3151696

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An Empirical Investigation of the Information Sources Used during the Industrial BuyingProcess Author(s): Rowland T. Moriarty, Jr. and Robert E. Spekman Source: Journal of Marketing Research, Vol. 21, No. 2 (May, 1984), pp. 137-147Published by: American Marketing AssociationStable URL: http://www.jstor.org/stable/3151696Accessed: 17-04-2015 16:54 UTC

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ROWLAND T. MORIARTY, JR. and ROBERT E. SPEKMAN*

It is important for industrial marketers to gain a high degree of synergy among the various elements of their promotional mix. To that end, the authors investigate the sources of information sought by decision participants during the industrial buying process. They also examine those factors that help determine why certain information sources are used during the procurement decision-making process. The results suggest that industrial marketers should consider seriously the use of communications vehicles to supplement the traditional reliance on the industrial sales-

person.

An Empirical Investigation of the Information

Sources Used During the Industrial Buying Process

Is industrial advertising useful, and when during the industrial buying process does it have the greatest impact? Why do buyers attend trade shows/exhibitions, and do sellers use this promotional vehicle appropriately? Do industrial buyers depend on salespeople throughout the buying process or only at specific times? Over the years these and similar questions have been asked by marketers who have sought to understand the informational requirements (both type and source) of the industrial buyer. Given both the increased complexity of the industrial buying process and the sharp rise in the cost of an industrial sales call, marketing practitioners have begun to examine more closely other ways to serve their customer base (i.e., telephone sales, demonstration centers, and industrial stores) as well as to allocate resources within their promotional budgets. With the cost of a local sales call often exceeding $100 (Lohr 1980), marketers would do well to develop more efficient and effective means

*Rowland T. Moriarty, Jr. is Assistant Professor of Marketing, Graduate School of Business Administration, Harvard University. Robert E. Spekman is Associate Professor of Marketing, College of Business and Management, University of Maryland.

The authors thank Paul Bagnoli and Tim Furey for their assistance during the data analysis, as well as Ben Shapiro, Gary Ford, Tom Bonoma, and John Bateson for their helpful comments on a draft of the manuscript. The contributions of two anonymous JMR reviewers are gratefully acknowledged. Any omissions and errors are solely the responsibility of the authors.

for reaching the industrial buyer. Turbull (1974) proposed several years ago that the time has come for marketers to strive for communications synergy. In addition, Morrill (1970) offers empirical support for a more fully integrated industrial communications program by show- ing that industrial advertising enhances the productivity of the personal sales call. Implicit here is the belief that marketers can influence the industrial buyer's decision through the source, timing, and quality of information proivded.

Though a normative, decision-oriented approach to the problem of what mix and level of corporate communications expenditure is useful (e.g., Buzzell and Farris 1976; Lilien and Little 1976) it does little to advance our understanding of those processes, or factors, that might explain why a buyer comes to rely on one information source over another. Any attempt to address the promotional mix problem by advocating communications synergy should be preceded by a basic conceptual understanding of information acquisition and utilization during the industrial procurement process. A small, but growing, body of literature (see Bonoma, Zaltman, and Johnston 1977 for a review) suggests several factors that either mediate industrial buyers' information search and acquisition or inhibit/enhance a firm's procurement/ adoption decision processes; however, this literature is fairly fragmented. By integrating concepts and measures from past research, we attempt to fill a void in the industrial communications literature. Building on past em-

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Journal of Marketing Research Vol. XXI (May 1984), 137-47



JOURNAL OF MARKETING RESEARCH, MAY 1984

pirical findings, we examine the industrial buyer's reliance on various components of an industrial marketer's total communications effort. More specifically, we address two major research questions.

1. What information sources should be emphasized by industrial marketers during the procurement process?

2. What factors help determine the sources of information deemed important by industrial buyers?

RELEVANT LITERATURE

Information Sources Consulted by Industrial Buyers Past research has focused on information acquisition

and utilization during the industrial adoption process (e.g., Baker and Parkinson 1977; Martilla 1971; Ozanne and Churchill 1971; Shiffman, Winer, and Gaccione 1975) and on those information sources consulted during purchases at varied levels of perceived risk/decision uncertainty (e.g., Cardozo and Cagley 1971; Dempsey 1978). Though this area of research is diffuse in both content and focus, a consistent "taxonomy of information sources" can be drawn from the literature. That is, one can array the various information sources investi- gated along two dimensions: commercial/noncommercial and personal/impersonal sources of information. The distinction between personal and impersonal sources of information is discerned rather easily and is based exclusively on face-to-face versus any other type of communications vehicle. The difference between commercial and noncommercial sources of information is less clear. A primary criterion for differentiating the two types is whether or not the information source or organization represented in and/or sponsoring the message benefits financially as a result of a favorable procurement decision. For instance, one can see that a salesperson and an outside consultant are both personal sources of information. A salesperson (or manufacturer's representative) benefits directly from the purchase and is expected by the buyer to take an advocacy and less-than-objective position. In contrast, the consultant (i.e., consulting en- gineer) is likely to be retained because of his or her sub- stantive expertise and is expected to furnish an unbiased, objective appraisal/evaluation of competing products/ proposals.

Most findings from past research emphasize the importance of personal commercial sources of information and stress the ubiquitous and pervasive influence of the industrial salesperson throughout the procurement decision process. Despite the strong reliance on salesperson- generated information, Webster (1968a) and others ob- serve that buyers acknowledge such information content as biased and, in the extreme, may even discount (or distrust) portions of a sales presentation. Other researchers (e.g., Baker and Parkinson 1977; Martilla 1971) have shown that as the procurement decision progresses there is a pronounced increase in the buyer's dependence on information furnished by personal noncommercial information sources. Patchen (1975) suggests that the ability to influence the procurement decision extends beyond

experts and opinion leaders to include users of the equipment. Similarly, Krapfel (1982) argues that these "significant others" (i.e., personal noncommercial sources) can affect dramatically a supplier's chances of acceptance if the supplier can develop an advocate among these noncommercial information sources.

Relatively few studies have examined impersonal commercial sources of information and the findings are less than conclusive. Part of this problem stems from the fact that industrial and trade advertising traditionally has taken a position of lesser importance in the industrial communications mix decision. Certainly, the proportion of promotional dollars allocated to personal sales far ex- ceeds the total expenditures for other, impersonal commercial communications vehicles. Nonetheless, both the importance of industrial advertising and its positive impact on buyers' perceptions of particular vendors have been supported empirically (Morrill 1970; Patti 1979). Furthermore, the literature (e.g., Ozanne and Churchill 1971) seems to suggest that buyers rely on impersonal commercial sources of information to a greater extent earlier in the decision process. As the procurement decision progresses, reliance shifts markedly to internally generated, impersonal noncommercial information sources. For instance, Dempsey (1978) has shown that internal purchasing documents (i.e., vendor reports/ analysis) gain in importance as the decision process pro- ceeds toward supplier evaluation and selection.

Factors Affecting the Use of Different Information Sources

Numerous factors mediate, influence, and channel industrial buyers' information search and acquisition. Such effects have been observed empirically in both the amount of information sought and the sources used during the industrial procurement/adoption process. Marketing scholars generally have focused on four factors: characteristics of the individual decision makers, organizational characteristics, characteristics of the buying situation, and the phases in the buying process.

Research on the effect of individual characteristics on procurement-related information sources has been rather fragmented, examining issues ranging from age to ed- ucational level to decision-making styles (e.g., Martilla 1971; Ozanne and Churchill 1971; Wilson 1971). The findings tend to mirror those in the consumer behavior literature (Engle, Blackwell, and Kollat 1982) and suggest, for example, that more innovative, younger, better educated, and less risk averse managers are more likely to be sensitive to and aware of a number of different information sources. Typically, such managers will search for externally generated information and are less likely to support the status quo in sourcing criteria and ap- proved lists of vendors (e.g., Ozanne and Churchill 1971; Wind 1978). Other research (e.g., Spekman and Stern 1979) has examined boundary-spanning activity and has shown that boundary spanners (usually functionally or hierarchically distinguishable) have different perceptions of environmental uncertainty and, as a result, different

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INFORMATION SOURCES IN INDUSTRIAL BUYING

information search patterns than nonboundary personnel. As organizational members far removed from their organization's technical core (see Thompson 1968), these persons have a greater need for access to externally generated information and are more likely to have a greater network of extra-organizational colleagues with whom they exchange information (e.g., Adams 1976; Keller and Holland 1975).

Organizational characteristics have encompassed such variables as size, profitability, organizational types, and the extent of R&D activities (e.g., Mansfield 1963; Webster 1968b, 1970; Zaltman, Duncan, and Holbek 1973). The research has emphasized primarily industrial innovativeness and adaption and has examined both the degree to which an organization is susceptible to change and the degree to which it is able to acquire, disseminate, and act on relevant innovation-related information. Though the results converge on the findings that more successful and/or more innovative firms are more open to information and appear to adopt organizational struc- tures that facilitate the flow of information into and within the organization (Zaltman, Duncan, and Holbek 1973), conclusions related to size are more equivocal. That is, large organizations support formal mechanisms for greater information exchange and facilitate development of better information sources; however, large size also breeds bureaucracy which tends to inhibit decision participation and informal communications flows (Rogers and Agar- walla-Rogers 1976; Webster 1980).

Marketing researchers (e.g., Cardozo and Cagley 1971; Choffray and Johnston 1979; Dempsey 1978; Gronhaug 1975; Hakansson and Wootz 1975; Lehmann and O'Shaugnessy 1974; Wind 1978) suggest that industrial buyers engage in greater information search, in general, and greater external search, in particular, when the buying situation engenders a higher degree of decision risk and/or turbulence (i.e., conflict, uncertainty, lack of consensus). The pattern of information utilization is based on those vendor/product attributes and information sources deemed pertinent to the buying problem. In addition, the buyers' information utilization extends beyond the salesperson to include a number of manufacturer-generated as well as other sources of procurement-related information. These findings are supported by Robinson, Faris, and Wind (1968) who show that greater decision novelty surrounding the purchase is likely to result in wider, more extended information search and utilization through all stages of the procurement decision process and particularly during the earlier stages. In addition, their findings suggest that greater decision novelty will result in a larger number of organizational participants in the process and that the importance of their input to the decision is more pervasive in the later stages of the procurement process.

Research Propositions The propositions we present posit anticipated theoret-

ical relationships on a global or aggregate level. Each proposition reflects the direction of the relationship be-

tween the industrial buyer's information search and acquisition behavior and each of the four factors shown previously to influence the procurement decision process. Our primary objective is to investigate more specifically those perceptions of the buying situation, characteristics of the organization, individual characteristics, and phases in the buying process that explain under what conditions industrial buyers (defined here as any purposive member of the buying center) seek certain procurement-related sources of information. The propositions are intended to guide the research effort, set the scope of the research, and bridge conceptually the rather fragmented literature upon which the research is based. In short, the propositions provide an organizing framework for the large number of independent variables pre- sented and discussed. On the basis of the literature we have cited, we posit the following illustrative propositions.

1. Industrial buyers will rely on information from impersonal commercial sources of information to a greater extent if the buying situation engenders perceptions of greater conflict, pressure, and/or risk than if the buying situation is perceived to be lower in conflict, pressure, and/or risk.

2. Organizations that are less innovative and/or perceive the buying decisions as routine will rely to a greater extent on information from personal noncommercial sources than will more innovative firms and/or organizations that perceive the buying decision as less routine.

3. Industrial buyers who perceive themselves as more innovative will rely to a greater extent on information from impersonal commercial sources of information than will less innovative industrial buyers.

4. Industrial buyers will rely on noncommercial sources of information (both personal and impersonal) to a greater extent as the buying decision progresses through the various phases of the procurement process than they will in the earlier stages of the process.

METHOD

Research Setting The research context was the decision to purchase

"dumb" or nonintelligent data terminals. A nonintelligent data terminal is a piece of peripheral data processing equipment that must be connected to a central processing unit to be operational. By concentrating on the nonintelligent data terminal market we can examine closely a purchase for which (1) the size and complexity of the relevant decision-making unit vary considerably, (2) the product class is defined by a fairly complete bun- dle of attributes, and (3) the measure of risk is believed to vary among companies, depending on the perceived importance of their information systems. Moreover, the product context allows investigation of a procurement decision process across a range of organizations of different sizes within several different industries.

Sample

During 1979 a stratified random sample of 319 companies was selected from a complete Dun and Bradstreet

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listing. Through a telephone screening process' firms were selected on the basis of whether they had made a major acquisition of "dumb" data terminals in the past 24 months. A major acquisition was defined as the purchase of three or more terminals that were not merely additions to an existing system. Firms included in the final sample also met a second criterion of truly having a multiperson (i.e., two or more people) decision unit responsible for the purchase of the product in question. Firms included in the study were selected from a stratified random sample representing five industrial sectors (business services, transportation, wholesale/retail, finance, and manufacturing) and three size classifications (100-249, 250-1000, and more than 1000 employees).

The next step entailed a determination of the relevant decision participants. For consistency with earlier op- erationalizations of the buying center construct, we chose decisions participants on the basis of their purposive in- volvement in the procurement decision process (Spek- man and Ster 1979; Wind 1978). Though our approach builds on earlier attempts to identify buying center mem- bership, our unit of analysis is the individual, not the buying center. As our objective was to learn about the views of all decision participants, we used an exhaustive snowballing technique. Such an approach is a departure from previous multiperson buying center empirical research (Johnston 1979; Silk and Kalwani 1982; Spekman 1977). An exhaustive snowballing procedure entails con- tacting a focal person (here, a data processing manager) who then identifies a primary group of decision participants with whom he or she interacts during the decision to purchase nonintelligent data terminals. These primary respondents are contacted, their participation in the decision process is verified, and they are asked to identify all those persons who, in turn, influenced their relevant procurement-related decision making. On the basis of their responses a second group of decision participants become eligible for inclusion in the sample. These sec- ondary respondents are contacted and the questioning cycle is repeated. This procedure is continued until no new names are added to the list of decision participants. At least four attempts were made to reach each person named as a decision participant. In total, 1670 questionnaires were mailed to potential respondents and total response rate was 39.7%. Data analysis shows no systematic bias by industry sector or company size.

Dependent Measure

The primary purpose of our research is to gain greater insight about the acquisition and use of procurement-related information. It is important that the dependent measures be relevant to the purchase of nonintelligent data terminals and consistent with past research. The 14

'For more discussion of the telephone screening process and a thorough discussion of the sampling plan and sample, see Moriarty and Bateson (1982).

Table 1 TAXONOMY OF INFORMATION SOURCES USED BY

INDUSTRIAL BUYERS

Personal Impersonal

Commercial Salespeople Advertising in trade publications Trade shows Sales literature Noncommercial Information systems dept.a News publications Top managementa Trade associations Using dept.b Rating services Terminal usersb Outside consultanta Colleaguesa Purchasing dept.a

aThese information sources can be described as influencers. 'These other information sources can be described as users.

information resources shown in Table 1 encompass a comprehensive distillation of past research findings (e.g., Dempsey 1978; Kelly and Hansel 1974; Martilla 1971; Ozanne and Churchill 1971; Webster 1970). In addition, the cell containing personal noncommercial information sources is broken down further to distinguish between users and influencers. Not only does this further delin- eation represent more closely two of Webster and Wind's (1972) buying center roles, it also enables us to examine aspects of intra-organizational influence (e.g., Patchen 1975) and provides potentially richer insights to the data. Composite scales representing each of the four cells2 shown in Table 1 were constructed. More precisely, the resultant composite variables represented an additive combination of each information source shown in each cell. These composite measures, reflecting different information sources, became input to the multiple regression analysis.

Independent Measures

Reliance on a particular source of information has been shown to be affected by several different factors circum- scribed by perceptions of the buying situation, characteristics of the organization, individual characteristics, and the particular phases of the buying process. In the Appendix we list and operationalize the set of independent variables used in our study. These variables are grouped into four primary sets of explanatory measures. Whereas past research typically examined only one set of explanatory variables, our research is an attempt to combine a range of diverse explanatory variables from numerous past empirical studies for a more comprehensive and thorough investigation of the factors affecting the extent of reliance on a particular information source. Our use of several different independent variables evolves

2The personal noncommercial information sources were broken down further and additional dependent measures constructed for "users" and "influencers."

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from a rather extensive tradition of organization buying/ industrial marketing research. Thus, it should be under- stood that the variables included in our analysis are those which, on the basis of past theoretical and empirical development, are expected to contribute to our ability to (1) explain better the industrial communication process and (2) synthesize a fragmented research base.

Data Analysis Procedure

A central aim is to synthesize the rather fragmented literature on industrial marketing communications research as it relates to determining which factors explain a decision participant's reliance on a particular source of information. Given the complex nature of the industrial buying process, multiple regression analysis enables us to investigate the simultaneous effect of situational, organizational, individual, and decision phase variables on the importance attributed to a more parsimonious array of information sources used by organizational decision participants. The dependent measure for each multiple regression equation is the composite variable constructed from Table 1.

To investigate the relationships proposed, we performed a series of stepwise regression analyses with each of the criterion variables. Stepwise regression was em- ployed primarily to identify those variables, distilled from past research, that were related significantly at the 0.05 level and beyond to each dependent variable (see Cohen and Cohen 1975). Then each of the reduced models was run in a multiple regression equation to measure the simultaneous influence of the independent variables.

RESULTS AND DISCUSSION

Relative Importance of Information Sources

As a first step in reporting the findings, we discuss the relative importance of each of the 14 information sources (Table 2). Such a discussion enables us to investigate each of the variables prior to an exposition of

Table 2 PERCEIVED IMPORTANCE OF INFORMATION SOURCES

Information sources Meana S.D.

Information systems department 5.011 1.257 Using department 4.688 1.406 Top management 4.213 1.528 Salespeople from manufacturer 3.862 1.454 Actual terminal operators 3.767 1.543 Sales literature 3.446 1.504 Colleagues in other companies 3.220 1.505 Rating services 2.848 1.672 New stories in trade publications 2.684 1.424 Trade association data 2.510 1.478 Trade shows 2.473 1.513 Advertising in trade publications 2.290 1.290 Outside consultants 2.090 1.489 Purchasing department 1.675 1.086

aThe scale ranged from not important = 1 to very important = 6.

the composite dependent measures of information sources. Corroborating earlier findings (Webster 1968b) is the interesting fact that of the seven most highly ranked information sources listed, six are personal and five of those represent noncommercial information sources. One would expect that "expert" advice supplied by the information systems department (X = 5.011) would be relevant in assessing general system requirements, capability, etc., whereas information sought from the using department (X = 4.668) probably would relate to a determination of departmental needs and performance expectations about the data terminal equipment. It is interesting also to recognize the relative importance attributed to the actual users of the equipment-the terminal operators (X = 3.767). At the other extreme, top management (X = 4.213) is likely to be consulted during the process by virtue of their fiscal and supervisory responsibility. Iron- ically, the purchasing department (X = 1.675) is viewed as the least influential information source. Given the fairly technical nature of our research context, however, the finding is not totally unexpected despite procurement's responsibility for the purchasing workflow.

Decision participants seem to rely fairly heavily on information provided by the manufacturer either through its salesforce (X = 3.862) or its sales literature (X = 3.446). Both of these information sources provide specific performance, cost, and technical information. Although the data suggest that information furnished through manufacturers' "spec" sheets, brochures, catalogs, or other direct mail communications is important to industrial buyers, one should not ignore the finding that an "informational" public relations piece (i.e., news story) in a trade publication about recent corporate de- velopments or product/service improvements can be a rather compelling information source to the decision participant.

Factors Determining Use of Information Sources Table 3 summarizes the multiple regression results for

each of the separate multiple regression equations. Only the standardized beta coefficients and the t-statistic for each of the independent measures contributing to the explained variance that is significant at the p - .05 level are shown. Overall the R2 values range from .095 to .182. In the following discussion, organized according to the major sources of information used by the decision participants, we examine the conditions under which the various information sources are important to buying center members. Within each section the findings are ar- rayed so that each of the independent variables is grouped according to its more general category of explanatory measures (i.e., perceptions of the buying situation, characteristics of the organization, individual characteristics, and phase of the buying process). Personal Commercial Information Sources

The results show that more than 50% of the explained variance in the model is attributable to the decision par-

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Table 3 SUMMARY OF MULTIPLE REGRESSION ANALYSIS EXPLAINING THE USE OF EACH INFORMATION SOURCE

Information sources

Independent Personal Personal Impersonal Impersonal variables commercial noncommercial commercial noncommercial

Characteristics of the buying situation CONFLT 0.19 0.14 0.13

(t = 17.95) (t = 9.17) (t = 6.82) PERCONF 0.12

(t = 7.05) RISKO1 0.09 0.12

(t = 3.8) (t = 7.13) RISKO2 0.15

(t = 10.6) Organizational characteristics

ACQUIS DECN 0.07 0.09 0.08

(t = 2.59) (t = 3.98) (t = 3.18) INNOV -0.08 -0.10

(t = 3.16) (t = 4.98) LOYAL 0.13

(t = 8.21) SIZE -0.10 -0.12

(t = 5.52) (t = 7.02) Individual characteristics

FUNCadn,u 0.12 -0.17 -0.12 (t = 6.4) (t = 12.03) (t = 5.82)

FUNCusng dept 0.15 -0.13 -0.13 (t = 10.2) (t = 7.01) (t = 6.70)

HIERpper 0.11 (t = 4.68)

HIERlower/mid Phases in the decision process

RECOG 0.19 0.09 0.14 (t = 17.38) (t = 3.99) (t = 8.47)

SEARCH 0.12 0.11 0.17 0.28 (t = 7.24) (t = 5.17) (t = 14.06) (t = 20.75)

VENDOR -0.16 (t = 6.52)

F of regression equation 11.48 10.64 9.18 7.73

R2 of regression equation .157 .182 .095 .139

ticipants' particular phase in the decision process. More- over, the data appear to substantiate the pervasive impact of personal sales throughout the procurement decision process. The positive coefficients associated with both RECOG (P = 0.19) and SEARCH (P = 0.12) suggest that decision participants come to rely on personal sales, either through a sales call or a trade show, at the recognition-of-need stage and later during the search-for- alternative-vendor stage of the buying process. In addition, the positive coefficient associated with CONFLT (3 = 0.19), explaining an additional 24% of the variance in the model, suggests that industrial buyers rely more heavily on personal commercial sources of information when the buying decision engenders higher levels of decision conflict. A greater dependence on this information source during periods of decision turbulence is supported further by the positive coefficients associated with both

RISKO1 (P = 0.09) and PERCONF (P = 0.12). More specifically, industrial buyers appear to depend on personal commercial information sources when higher de- grees of economic risk are associated with the purchase. Thus, industrial buyers apparently rely on personal commercial information sources not only to help shape the decision during the problem-recognition stage and again to narrow the evoked set of potential suppliers during the search-for-alterative-vendor phase, but also seek these information sources when faced with higher levels of decision turbulence.

Finally, the results show that two organizational characteristics contribute to the model's explanatory power and help us further understand under what conditions industrial buyers come to rely on personal commercial sources of information. Though marginally significant, the coefficients associated with DECN (3 = 0.07) and

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INNOV (p = -0.08)3 suggest, respectively, that organizations having more experience with similar procurement decisions or are perceived as more innovative by their members rely to a greater extent on salespeople and trade shows/exhibitions. On the basis of previous research (e.g., Webster 1980), we would expect more innovative firms to be more receptive to personal commercial information sources. However, more experienced firms would be less likely to rely on those information sources. This finding adds to the pattern of widespread use of and pervasive reliance on commercial personal sources of information by industrial buyers. Personal Noncommercial Information Sources

Research (see Galper 1979 for a review) points to the importance of information elicited from "significant others," or opinion leaders, within one's company during the procurement decision process. Our findings are consistent with that research. For instance, the results show that variables representing characteristics of the buying situation together account for close to 50% of the explained variance in the model. More specifically, the positive coefficients associated with CONFLT (p = 0.14), RISKO1 (P = 0.12), and RISKO2 (p = 0.15) suggest that decision participants rely more heavily on personal noncommercial information sources during periods of greater decision conflict and when the purchase is felt to contain elements of both performance and economic risk for the purchasing unit. In addition to building an ar- gument for the importance of significant others as potential conflict-resolution and risk-reduction mechanisms, these findings broaden the conventional wisdom which tends to limit the influence of significant others to later stages of the decision process. The positive coefficients associated with RECOG (P = 0.09) and SEARCH (p = 0.11), together accounting for an additional 17% of the variance, suggest that industrial buyers rely on personal noncommercial information sources during both the problem-recognition and search-for-alternative-vendor stages of the process.

Interestingly, one's functional role influences the degree to which one relies on personal noncommercial sources of information. The positive coefficients associated with FUNCadnin (P = 0.12) and FUNCsers (P = 0.15) suggest that, though both types of personnel rely on information furnished by significant others, persons in the using department are more dependent on this information source. This finding adds credence to the importance of word-of-mouth communication during the industrial diffusion/adoption process (Webster 1968b, 1980).

Explaining slightly more than 25% of the variance in the model, the variables representing organizational characteristics provide interesting findings. The positive

3This variable is reverse scored, i.e., a lower score connotes higher perceived innovativeness.

coefficient associated with LOYAL (3 = 0.13) suggests that the more source-loyal buyers rely to a greater extent on personal noncommercial information sources whereas the negative coefficient associated with SIZE (P = -0.10) implies that smaller organizations depend more on these significant others for procurement-related information than do larger organizations. We would expect the more source- loyal buyers to be less receptive to externally generated information and more open to information from within their own firm. We would predict also that smaller organizations, having fewer resources and personnel to de- vote to the development and accumulation of internally generated procurement information, would seek information actively from outside sources. It is important to note that these sources of personal noncommercial information often are colleagues in other organizations.

In Table 4 we can examine more closely the use of personal noncommercial information sources by cate-

Table 4 SUMMARY OF MULTIPLE REGRESSION ANALYSIS

EXPLAINING USE OF PERSONAL NONCOMMERCIAL INFORMATION SOURCES

Independent Information sources variables Users Influencers

Characteristics of the buying situation CONFLT 0.10 0.12

(t = 4.68) (t = 6.42) PERCONF RISKO1 0.19

(t = 17.22) RISKO2 0.09 0.13

(t = 4.08) (t = 8.21) RISKO3 0.09

(t = 3.99) Organizational characteristics

ACQUIS 0.09 -0.08 (t = 4.39) (t = 3.28)

DECN 0.09 (t = 4.45)

INNOV -0.09 (t = 3.97)

LOYAL 0.16 (t = 12.52)

SIZE -0.09 -0.09 (t = 3.61) (t = 3.61)

Individual characteristics FUNCan 0.15

(t = 9.26) FUNCsng dept 0.15

(t = 10.00) HIERlower/md

Phase in the decision process RECOG 0.11

(t = 5.53) SEARCH 0.15

(t = 8.96) VENDOR F of regression

equation 7.55 8.07 R2 of regression

equation .137 .157

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gorizing these individuals as "users" or "influencers." By comparing these findings one can draw important distinctions about the industrial buyer's use of these two information sources. For instance, the positive coefficients associated with ACQUIS (P = 0.09) and DECN (3 = 0.09) suggest that buyers rely more heavily on users when they have more experience with the purchasing context. The negative coefficient associated with ACQUIS (P = -0.08) implies, in contrast, that influencers are less important sources of information when buyers have greater past experience with similar types of purchases. However, influencers rather than users seem to be consulted when the risk associated with the purchase reflects on the buyer personally (RISK 03, 3 = 0.09). In addition, the reliance on influencers appears to be greater across functional roles as is indicated by the positive coefficients associated with FUNCadmin (P = 0.15) and FUNCusing dept (3 = 0.15). Furthermore, the positive coefficient associated with RECOG (3 = 0.11) suggests that influencers are consulted earlier in the decision process than users, who appear to have a more significant role during the search-for-alternative-vendor (SEARCH, 3 = 0.15) phase of the process. The inference here is that influencers may help shape and define the decision context whereas users may help define further the set of relevant decision criteria after general procurement pa- rameters have been set. One can envision easily the user- generated information being more procedural in content (i.e., "what the terminal should do") and the influencer information being more technically and performance oriented (i.e., "what the terminal is capable of doing, how effectively and how efficiently"). Moreover, because of the positive coefficient associated with LOYAL ( =

0.16), the more source-loyal buyers, utilizing a more constrained choice set, appear to rely more heavily on influencers. Though we cannot conclude whether users or influencers are more important to the industrial buyer, the two information sources appear to be used differ- ently.

Impersonal Commercial Information Sources

The results suggest that industrial buyers use impersonal commercial sources of information (i.e., sales literature and trade advertising) during the search-for-alternative-vendor stage of the process. In fact, SEARCH (p = 0.17) accounts for 47% of the total variance in the model explaining why buyers use impersonal commercial information sources. Interestingly, past research (Webster 1968, 80) suggests that vendor-furnished information would be sought more purposively during the earlier stages of the process. In addition, the negative coefficient associated with SIZE (P = -0.12) suggests that smaller firms rely more heavily on such information sources. This finding is consistent with previous research results and supports the notion that smaller organizations are less likely to develop in-house vendor and/or product-specific data banks.

Despite this potential "information gap," the negative

coefficients associated with FUNCadmin (P = -0.17) and

FUNCusing dept (P = -0. 13) suggest that both administra- tors and users rely on this information source to a lesser extent than do personnel from the data processing department. Because vendor-supplied product information is likely to be technical, this finding is not surprising. Though we do not examine the possibility explicitly, data processing people, by virtue of their functional expertise, appear to have a potentially important role in the transfer of vendor/product-related information. Further- more, this specialized procurement-related information transfer function adds credence to the importance of word- of-mouth information flows during the procurement process. Finally, the marginally significant coefficient associated with DECN (P = 0.09) suggests that buyers having greater past experience with similar decisions rely more heavily on impersonal commercial sources of information. Perhaps as a buyer's experience with a specific purchase increases, he or she develops greater ease with and knowledge of product/vendor-related information and feels more comfortable in evaulating competing offers without assistance from others.

Impersonal Noncommercial Information Sources

The three variables encompassing different phases of the decision process together account for 65% of the variance in the model, of which RECOG (P = 0.14) and SEARCH (P = 0.29) represent more than 95%. This finding suggests that industrial buyers seek actively the more objective, less biased nonpersonal information sources (e.g., rating services) both during the earlier phases of the decision process as the problem is being shaped/defined and later during the search-for-alternative-suppliers stage of the procurement process. Inter- estingly, buyers rely little on such information sources during the actual vendor-selection phase of the process (VENDOR, 1 = -0.16). Though this finding is seem- ingly contrary to expected results, one plausible explanation is that during the actual selection phase industrial buyers' information requirements may pertain more directly to manufacturer-generated information related to the final proposal or bid.

Buyers also appear to rely on impersonal noncommercial sources when a higher degree of conflict is associated with the purchase decision (CONFLT, 3 = 0.13). This desire on the part of the buyer to seek a more objective source of information during periods of higher decision turbulence has not been discussed previously in the literature, though Dempsey (1978) does make ref- erence to the use of purchasing records and other such documents. Nonetheless, such a finding carries strong intuitive appeal. Also, the negative coefficient associated with INNOV (P = -0.10) suggests that the more innovative organizations are more open to a number of information sources and that buyers in such organizations are less likely to be bound exclusively to manufacturer-generated information.

Individual characteristics provide some interesting in-

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sights about the use of impersonal noncommercial information sources as both hierarchical level and functional role influence the industrial buyer's information acquisition and utilization. The positive coefficient HIERupper (P = 0.11) suggests that upper level personnel rely on such information sources to a greater extent than others. This finding is supported by research suggesting that upper level managers engage in different kinds of information search and are more sensitive to different information sources than are other organizational members (see Aguilar 1976). Though certainly not conclusive, these findings portray upper level managers as depending on more objective, more general kinds of vendor and/or product-related information. Across functional roles, both administrative personnel (FUNCadmin, P = -0.12) and persons in the using department (FUNCusingdept, P = -0.13) rely on impersonal noncommercial information sources less than do data processing personnel. This finding is consistent with the specialized information search, acquisition, and filtering activities that accompany organizational differentiation/division of labor (see Adams 1976; Thompson 1968). More specifically, data processing personnel appear to be more sensitive to these particular procurement-related information sources and may filter and disseminate this information to other organizational functions.

IMPLICATIONS

Our findings hold specific implications for the industrial marketer that warrant further elaboration. Past research tends to downplay the efficacy of commercial impersonal sources of information and seems to limit the impact of industrial advertising and other supplier-generated information to the earlier stages of the procurement decision process. Our findings suggest that manufacturer-generated information (i.e., direct mail pieces, catalogs) is sought by decision participants at other than the earliest stages of the decision process and appears to be particularly useful to smaller organizations. Because the amount of information available to the buyer is a function of the seller's total promotional budget, and the cost associated with a personal sales effort continues to escalate, such information sources warrant greater scru- tiny by industrial marketers than earlier research implies. For instance, it might be feasible to segment one's market by size and to direct communications efforts accord- ingly because smaller firms appear to be more receptive to impersonal commercial communications vehicles. Though beyond our findings, the use of industrial advertising and direct mail to supplement telephone sales or other more expensive "personal contact" sales strate- gies would enable marketers to decrease the sales ex- penses associated with servicing smaller accounts.

Impersonal noncommercial sources of information have received little attention previously. As this information is independent of the seller's "control," one easily ap- preciates the paucity of empirical research. Nonetheless, industrial buyers, particularly higher level personnel, do

appear to rely on these sources of information at different phases during the purchasing process. This finding supports the central role of "relative quality" in one's marketing program because rating services and other independent evaluations seem to be valued information sources. Also, the implied link between one's image and reputation and sales performance is brought to the fore. Porter (1981) mentions the use of the media as a competitive weapon because press releases and news stories can be used to gain a competitive edge.

Our findings emphasize also the importance of personal noncommercial information sources throughout the decision process. Other researchers have acknowledged that these information sources become more important during later stages of the buying process, but our findings do not place such a limiting role on the utility of these sources. Differentiating between users and influencers, we find that the nature and scope of information sought by decision participants depend on the source of personal noncommercial information used. Through a microsegmentation approach the industrial marketer must pinpoint the relevant actors, tailor the message (both personal and impersonal), and recognize the importance of gaining an advocate (see also Krapfel 1982) among those persons on whom upper level managers rely to furnish purchasing-relevant information. Clearly, the importance of focusing attention on experts and opinion leaders is emphasized; however, the data suggest also that marketers should not ignore users because they do help shape the decision outcome as it progresses. The ability to trace and understand the communication patterns within the buying unit is an important part of the industrial communications process. Access to the powerful members of the decision group is important, but our findings (not reported here) suggest that access to the "gatekeep- ers" who collect, filter, and transmit purchasing-relevant information to the key decision makers is no less important (i.e., Pettigrew 1973).

Our results support earlier conclusions that the industrial salesperson has a critical role as a valued source of information and a stimulus at all stages during the industrial buying process. In fact, the findings suggest that when decision participants are very concerned about making the correct decision they tend to rely heavily on the manufacturer's salesperson. Nonetheless, a central premise of our research, which is also substantiated by the findings, is that the industrial marketer should not rely exclusively on the salesperson. Our findings provide compelling evidence for a comprehensive promotional plan that includes several different communications vehicles. Though previous research has indicated that impersonal sources of information are useful in comple- menting or bolstering a sales presentation, our findings suggest that, under certain conditions, these other information sources might be a substitute for a personal sales call. Competitive pressures, inflation, slow growth, ma- terials shortages, etc. are placing extreme demands on industrial marketers to gain greater efficiency and effec-

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tiveness within their marketing programs. Our findings imply that greater use of a number of different communications vehicles can result in heightened synergy and coordination among the various elements of a firm's promotional program.

SUMMARY

Past research has shown that an industrial buyer's sen- sitivity to and/or perceived utility for procurement-related information depends on characteristics of the buying situation, the buying organization, the individual decision maker, and the stage in the buying process. Though earlier research has provided a fairly sound base of knowledge upon which industrial marketers can build a better understanding of the industrial marketing communications process, much of that research is fragmented. That is, researchers generally have studied only one communications vehicle (i.e., trade shows or in-

dustrial advertising) or have examined the impact of a particular type of explanatory variable (i.e., perceived risk, stage in the decision process) on an industrial buyer's search for purchasing-relevant information. A major contribution of our research is the synthesis of a diverse body of literature into a rather comprehensive research paradigm. We not only address a more complete listing of information sources used by industrial buyers, but also include in the regression equations an array of predictor variables encompassing those different situational, individual, organizational, and buying phase factors that previous research has shown to influence the type(s) of information source deemed important by decision participants. Thus, our research affords a richer explanation of why industrial buyers use particular information sources and an appreciation for the need to develop and imple- ment a comprehensive, coordinated approach to the industrial communications process.

APPENDIX INDEPENDENT VARIABLES AND THEIR OPERATIONAL DEFINITIONS

Definition

CONFLT

PERCONF

RISKO1-RISK03

ACQUIS

DECN

INNOV

LOYAL

SIZE

FUNC

HIER

RECOG

SEARCH

VENDOR

Characteristics of the buying situation A contextual variable measuring the degree of conflict the respondent perceived this purchase entails in relation to

other decisions in which he/she normally is involved. Scores ranged from 1, "much less conflict," to 6, "much more conflict."

A variable measuring the respondent's sense of confidence associated with the purchase decision. Specifically, re-

spondents were asked to relate how important it was for them to have a personal feeling of "confidence" about the

product. Scores ranged from 1, "not important," to 6, "very important." Three variables measuring different dimensions of perceived risk. RISKO3 measures the perceived personal conse-

quences of selecting a data terminal that is less economical than projected. Scores on these variables ranged from 1, "would not affect my position or credibility," to 6, "would highly endanger my position and credibility." RISKO measures the perceived consequences to the buying unit if their data terminal were less economical than projected and RISKO2 measures the perceived consequences to the buying unit if the terminal were less reliable than pre- dicted. Scores on both variables ranged from 1, "of little consequence to the buying unit," to 6, "potentially catastrophic."

Organizational characteristics A dummy variable describing the type of acquisition. If the acquisition was a "pilot" or "implementation" it was

categorized as 0; if it was a "replacement" or "expansion" it was categorized as 1. A variable measuring the firm's degree of experience with similar kinds of purchase decisions. Specifically, respon-

dents were asked to relate the number of major data terminal decisions their company had made in the past five

years. A variable measuring the degree of perceived innovation within an organization. Respondents were asked to rate their

organization's attitudes toward product selection decisions. Scores ranged from 1, "liked to be on the forefront," to 3, "prefer to wait for market acceptance before acceptance."

A composite variable measuring the degree of importance associated with purchasing data terminals from present vendors and from present mainframe manufacturer. Scores ranged from 1, "not important," to 6, "very important."

A dummy variable measuring the size of the organization by number of employees. If the organization had less than 250 employees the variable was coded 0; if it had 250 or more the variable was coded 1.

Individual characteristics An individual, three-level dummy variable representing the function performed by the individual respondent. One

level represents those in administrative positions (1, 0), a second level encompasses those functional departments that would be users (0, 1), and the third represents those who work in data processing (0, 0).

An individual, three-level dummy variable describing a respondent's level of authority (or hierarchical position) within the organization. The three levels are top (1, 0), middle and first line (0, 1), and senior and junior staff (0, 0).

Phase in the buying process One of several variables that examine the degree of importance each respondent felt he had at a particular stage in

the buying procurement process. This variable measures the perceived importance of respondent's role in the rec-

ognition of the need for an information system incorporating a data terminal. Scores ranged from 1, "not important," to 6, "very important."

A variable measuring the perceived importance of the respondent's role in the search-for-alternative-vendor phase of the decision process. Scores ranged from 1, "not important," to 6, "very important."

A variable measuring the perceived importance of the respondent's role in the vendor-selection stage of the decision process. Scores ranged from 1, "not important," to 6, "very important."

Variable name I

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