatively small proportion of highly educated people, and firms are average in their propensity to innovate. Relatively few innovating firms conduct R&D. This sector is probably particularly diverse, including a few high-tech telecommunications businesses and many low tech transport firms Firms are much more likely to be large, and much less likely to be micro or small. Half these firms are classified as Largely Standardised, and only 4% are Bespoke service providers. The sector employs a medium level of highly educated people, but these firms are amongst the most likely to innovate. Around 25% of innovators conduct R&D Much more likely to be micro firms, and much less likely to be medium sized or large, these firms are also significantly less likely to be Wholly or Largely Standardised service providers, and are much more likely to be Bespoke or Customised service providers. The level of employment of highly educated people is perhaps surprisingly low given the dominance of micro and small firms. These firms are around average in their propensity to innovate, but few of the innovating firms conduct R&D Firms are more likely to be small, and less likely to be large, the sector has the smallest proportion of Wholly Standardised service providers. Software firms are much more likely than other service firms to be Bespoke or Customised service providers, although the proportion of Customised firms declined with size, giving way to more Largely Standardised service providers. The sector has a high proportion of highly educated people and, unsurprisingly, a high proportion of innovators. Perhaps surprisingly, only around 40% of the innovators have R&D activities Firms are more likely to be micro enterprises and are less likely to be large than other services. These firms are also significantly less likely to be Wholly Standardised service providers. The sector has the largest proportion of Bespoke service providers, and employs a large proportion of highly educated people, especially amongst the Bespoke and Customised service providers. The propensity to innovate is higher than average, as is the propensity, amongst innovators, to conduct R&D These firms are less likely to be Wholly Standardised service providers than other services and are mainly Largely Standardised and Customised service providers. The highly educated form a large proportion of total employment amongst Bespoke and Customised service providers, but not amongst Wholly Standardised firms. The propensity to innovate is below average amongst the Wholly Standardised firms, but above average for the other firms. About 25% of the innovating firms conduct R&D, this increases with particularisation

Transport and communications

Banking and insurance

Other financial services

Software

Technical services

Other business services

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we do not believe the reverse product cycle model should be assumed to apply as a generic temporal sequence, it does usefully highlight the strategic choices which firms confront in relation to their innovation and standardisation–particularisation strategies. For example, we suggest that some firms — particularly but not exclusively in scale-intensive price sensitive sectors such as mass-retailing — continue to focus on the provision of low cost standardised services, whilst others do not, choosing instead to focus on flexibility and compete on quality rather than price. Thus, while some firms may use technologies (especially but not only ICTs) to maximise order and control over production and to minimise costs, others (notably but not exclusively in scale-oriented sectors such as banking and telecommunications) are able to use similar technologies to provide more flexible and partially customised services (whilst still maintaining a high degree of order or control over production). Still other firms, in a wide variety of sectors, will concentrate on specialised markets which are less concerned with price, and in which customised or bespoke services are largely created and delivered on the basis of the skills and knowledge of employees rather than via elaborate technological systems. Amongst these, customer satisfaction takes precedence over maintaining a high degree of order or control over the system of production. From this perspective, firms are able to make strategic choices about their markets, and how they serve them. They can focus on process innovation and standardisation, or on ‘product’ innovation and customisation; and they develop their employment and technology bases accordingly. This helps account for the heterogeneity displayed among firms of the same size and in the same broad sector: strategy combined with labour, human capital and technology provides considerable scope for choice. Of course, there are ‘selection processes’: such strategic choices will relate to commercial and economic success or failure in the longer term. The workings of these processes in different sectors and at different times remain to be explored, as does the matter of the opportunities and difficulties firms face if they seek to change their strategies in the context of unfavourable market conditions. Overall, the most striking finding from our analysis is the tremendous diversity that is repeatedly found within the population of service firms. There are broad

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trends, which reflect the sectoral categorisations discussed earlier, but there is also immense variation in behaviour within each broad sector. Whilst useful as starting points, simple taxonomies may mislead us into expecting much more homogeneity within classes or sectors than is actually the case. The diversity amongst service firms needs to be more fully understood. Most probably there is a need for detailed service industry case studies, and detailed analyses of data-sets, such as that undertaken by Evangelista and Savona (1998). It certainly makes no sense to analyse services as a homogeneous whole.

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