Modelling advertising decisions by accountants: A path analysis

British Arcow@q

Review (1990) 22, 3-26

MODELLING ADVERTISING DECISIONS ACCOUNTANTS: A PATH ANALYSIS

BY

A. DIAMANTOPOULOS* University

of Edinburgh

S. O’DONOHOE University

of Edinburgh

J. LANE Ernst & Whinney

Based on a national survey of chartered accountancy practices, this paper develops and tests a path model of the advertising management process in the profession. Specifically, it examines the relationship between resources devoted to advertising, key decision areas and the success of advertising campaigns. The findings are discussed in light of previous empirical work and their managerial implications are highlighted.

1. INTRODUCTION The economic importance of the service sector has increased dramatically in recent decades. Bradlow (1986) for example, notes that the service sector in the United States increased its share of GNP from 54% to 66% between 1948 and 1978. The trend towards a service-oriented economy is also evident in the United Kingdom. In 1966, services contributed 42% to GDP, rising to 48% by 1986 [Central Statistics Ofice (CSO), 1976a; 1988a]. A more striking indicator of the growth of services is the major change in employment patterns over the same period. Less than half of UK employees worked in the services sector in 1966; by 1986 this sector accounted for just over two-thirds of the total number of employees (CSO, 19766; 19886). Corresponding to the growing importance of the services sector is the growing literature on services marketing. An interesting indicator of this is provided by Gummesson (1978), who laments the fact that Kotler’s (1972) classic text devoted less than two of its 885 pages to the marketing of services. In recent years, however, Kotler has not only included in revised editions of his basic text entire chapters on nonbusiness marketing (Kotler, 1980) and service marketing (Kotler, 1988), but he is also one of many authors writing whole textbooks on the marketing of specific *Address for correspondence: Mr. A. Diamantopoulos, Department of Business Studies, University of Edinburgh, William Robertson Building, 50 George Square, Edinburgh EH8 9JY. 0890-8939/9O/Ol(N)O3+24 $03.00/O

(Q 1990 Academic Press Limited

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services, such as non-profit organisations (Kotler & Andreason, 1987), educational institutions (Kotler 81 Fox, 1985), health-care organisations (Kotler & Clarke, 1987) and professional services (Kotler & Bloom, 1984). The marketing of professional services in particular has been increasingly addressed in the literature, with emphasis on its distinctive characteristics and the implications for strategy development (Kotler & Connor, 1977; Gummesson, 1978; 1979; Hill & Fannin, 1986). The scope of much of this work is similar to that noted by Zeithaml et al. (1985) in their review of the services marketing literature. This review identified three areas of common concern: notably (a) the unique characteristics of services marketing; (b) the problems which these characteristics pose for services marketers, and (c) the marketing strategy solutions for those problems. Within the field of professional services, financial and related services have been experiencing explosive growth. Between 1966 and 1986, the contribution of insurance, banking, financial and business services to the UK GDP virtually trebled, rising from 3.8% to 10.7% (CSO, 1976~; 1988~). Against this background, it is not surprising that the marketing of accounting services has emerged as a major area of interest to both marketing and accounting professionals. The application of marketing theory to the provision of accounting services has been the subject of several books (e.g., Congram & Dumesic, 1986; Listman, 1988), and advice on marketing principles and procedures abounds in accounting journals (e.g., Scholten, 1984; Davies, 1985; Williams, 1985; Booth, 1986; Isaacson, 1987). A considerable proportion of these books and articles has been devoted to the development of effective promotion strategies. Accountants’ ‘marketing mix’ (i.e., factors under their control which influence demand for their services) also includes the services offered, their price and how they are made available. However, promotion is a crucial element of the marketing mix, as it is concerned with communicating what is being offered to actual and potential clients. The ‘promotional mix’ consists of four main communication methods, namely advertising, publicity, sales promotion and personal selling. Of these, advertising is generally the most highly visible and, in the case of accountants, it has been the most emotive and controversial aspect of promotion. Indeed, according to the ‘ethical prohibitions’ on advertising in the UK accounting profession (removed quite recently), only recruitment advertisements and ‘tombstone’ professional announcements were accepted as good practice. Then, in October 1984, in response to increasing competition from management consultants, banks and other institutions, as well as pressure from the Office of Fair Trading and The Monopolies and Mergers Commission, the restrictions were removed; this was in line with changes

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taking place in the profession internationally. Accountants could advertise their services, subject to the requirements of good taste and responsibility to the profession. Initially, advertisements placed in newspapers could not exceed a quarter page, and unsolicited material could not be sent to nonclients. However, the quarter-page restriction was relaxed in October 1986, and direct mailing has been allowed since February 1987. The attitudes of accountants and their clients towards advertising leading up to the removal of restrictions on promotion have been the subject of considerable empirical research in several countries (Darling, 1977; Carver et al., 1979; Dixon & Taylor, 1979; Teoh & Gull, 1985). However, relatively little research has been conducted subsequently to investigate what accountants have actually done with their newly-found freedom to advertise (King & Carver, 1984; Driscoll, 1985; Morgan, 1988). A study addressing this issue in the UK was recently reported by Diamantopoulos et al. (19896) in which the extent and practice of advertising in the accounting profession were examined. The findings supported the contention of Watkins & Wright (1985) that a practice’s size would influence the communication strategy it employed. Larger firms (in terms of employee numbers and annual fee income) were more likely to advertise in the first place and, among advertisers, it was the larger firms which tended to use advertising agencies and to devote greater financial resources to advertising. Further analysis (Diamantopoulos et al., 1989b) examined differences in advertising practices between accountancy firms and investigated the extent to which these could be attributed to differences in resources. While financial resources (as measured by size of the advertising budget) were found to have a considerable influence on advertising activities, the mere availability of finance was no substitute for the expertise gained from the use of advertising agencies. Firms which employed advertising agencies were found to have a more systematic approach to promotion; they were more likely to undertake pre-advertising research, market segmentation and advertising evaluation, and their use of media was more varied and intensive. The present paper seeks to provide further insights into the advertising practices of accountancy firms by investigating the interaction between different advertising decision areas and relating them to the resources at the firms’ disposal and to the perceived success of advertising campaigns. To this end, a model of accountants’ advertising practice based on theoretical expectations is formulated and tested, using the technique of path analysis as an expository device. Briefly, path analysis involves the construction of a model specifying the expected relationships between the independent variables and the ultimate variable of interest, as well as the relationships between the prior (i.e., independent) variables. This is usually shown by means of an arrow

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diagram whereby the linkages among variables are represented by arrows, the direction of an arrow signifying the postulated order of causality. Thus, each included linkage represents a hypothesis which can subsequently be tested by estimating the magnitude of the relationship. Variables may be connected directly as well as indirectly to one another; the latter situation arises where there are intervening variables. As a result, the total effect (i.e. impact) that one causally prior variable can have on another may consist of both a direct and an indirect component. Having specified all relevant linkages (i.e. hypotheses) in one’s model, the next step involves the estimation of what are known as ‘path coefficients’, which describe the magnitude of the relationship among the variables concerned. This is usually done by regression analysis, with the relevant causal prior variables serving as predictors for each dependent variable involved. If the estimation procedure confirms the model, then the initial specification can be taken as supported by the empirical data. If certain parts of the model (i.e. individual linkages) are not confirmed, then appropriate revisions may be undertaken and the estimation process repeated for the modified version. It is important to stress that an essential prerequisite for the successful application of path analysis is the formulation of sound theoretical expectations regarding the nature of the relationships of interest so that a conceptually meaningful model is constructed for subsequent testing. As Asher (1976, p. 10) points out, ‘. . . if one has little confidence in few, if any, of the posited linkages, the application of causal modeling techniques may become a mindless attempt to find the best fit to the data, regardless whether the final result is substantively and theoretically plausible’. 2. METHODOLOGY 2.1. Data The data from the present study were drawn from a questionnaire mailed at the end of November 1985 to the senior partner in 200 large chartered accountancy practices throughout the UK. As no definitive list of accountancy practices by size exists, the sample was constructed from a combination of sources. A questionnaire was sent to each firm in the UK Accounting Bulletin’s May 1985 list of the top 52 practices according to fee income. The balance of the questionnaires was mailed to firms which, according to the directories of the various Chartered Accountancy Institutes, employed the greatest number of Chartered Accountants. The use of different size criteria (fee income and employment) is not ideal, but this sampling method was adopted in the absence of any other readily available method of targeting the largest firms. Sixty-three usable replies were obtained (an effective response rate of 31.5%), nineteen of which were from firms which did not advertise. The present analysis is concerned

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Variables and their measures (a) Resources 1. Advertising Budget: Annual expenditure on advertising (in pounds) 2. Agency Use: Dichotomous variable (0 = do not use an agency; 1 = agency is used) (b) Product Mix Diversity Number of different products/services offered, as ticked from the following checklist: audits; accounts; tax consultancy; estate planning; computer services; management consultancy; investment advice; mortgage and loan advice; employment regulations; pension planning; wages services; VAT services; other (c) Advertising Management Decisions 1. Pre-advertising Research: Dichotomous variable (0 = no research done; 1 = research undertaken) 2. Market Segmentation: Dichotomous variable (0 = no segmentation; 1 = segmentation practiced) 3. Media Variety: As press advertising was by far the dominant approach (Diamantopoulos et al. 1989a), this variable was measured by the number of different press media used (min = 1; max = 5) 4. Media Intensity: Summated scale (alpha = 0.75) indicating usage of five press media (notably national newspapers, regional newspapers, business periodicals, financial press, and other periodicals). Use of each of the media was registered on a Cpoint scale (4 = used widely; 1 = not used at all) (d) Advertising Success Sum of perceived success ratings (1 = very successful; 4 = totally unsuccessful) each press medium used, divided by the number of press media employed.

for

solely with those firms which did engage in advertising, hence a data set of forty-four advertisers was used as the empirical base; further data collection details, as well as a comparison of advertisers and non-advertisers, can be found in Diamantopoulos et al. (19896). 2.2. Vuriables Only variables for which directional hypotheses could be developed and translated into causal links were included in the path analysis. In this context, the questionnaire requested, among others, information on the execution of accountants’ advertising messages (humour, visual impact, etc.), and it would have been interesting to examine the relationship between, say, humour and media usage. However, as the expected direction of such a relationship could not be reasonably specified a priori (i.e. a humorous execution could not be hypothesized to lead to more/less intensive media usage), this variable was excluded from the analysis; a similar rationale applies to other questionnaire variables which were not incorporated in the proposed model. Table 1 describes the variables utilised to build the model of the advertising process.

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3. MODEL

ET AL.

DESCRIPTION

Figure 1 overleaf shows the proposed model of the advertising process within the accounting profession, utilising the eight variables described in Table 1. Each link represents a theoretically founded hypothesis, the nature of the expected relationship between the variables concerned being represented by the sign of the arrow. Thus, the model is based on a total of fifteen hypotheses (equal to the number of postulated linkages), which are summarised in Table 2 and further elaborated below. 3.1. Financial resources (Hl. 1-Hl.4) The size of a firm’s advertising appropriation could be expected to exert considerable influence on many advertising management decisions, since advertising is a cost-incurring activity; thus, availability of funds would facilitate the employment of advertising agencies, the conduct of pre-advertising research and the frequency/intensity of media usage. Furthermore, in view of set-up costs frequently associated with advertising in each new medium (Broadbent &Jacobs, 1984), one would expect larger advertising budgets to lead to greater media variety. However, affordability is only one facet of the role of resources in advertising decisions. For example, in the case of the agency-use decision, it could be argued that as the financial resources devoted to advertising increase, their effective deployment could become a more demanding and timeconsuming managerial task; if neither the time nor the expertise required is available in-house, an advertising agency may be employed. Similarly, as the financial resources devoted to advertising increase, pre-advertising research may be considered a necessary control mechanism to ensure their effective deployment. 3.2. Use of advertising agencies (H2. I-H2.4) Firms employing advertising agencies presumably do so in the expectation of benefiting from their expertise and achieving more favourable results from their advertising campaigns than if they had ‘gone it alone’; it should be noted, in this context, that accountants have had little time to develop advertising expertise themselves, since it is only since October 1984 that they have been allowed to advertise. Thus, one would expect a positive relationship between agency use and advertising success. Bearing in mind that agency expertise extends beyond the creative dimension to cover areas of advertising management, accountants using advertising are likely to be advised of the benefits of research, market segmentation and advertising repetition and thus more likely to undertake such activities than non-users. 3.3. Pre-advertising research (H3. I-H3.3) As a result of pre-advertising research, firms should gain a greater understanding of their markets and, thus, are more likely to recognize the

I

1 Advertising agency use

Advertising budget +

+

+ 1

I

I I-

1

Figure 1. Path model of advertising behaviour in the accounting profession: expected signs of path coefkients. (The negative signs to ‘Advertising Success’ are due to the measurement scheme of the latter; i.e., low values = high success, and high values = low success).

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Study hypotheses Hl:

Financial Resources : The greater the financial resources devoted to advertising 1 .l the greater the likelihood of using an advertising agency 1.2 the greater the likelihood of conducting pre-advertising research 1.3 the greater the number of advertising media used 1.4 the more frequent/intense use of media

H2: Use of Advertising Agencies : Firms using an advertising 2.1 conduct pre-advertising research 2.2 undertake market segmentation 2.3 make more intensive use of advertising media 2.4 develop successful advertising campaigns

agency are more likely

H3: Be-advertising Research : Firms conducting pre-advertising 3.1 practice market segmentation 3.2 use a greater number of advertising media 3.3 make more intensive use of advertising media H4: Product Mix Diversity: market segmentation

Firms with

a wide product

H5: Market Segmentation : Firms practising greater number of advertising media

research are more likely

mix are more likely

market segmentation

H6: Media Variety: Firms using a greater number more successful in their advertising

to

to practice

are more likely

of advertising

media are likely

H7: Media Usage lrztensity : Firms making more intense use of advertising to be more successful in their advertising.

to

to use a to be

media are likely

potential utility of market segmentation in facilitating the targeting of appeals. Firms conducting pre-advertising research are also more likely to observe differences in service requirements among current/potential customers and media usage habits in different market segments. This knowledge could be expected to be used in the determination of appropriate repetition levels of advertising messages, suggesting a positive relationship between the undertaking of pre-advertising research and media intensity; one could also expect a positive relationship between preadvertising research and media variety since a firm conducting research would be in a better position to match particular forms of media with specific types of audience. 3.4. Product mix diversity

and market segmentation

(H4-H5)

Introducing the concept of market segmentation to accountants, Listman (1988) advises that resource allocation cannot be maximised if an organisation tries to be all things to all clients. By dividing the total market into segments, each with distinct needs and levels of receptiveness to various

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services, a firm can develop a unique mix designed to fit the service, fee, promotion and distribution requirements of specific market segments. Given that different kinds of accounting services may appeal to different market sectors, a ‘blanket’ approach to advertising is likely to be inappropriate for firms with a wide range of services; hence, firms with a wide product mix are more likely to practice market segmentation than firms with a narrow mix. In turn, since different market segments may require different channels to be reached effectively (Aaker & Myers, 1987), it can be expected that firms which segment their market will use more advertising media. 3.5. Media variety and intensity (H&H7) More diverse use of advertising media could be expected to contribute to advertising success, as it would tend to increase the reach of a campaign (i.e. the total au d’ience exposed to it). As reach is especially important for creating awareness of new products (Aaker & Myers, 1987), it should also be important for accountants presenting their services to the public through advertising for the first time. In addition, more frequent use of media would be expected to produce the benefits of repetition (such as greater awareness, learning, comprehension and reinforcement of the message) with a corresponding effect on the success of advertising campaigns. 4. ANALYSIS Bearing in mind the overidentified nature of the postulated model, the path coefficients were estimated following Goldberger’s (1970) method; that is, through a series of regression equations whereby only those variables assumed to have direct causal effects on a given dependent variable were included as predictors (i.e. the path coefficients are represented by the standardised regression weights). As Figure 2 indicates, all but four coefficients were significant at the 5% level or better. Subsequently, the non-significant paths were removed, and the model re-estimated in its reduced form; the removal of the four non-significant paths made very little difference for the remaining linkages, as indicated by the rather negligible changes in the magnitudes of the path coefficients in the final model (Figure 3). Before discussing the nature of the linkages in the final model, attention is drawn to the hypothesised relationships which were not supported. 4.1. Non-signi_Fcant paths 4.1.1. Financial resources,agency use and pre-advertising research. Surprisingly, the undertaking of pre-advertising research was not substantially affected

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by either financial resources (H1.2) or advertising agency use (H2.1); although the relationships were found to be in the expected direction, they were not significant. This may be interpreted in several ways. Given the logical attraction of the hypotheses, one could perhaps take the limitations of sample size into account and argue that the results should be treated as inconclusive, in that significance could have been achieved with a larger sample. However, the validity of this explanation in this context is questionable since there is only a limited number of large firms and a limited number of firms which advertise. Previous analysis conducted by the authors (Diamantopoulos et al., 1989b) may be useful in clarifying the issues involved. In that analysis, a typology of accounting firms was developed, based on the size of advertising expenditures and use of an advertising agency, which resulted in the identification of three distinct groups of firms: Agency Users, Agency Decliners and Agency Denieds. Decliners were so labelled because they did not use an advertising agency despite having advertising budgets at least equal to the minimum level of Agency Users, while the financial resources devoted to advertising by the third group were so limited that using an agency was clearly beyond their means. Within this typology, Agency Users were found to be the group most likely to conduct pre-advertising research. This is hardly surprising. Not only did firms in this group possess the required financial resources, but they presumably had the encouragement of their advertising agencies as well (especially since the advertising of accounting services was a new activity for both parties). One would also expect the incidence of preadvertising research to be considerably lower among Agency Denieds (given their limited funds), and this indeed proved to be the case. Surprisingly, however, it was the Agency Decliners (who did not suffer the budget restrictions of the Denieds) who were leust likely to conduct research prior to advertising. On further inspection of the data, a positive relationship appeared to exist between a high budget and the conduct of pre-advertising research ifthe firm also used an agency. However, if the firm did not use an agency, a negative relationship was observed. Therefore, the non-significant linkages identified suggest that the relationships between agency use and research, and between advertising budget and research are not perhaps as straightforward as might be expected; research appears to be affected by the interplay between agency use and advertising budget rather than by either of these factors in isolation. 4.1.2. Advertising agency use and advertising success.While the direct effect on advertising success observed for agency use was in the expected direction, it was not significant; thus, there is insufficient evidence to support hypothesis

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H2.3. However, this is not as disturbing as may be initially thought, in the light of the indirect effects observed (see Section 4.2.2). It appears that the use of an advertising agency per se is not directly reflected on advertising success, but rather its impact is achieved by a more circuitous route; specifically, agency expertise seems to be channelled through specific decision areas, such as selection of target markets and media planning. 4.1.3. Be-advertising research and market segmentation. In this case, the relationship between the two variables was both non-significant and in the opposite direction to that hypothesised (H3.1); however, the magnitude of the relevant path coefficient was practically zero. An examination of the kind of research conducted and the segmentation bases preferred may be helpful in throwing some light on this finding. As observed in Diamantopoulos et al. (1989b), the most common area of pre-advertising research related to the suitability of alternative advertising media, followed by clients’ knowledge of the range of services offered, public awareness of the firm’s name, and the public image of accountants. The preferred bases for segmentation, on the other hand, were concerned with the type of service, type of client, industry sector, and geographical location (in that order). While there appears to be some overlap between research and segmentation in terms of service type, on the whole the segmentation bases relate to client characteristics which did not constitute the main focus of pre-advertising research. Further, it is possible that segmentation efforts, at least initially, were based on information concerning current customers (which would have been relatively easy to obtain from the firm’s internal records). While this would certainly indicate that firms conducted desk research with a view to segmenting their markets, the questionnaire used in the present study did not explicitly distinguish between different types of research activity (e.g. primary vs. secondary, continuous vs. ad-hoc, etc.); this may well have clouded the research-segmentation relationship. 4.2. Significant paths 4.2.1. Financial resources.Financial resources (as measured by the size of the advertising budget) were found to have the expected relationships with advertising agency use, media variety and media intensity; thus supporting hypothesis Hl .l, H1.3 and H1.4, respectively. Table 3 shows the decomposition of the relevant total effects into direct and indirect components. The indirect effect is calculated by multiplying the coefficients for each distinct indirect path and subsequently adding the products together. To illustrate the approach, consider the indirect effect of the advertising budget on advertising success in Figure 3. There are four ways of getting from the

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TABLE Impact ojjinancial

ET

AL.

3 resources Effect decomposition

Dependent

variable

Advertising agency use Media variety Media intensity Advertising success

Direct

Indirect

Total

0.53 0.36 0.44 -

0.07 0.19 - 0.20

0.53 0.42 0.63 -0.20

former to the latter variable, notably: (a) through media variety; (b) through media usage intensity; (c) through advertising agency use and media usage intensity, and (d) through advertising agency use, market segmentation, and media variety. Thus, the total indirect effect comes to (0.36 x 0.54) + [0*44 x (-0.68)] + [0.53 x 0.36 x (-0.68)) + (0.53 x 0.45 x 0.28 x 0.54) - 0.20. The strongest direct effect was found with respect to use of advertising agencies. This is consistent with previous evidence (Diamantopoulos et al., 1989~) indicating that agency users were significantly larger companies than non-users (both in terms of fee income and number of employees) and spent, on average, seven times more on advertising. Financial resources were also found to have a positive impact on media variety, revealing both a direct and an indirect effect (the latter being channelled through agency use and market segmentation). Bearing in mind the set-up costs generally associated with each new medium employed (Broadbent & Jacobs, 1984), it is not surprising that it is the firms with the larger advertising budgets which can best bear this expense. Both direct and indirect effects were also observed with respect to media intensity; indeed, it is with respect to this that financial resources have the largest overall effect. The direct effect reflects the rather obvious fact that as the number of exposures increases, so does the cost of a campaign. The indirect effect, on the other hand, is channelled through advertising agency use and reflects the latter’s expertise in ensuring adequate exposure of advertising messages in the relevant media. Finally, financial resources appeared to have a positive but indirect effect on advertising success; the negative sign in Table 3 reflects the measurement scheme of the success variable (see Table 1 in Section 2.2) and is consistent with expectations. It is interesting to note that the impact of financial resources is mediated through cost-incurring activities, such as agency usage and media employment.

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4

Impart of advertising agency me Effect decomposition Dependent

variable

Market segmentation Media variety Media intensity Advertising success

Direct

Indirect

0.45 0.13 0.36 -0.18

Total 0.45 0.13 0.36 -0.18

4.2.2. Advertising agency use. As Table 4 indicates, there is a positive direct effect of agency use on market segmentation, lending support to hypothesis H2.2. It seems, therefore, that firms employing the services of advertising agencies are encouraged to treat the market for their services in terms of identifiable groupings with distinct characteristics, rather than as a single homogeneous entity. This implies that, in addition to the creative function which agencies are expected to fulfll as a matter of course, their expertise may be useful in leading accountants to a deeper understanding of their markets, thus facilitating the development of advertising campaigns with a better targeting potential. Advertising agency use also impinged indirectly on the number of media used, its effect being mediated through market segmentation. With regard to agencies’ influence on the extent to which media are used, the use of advertising agencies is positively and significantly related to media intensity; this is in accordance with hypothesis H2.3. From a professional standpoint, this reflects the fact that advertising agencies would be aware of the need for repetition to ensure that an advertising message/campaign makes a significant impression on the target audience. While cynics might add that it is in the agencies’ own financial interest to encourage greater use of media, agencies are generally less open to such accusations with the advent of commission rebates and the relative decline of straight commission as a form of remuneration. As mentioned briefly in Section 4.1.2, the influence of advertising agency expertise on advertising success is channelled through intermediate variables. These are media intensity on the one hand and market segmentation/media variety on the other; the overall effect is in the expected direction, signifying that agency use makes a positive contribution to advertising success. 4.2.3. Pre-advertising research. The effect decomposition relating to the impact of pre-advertising research is displayed in Table 5. The direct effects

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5

Impact of pre-advertising

research

Effect decomposition Dependent

variable

Media variety Media intensity Advertising success

Direct

Indirect

0.29 0.34 -0.07

Total 0.29 0.34 -0.07

obtained, with regard to the two media-usage indicators, confirm that conducting pre-advertising research leads to a greater variety of media being used (hypothesis H3.1) and also to more intensive media usage (hypothesis H3.3). As the suitability of alternative media was the most popular area of research among the accountants surveyed (see Section 4.1.3), one would expect firms undertaking such research to be more aware of media opportunities and to capitalise on this knowledge by using a wider range of available options. Similarly, one may also expect such research to sensitise advertisers to the need for repetition in order to ensure sufficient impact of the advertising message. Only a weak, indirect relationship could be established between preadvertising research and advertising success, which was mediated through the two media indicators; nevertheless, the nature of the relationship indicates that research has a positive impact on advertising success. 4.2.4. Product mix diversity. The width of the product mix was expected to influence whether or not accountants segmented their markets (hypothesis H4), as different and specialised services are likely to appeal to different market segments. This indeed proved to be the case as Table 6 illustrates. The observed relationship between product-mix diversity and market TABLE

6

Impact ofproduct mix diversity Effect decomposition Dependent

variable

Market segmentation Media variety Advertising success

Direct

Indirect

Total

0.08 0.04

0.28 0.08 0,04

0.28

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7

Impact of market segmentation Effect decomposition Dependent

variable

Media variety Advertising success

Direct

Indirect

Total

0.28 -

0.15

0.28 0.15

segmentation is consistent with previous findings (briefly mentioned in Section 4.1.3) which highlight the popularity of type of service as a basis for segmentation. However, a word of warning may be appropriate on using the type of service as a segmentation basis. Specifically, one would hope that in using this method, accountants are focusing their efforts on the needs and characteristics of identifiably distinct customer groups rather than simply assuming that different types of customers would automatically be attracted simply as a result of the variety of services on offer. Accountancy firms, however, being relative newcomers to the world of marketing and advertising, may not be very clear about the difference between product differentiation and market segmentation. Indeed, Carter & Lindgren (1981) report that large professional accounting firms in the USA have traditionally ‘segmented’ practices into separate areas such as taxation, consulting and auditing, with little regard for their potential different marketing-strategy requirements. In this respect, guidance from advertising agencies would appear to be desirable and, in the light of the strong link observed between advertising agency usage and the use of market segmentation (see Section 4.2.2), one has reason to believe that this is indeed the case. The width of the product mix also has an indirect effect on media variety (through market segmentation), indicating that firms offering a greater number of different services are more likely to utilise a broader variety of advertising media to reach their audiences, a finding that makes intuitive sense. On the other hand, the indirect effect between product mix diversity and advertising success, albeit small in magnitude, suggests that firms with a wider product mix are, overall, somewhat less satisfied with the success of their advertising efforts than firms offering a narrower range of services. 4.2.5. Market segmentation. Consistent with expectations, market segmentation has a positive impact on the variety of media used in advertising programmes (Table 7). This supports hypothesis H5 and suggests that

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8

impact of media variety Effect decomposition Dependent Advertising

variable success

Direct

Indirect

0.54

Total 0.54

market segmentation, in addition to enabling the identification of distinct customer requirements, may reveal that different market segments have different media consumption patterns; this, in turn, may lead to the adoption of a separate media mix for each segment and, thus, to a greater number of media altogether. It is also interesting to note that market segmentation is also indirectly related to advertising success (media variety being the mediating variable); the positive sign of the effect suggests that firms undertaking segmentation perceive their campaigns as being less successful than firms treating their market as a homogeneous entity. This is a somewhat surprising finding but should become clearer after an examination of the direct link between media variety and advertising success, which is undertaken in the next section. 4.2.6. Media variety/intensity and advertising success.Both media variety and media intensity were found to have strong direct effects on advertising success, as indicated in Tables 8 and 9. However, while the relationship between media intensity and success is in the direction postulated by hypothesis H7 (i.e. the more intensive the media usage, the greater the success), the same cannot be said with respect to the impact of the media variety variable. According to the results, using a large number of media appears to detract from the success of advertising campaigns. This finding contradicts hypothesis H6 and is quite surprising, since greater media variety should enhance the reach of a given campaign, thereby conTABLE

9

Impact ofmedia intensity Effect decomposition Dependent Advertising

variable success

Direct -0.68

Indirect -

Total -0.68

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tributing to its effectiveness. However, the results indicate that it is media intensity (i.e. frequency of usage) rather than media variety (i.e. breadth of coverage) which has a positive effect on the perceived success of accountants’ advertising campaigns. The negative relationship between media variety and advertising success could be interpreted as highlighting a trade-off between intensity and diversity in media usage; that is, variety may have been pursued at the expense of intensity, thereby diluting the total advertising effort. While this explanation is intuitively appealing, it should also be remembered that both variety and intensity are largely dependent upon the availability of advertising funds and, thus, it is likely that firms employing a greater number of advertising media would also be in a position to use them more frequently. In this context, Diamantopoulos et al. (1989h) found that Agency Users (the group with the greatest fee income and largest advertising budgets) used a greater number of media than the other two groups, and also made more intensive use of the media which they employed. An alternative interpretation that can be offered is based on the specific clzoiceof media made. In this context, the results can be viewed as implying that, on the whole, firms using a smaller number of media do so because they have selected the ‘best’ among the available alternatives. In contrast, firms using a larger number of different media, may be doing so (at least initially) in an experimental fashion, i.e. in order to identify precisely which types of media should be used in the long-run; in this case, the effectiveness of some of the media tried may be low, a fact which would adversely affect the overall success rating. The extent to which this line of argument provides a satisfactory explanation for the results obtained can only be determined by reference to the specific media used by the firms concerned (i.e. the particular publications in which advertisements are placed); unfortunately, the data on media usage obtained through the questionnaire do not possess the degree of detail required to throw light on this issue. A third possible explanation is that there may be a degree of overlap in readership among the various media, so that as the number of media used increases, diminishing returns may set in. Again, detailed information on the specific media employed would be necessary in order to determine whether this is actually the case. Finally, it is important to bear in mind the meastlre of advertising success utilised in this study. As was stated in the methodology section, the operationalisation of success was in terms of the firm’s own perception of the effectiveness of their advertising effort rather than in terms of an ‘objective’ success measure. While it is readily conceded that this is a rather crude measure, from a practical point of view, it is very difficult to use an objective indicator of overall advertising success. The reasons for this are

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two-fold. First, a substantial proportion of the firms in the sample (some 40%) did not make any systematic/formal effort to evaluate advertising effectiveness (Diamantopoulos et al. 1989a), a number of them commenting that it was ‘too early to assesstheir advertising’. Second, even if all firms actually did so, one would somehow have to incorporate differences in advertising objectives within a success measure; how this could be done effectively is far from obvious. Thus, while certainly admitting that the measure of success employed leaves a lot to be desired, it was nevertheless considered preferable, from a theoretical point of view, to incorporate advertising success in the model, rather than exclude it purely because a better measure was not readily available. 4.3. Overall model assessment Having examined in detail the individual components/linkages comprising the model of the advertising management process within the accounting profession, attention is now drawn to an overall assessment of the model. Given that the proposed model is a restricted model (since some parameters are assumed to be zero, as illustrated, for example, by the absence of a direct link between advertising budget and market segmentation), it is helpful to evaluate its adequacy vis-a-vis the relevant general model (i.e. that which woul’d result if each endogeneous variable was related to 612 variables of a higher causal order); this provides an indication of the extent to which the model, as currently specified, fits the data. A test appropriate for this purpose has been proposed by Land (1973) and involves the calculation of a quantity which is distributed as a chi-square statistic with degrees of freedom equal to the number of overidentifying restrictions; if this chi-square test is not significant, then the model performs adequately. In the present case, the chi-square value was very low, indicating that the model as specified is not statistically inferior to the general model (x’ = 2.39, df = 7, not significant). Further insight into the overall performance of the model can be gained by looking at the coefficients of determination (R2) of the dependent variables. It should be stressed, however, that the prime purpose of path analysis is not to maximise R2, but rather to trace the consequences of a set of causal assumptions; as Duncan (1975, pp. 6546) points out, “it is a mistake-the kind of mistake easily made by the novice-to focus too much attention on R’. Merely increasing RZ by lengthening the list of regressors is no great achievement unless the role of chose variables in an extended causal model is properly understood and correctly presented . high values of R’, in themselves, are not sufficient to evaluate a model as successful”.

Nevertheless, inspection of R2 values provides some indication of the likely impact of variables not explicitly included in the model. In this

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context, the coefficients of determination obtained are 0.28, 0.30, 0.45, 0.73 and 0.20 for agency use, market segmentation, media variety, media intensity and advertising success, respectively. It can be seen that the highest R2 is obtained for media intensity, whereas the lowest R2 relates to advertising success. With respect to the former variable, the high proportion of variance explained can be attributed to the fact that almost all factors that could reasonably be expected to determine the intensity of media usage (i.e. prior research, expertise and availability of funds) were explicitly included in the model. In contrast, it is evident that not all influences that could possibly affect the perceived success of advertising campaigns were incorporated in the model; qualitative aspects of advertising such as the creative content/presentation/timing of advertisements will no doubt have an impact on success and so will environmental factors (e.g. advertising activity by competition). Unfortunately, while it is easy to acknowledge the potential impact of such influences, it is very difficult to model their effects on an a priori basis. While this may initially be perceived as an admission of model mis-specification, this is not necessarily the case, provided that the omitted factors (reflected in the disturbance terms) are not correlated with variables incorporated in the model. 5. DISCUSSION

AND

CONCLUSIONS

The model of the advertising decision process among accountants which was developed and tested in the present study indicates that both financial resources and the use of advertising agencies exert considerable influence on a number of important decision areas relating to advertising. Advertising expenditures were positively related to a greater media presence (more media used, media used more intensively); use of advertising agencies also tended to lead to more intensive media usage and, through market segmentation, to greater media variety. The impacts of financial resources and use of agencies on advertising success were positive and approximately equal (see Tables 3 and 4, respectively), while a positive link was also established between media usage intensity and success. The most surprising finding was the discovery of a negative link between media variety and advertising success which, however, can be subjected to a number of interpretations as already pointed out in Section 4.2.3. At this stage it may be useful to reconsider the nature of the modelling effort that was attempted in this paper. In particular, it should be recognised that the model examined describes the advertisement management process at quite a high level of aggregation; that is, it examines linkages between advertising resources, advertising decision areas and advertising success, using summary descriptors of these constructs. For example, no attempt was made to differentiate between different forms of pre-advertising

24

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research, market segmentation bases, or specific media used; similarly, rather broad indicators of product mix diversity, media variety and advertising success were employed. While modelling at an aggregate level is a first useful step (particularly in the absence of a concrete body of theory/evidence), it is important that future attention be drawn to: a c an in im roving the nature of theoretical links between the con( ) 1 ‘fY’ Ed’ P structs concerned; (b) developing richer measures to operationalise the relevant constructs; and (c) attempting to differentiate between distinct sub-elements of the areas under investigation (i.e. building a less aggregate model). In the context of the present study these considerations imply that it would be useful to reformulate/extend the model presented in such a fashion as to enable more detailed inferences to be drawn regarding the relationships of interest. This could be achieved, for example, by utilising multiple indicators to represent each advertising decision area and recasting the entire model in terms of unobservable (i.e. latent) variables; a LISREL analysis could then be performed on a larger sample of accountancy firms to estimate and test it. The benefits of advertising agency use in terms of expertise have been incorporated into the current model. However, particularly as marketing and advertising become more established activities within accounting practices, it may also be useful to consider internal sources of promotional responsibility and expertise, such as marketing or practice-development partners, managers, etc. It would also be helpful to subject to further examination certain issues for which the present study raised questions rather than provided answers. Specifically, a more detailed investigation of accountants’ market segmentation activities should prove interesting, particularly with reference to the kind of research conducted or considered appropriate; this would serve to clarify the extent to which desk research is used to provide a basis for market segmentation (see Section 4.1.3). Secondly, the relationship between media variety and advertising success is worthy of future attention, both in order to verify (or disconfirm) the finding from the present study and, in case the same pattern is repeated, to establish why media variety is perceived to be counter-productive in the accounting profession; a related issue would be to examine this relationship (as well as the rest of the linkages included in the model) using alternative measures of advertising success (bearing in mind, however, the potential difficulties mentioned in section 4.2.3). Finally, bearing in mind the need for empirical research in the marketing of services, transcending specific industries (Zeithaml et al., 1985), a comparison of advertising practices between accountants and other professionals may be worthwhile. For example, does the model of the advertising management process specified and tested in this paper hold true

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for management consultants or insurance brokers? If not, what are the differences and why do such differences exist? Empirical evidence on such questions would be most welcome, both in terms of increasing the academic’s understanding of the advertising process in a service context and in terms of providing an informational base, which can be used as input by interested parties (such as advertising agencies) in the development of their marketing strategies.

REFERENCES Aaker, D. A. 81 Myers, J. G. (1987). Advertising Management (3rd edn), Englewood Cliffs, NJ: Prentice-Hall. Asher, H. B. (1976). Causal Modeling, London: Sage Publications. Booth, J. (1986). ‘If you’re not sure then ask’, Accountancy, November, pp. 9495. Bradlow, D. A. (1986). ‘Positioning the professional service firm’, Legal Economics, February, Vol. 12, pp. 30-35. Broadbent, S. &Jacobs, B. (1984). Spending Advertising A4oney (4th edn), London: Business Books. Carter, W. K. & Lindgren, J. H. (1981). ‘Marketing professional services’, Buriaess, September-October, pp. 9-13. Carver, M. R., King, E. K. & Label, W. A. (1979). ‘Attitudes toward advertising by accountants’, Financial Executive, Vol. 47, pp. 27-32. Central Statistics Office (1976a). A nnual Abstract of Statistics, London: HMSO. Central Statistics Office (1976b). Social Trends, London: HMSO. Central Statistics Ofice (1988a). Annual Abstract ofStatistics, London: HMSO. Central Statistics Office (1988b). Social Trends, London: HMSO. Congram, C. A. & Dumesic, R. J. (eds). (1976). The Accountant’s Strategic Marketing Guide, New York: Wiley. Darling, J. R. (1977). ‘Attitudes toward advertising by accountants’,_loumal ojdccountancy, February, Vol. 143, pp. 48-53. Davies, E. (1985). ‘Model building: How to market your firm’, Accounrarzcy, January, Vol. 96, pp. 97-99. Diamantopoulos, A., O’Donohoe, S. & Lane, J. (1989a). ‘Advertising by accountants: An empirical study’, Managerial AuditingJournal, Vol. 4, No. 1, pp. 3-10. Diamantopoulos, A., O’Donohoe, S. & Lane, J. (1989h). ‘A comparison of advertising practices within the accounting profession’, Service Industries_loumal, Vol. 9, No. 2, pp. 280-296. Dixon, B. R. & Taylor, D. B. (1979). ‘Advertising: Attitudes and reactions of New Zealand accountants’, The Accountant’sjournal, October, Vol. 58, pp. 337-340. Driscoll, F. (1985). ‘Things will never be the same again’, Accountancy, October, Vol. 96, pp. 120-123. Duncan, 0. II. (1975). Introduction fo Structural Equation Models, New York: Academic Press. Goldberger, A. S. (1970). ‘On Boudon’s method of linear causal analysis’, Amerirafl Sociological Review, Vol. 35, pp. 97-101. Gummesson, E. (1978). ‘Toward a theory of professional service marketing’, Indurtrial Marketing Management, April, Vol. 7, pp. 89-95.

26

A.

DIAMANTOPOULOS

ET

AL.

Gummesson, E. (1979). ‘The marketing of professional services-an organisational dilemma’, European journal ofhlarketing, Vol. 13, No. 5, pp. 308-318. Hill, C. J. & Fannin, W. R. (1986). ‘Professional service marketing strategies in the BOs’, ]ournuf ofProfessional Services Marketing, Fall/Winter, Vol. 2, pp. 11-23. Isaacson, R. W. (1987). ‘Ten reasons why professional service firms fail at marketing’, CPA_lournal, Vol. 57, No. 1, pp. 106-108. King, T. E. 81 Carver, M. R. (1984). ‘CPA advertising: How successful has it been?‘, Financial Executive, Vol. 52, No. 9, pp. 34-42. Kotler, P. (1972). Murketing Management: Analysis, Planning and Control (2nd edn), Engelwood Cliffs, NJ: Prentice-Hall. Kotler, P. (1980). Marketing Management: Analysis, Planning and Cotwol (4th edn), Engelwood Cliffs, NJ: Prentice-Hall. Kotler, P. (1988). Marketing Management: Analysis, Planning, lrnplementution and Control (6th edn), Engelwood Cliffs, NJ: Prentice-Hall. Kotler, P. 81 Andreason, A. R. (1987). Strategic Marketing in Nonprofit Organizations (3rd edn), Engelwood Cliffs, NJ: Prentice-Hall. Kotler, P. & Bloom, P. (1984). Marketing Professional Services, Engelwood Cliffs, NJ: Prentice-Hall. Kotler, P. & Clarke, R. (lY87). Murke&g For Health-Cure Organizations, Engelwood Cliffs, NJ: Prentice-Hall. Kotler, P. & Connor, R. A. (1977). ‘Marketing Professional Services’,journul ofhrlarketing, January, Vol. 41, pp. 71-76. Kotler, P. & Fox, K. A. (1985). Strategic Marketing For Educational Institutions, Engelwood Cliffs, NJ: Prentice-Hall. Land, K. C. (1973). ‘Identification. parameter estimation, and hypothesis testing in recursive sociological models’. In (Goldberger, A. S. 81 Duncan, 0. D., eds), Structural Equation Models in the Social Sciences, pp. 19-49, London: Seminar Press. Listman, R. J. (1988). Murketing Accounting Servicer, Homewood, Ill: Dow Jones-Irwin. Morgan, N. (1988). ‘Marketing in professional accounting firms’. In (Robinson, T. & Clarke-Hill, C., eds), Marketing: Past, Present and Future, Proceedings Annual Conference ojthe Murketing Education Group, 18-21 July, pp. 541-560. Scholten, B. (1984). ‘To advertise or not to advertise. 7’, The Australian Accountant, Vol. 54, pp. 167-171. Teoh, H. 81 Gull, F. (1985). ‘Perceptions of Australian finance managers on the impact of advertising in the accounting profession: Some empirical evidence’, Accounting and Finance, Vol. 25, pp. 41-55. Watkins, T. & Wright, M. (1985). ‘Firm and industry effects on advertising accountancy services’, Service Industriesjournal, Vol. 5, No. 3, pp. 307-321. Williams, B. (1985). ‘Techniques for enhancing your image’, Accountancy, April, Vol. 96, pp. 84-86. Zeithaml, V. A., Parasuraman, A. & Berry, L. L. (1985). ‘Problems and strategies in services marketing’,Journu/ of Marketing, Spring, Vol. 49, pp. 33-46. Dates: Received

30 September,

1988; final version

received

February

1989