Introduction

The role the Internet plays in business-to-business (B2B) purchasing activities is evolving, with applications, technology, and systems remaining dynamic. Predictions abound, and promises of unprecedented benefits are widespread. By 2003, B2B activities on the Internet are expected to be six times as large as business-to-consumer (B2C) activities (Cohn, Brady and Welch 2000). B2B sales are predicted to be $2.7 trillion in 2004 (Blackmon 2000). With B2B Internet usage, purchasing cost reduction estimates range from ten to thirty percent over the next five years (Cohn, Brady and Welch 2000; Strauss and Frost 2001). Yet evidence supporting such claims is certainly speculative.

Use of the Internet to expedite purchasing transactions through reduced cycle time and lowered labor costs is reported to be escalating. However, little research has been executed that examines industrial buyers' perceptions of this tool. From a sales management perspective, a better understanding of the extent of industrial buyers' Internet use and their perceptions of the role of this technology (i.e., as a replacement for salespeople or as a means to augment the purchasing process) would be helpful. Such a concern warrants inquiry as some sources (e.g., Sheth and Sisodia 1999) project the Internet may well supplant the use of salespeople.

The first step in understanding how online purchasing impacts the role of the sales force would be to investigate how professional buyers employ the Internet in purchasing. Toward this end, and as shown in Figure 1, we address three research questions:

RQ1: How are purchasing professionals using the Internet (RQ1a), and what benefits do buyers seek from online buying-related activities (RQ1b)?

RQ2: To what extent do buyers' demographic or organizations' structural characteristics distinguish professional buyers who are current Internet users from nonusers?

RQ3: What individual, organizational, or market variables influence professional buyers' propensity to use the Internet?

Our goal in exploring these questions is to initiate a knowledge base of professional buyers' needs, experiences, and expectations concerning online purchasing activities. As sales management gains greater understanding of how industrial buyers perceive and use online options, strategies can be devised and implemented to serve such uses (Hunt and Bashaw 1999).

To address our research questions, we first review literature relevant to B2B online purchasing activities. We then briefly describe our research methodology and present our findings related to each of our research questions. Next, we discuss our study findings in terms of implications for the sales force. Finally, we present ideas for further research of B2B Internet use and the role of the sales force as this technology evolves.

[FIGURE OMITTED]

Background for Research Questions

When considering the Internet and its possible effect on the sales role, a distinction must be made between using the Internet as an information gathering tool versus its use as a transactional tool (i.e., e-commerce). Undoubtedly, these two scenarios have different ramifications for salespeople. When viewed as an information gathering tool, the Internet may be used by suppliers to gather information, with salespeople still involved in consummating the actual transaction. Alternatively, suppliers using the Internet as a transactional tool may both gather information and conduct transactions online, thereby drastically changing or eliminating the sales role. Before consequences for the sales force can be identified, and appropriate strategies developed, basic questions regarding buyers' Internet use must be answered. Toward this end, the following sections establish the rationale for each of our research questions.

RQ1: B2B Internet Use and Benefits

Our first research question addresses the basic issues of how and why organizational buyers are using the Internet for purchasing activities. Given that industrial purchasing firms are carefully examining the utilities to be gained through the use of online purchasing systems, sales organizations need to understand more precisely what uses and benefits buying organizations seek from the Internet. For example, organizations are considering a variety of information gathering and transaction-based activities, including e-mail, customer service functions, and purchase transaction functions (Strauss and Frost 2001). Importantly, the use of these activities may vary across purchase situations, with purchasing professionals facing multiple buying situations, such as routine reorders, reorders with slight modifications, reorders with major modifications, simple new purchases, and complex new purchases (Robinson, Faris, and Wind 1967). Benefits sought by online buyers might include increased access to information, the ability to reduce costs, and the ability to reduce cycle time in the purchasing process.

Little research has been completed in this emerging area, necessitating an exploratory approach. Toward this end, RQ1 descriptively addresses the questions: How are purchasing professionals using the Internet (RQ1a); and what are the perceived key benefits of buying online (RQ1b)?

RQ2: Demographic Differences Between Users and Nonusers of Internet Purchasing Resources

The identification of demographic differences between users and nonusers can lead to the development of buyer profiles, which in turn can be useful to sales practitioners seeking to integrate the Internet with their personal selling efforts. Accordingly, with our second research question, we seek to determine if professional buyers currently using the Internet for purchasing activities can be distinguished from nonusers of this technology through buyers' personal characteristics and structural characteristics of their organizations.

Although research examining online buying behavior in an industrial context is scant, research conducted in the consumer buying environment provides some guidance. Data indicate that online buying increases as a buyer's income, education, and age increase (Bellman, Lohse and Johnson 1999; Kehoe, Pitkow and Rogers 1998). Evidence also suggests males are more likely to buy online than females (Pitkow and Kehoe 1996; Stores 1998), although this gender gap may be narrowing (Ebenkamp 2000).

In light of such, we expect that a buyer's use of online transactions will be greatest for older, more educated buyers. We also expect that males are more likely than females to buy online in an industrial context. We could find no studies examining years of purchasing experience relative to online buying behavior. However, it seems plausible that years of purchasing experience correlates positively with age. As such, we expect that professional buyers with more years of purchasing experience will be more likely to conduct corporate-related purchasing activities online.

In an industrial context, organizational demographics may also differentiate use of online resources. Research on the adoption of innovations by organizations suggests that buyers in larger organizations would have access to more resources, and consequently may be more likely to use the Internet for purchasing (Baldridge and Burnham 1975; Kimberly and Evanisko 1981; Moch and Morse 1977). Number of employees and sales revenue are structural indicators of the size and resources available to the firm and the buyer (Hurley and Hult 1998; Parasuraman 1981). Likewise, the number of product categories bought provides an indirect indication of organizational size, as well as the breadth of buyer responsibility. Accordingly, we expect that organizational buyers who have responsibility for more product lines and who work in firms with greater numbers of employees and higher sales revenues will be more likely to use the Internet for online purchasing activities.

RQ3: Personal and Organizational Variables Influencing Professional Buyers' Propensity to Use the Internet

To develop effective selling strategies, those organizations incorporating the Internet will require an understanding of buyers' intentions to use online information and resources. Of utmost importance is the identification of those variables influencing buyers' intent to use the Internet for corporate purchasing activities. Exploring future intent is critical at this early stage when not all buyers have Internet resources (Fishbein and Ajzen 1975). Based on existing diffusion of innovations research (e.g, Cool, Dierickx and Szulanski 1997; Gatignon and Robertson 1989; Huff and McNaughton 1991; Phillips, Calantone and Lee 1994; Rivers and Dart 1999; Robertson and Gatignon 1986; Rogers 1962; Wozniak 1987) and more recent work on the online experience of consumers (e.g., Hoffman and Novak 1996; Novak, Hoffman and Yung 2000), we identified three classes of variables that may influence buyers' propensity to conduct corporate-related purchasing activities online: (1) buyers' perceptions of technology, (2) organizational influences, and (3) market conditions.

Buyers' Perceptions of Technology. Theory and logic suggest a buyer's perception of technology impacts that buyer's desire to adopt a new technological innovation. Novak and Hoffman (2000) observe that buyers' perceived innovativeness, defined as the extent to which users prefer a variety of innovative experiences in their lives, positively influences use of technology. Novak, Hoffman, and Yung (2000) contend perceived Internet skill, the extent to which buyers feel they are adept at using the Internet and are knowledgeable about good search techniques, also influences technology use. Phillips, Calantone, and Lee (1994) found that the attitude and behavioral intention to adopt a new technology is dependent on the perceived benefits of the technology. As such, perceived communication convenience, the extent to which buyers expect the Internet to be a more convenient communication and purchasing tool when compared to more traditional sources, such as salespeople and customer service employees, might also influence buyers' technology use.

The expected influence of these personal variables is straightforward. Consider a buyer who does not like change, is not particularly innovative, is uncomfortable using the Internet, and does not understand the benefits of this new technology. It is likely this buyer is more resistant to change, content with the current order routine, and resistant to the Internet as an innovation that threatens to change the established routine (Ram 1987; Sheth 1981). At the other extreme, buyers who consider themselves to be innovative, with strong Internet skills and a keen understanding of the benefits offered by this new technology, will be more likely to embrace this innovation (Novak and Hoffman 2000; Novak, Hoffman and Yung 2000; Phillips, Calantone and Lee 1994). Accordingly, our expectation is that perceived innovativeness, perceived Internet skill, and perceived communication convenience positively influence organizational buyers' propensity to use the Internet for industrial purchasing activities.

Organizational Influences on Use of the Internet by Industrial Buyers. Several researchers have noted the importance of supplier support of online purchase systems, the degree to which purchasing professionals perceive their suppliers are providing encouragement, guidance, and incentives for purchasing via the Internet. For example, Gatignon and Robertson (1989) found that vendor support, through such mechanisms as educational seminars and monetary incentives, relates positively to the adoption of a new technology. Similar results were obtained by Cool, Dierickx and Szulanski (1997), who concluded that supplier-related factors were more likely to accelerate the acceptance of an innovation than demand-related factors. Along a related line, Huff and McNaughton (1991) suggested that ongoing training and support are critical to the successful adoption of a business system innovation.

The potential for cost reductions resulting from a move to online purchasing activities represents a consistent theme in the trade literature (Ansberry 2000; Champy 1999). These cost reductions, if realized, may provide online purchasing processes with a relative advantage over more traditional methods of buying (Gatignon and Robertson 1985). As such, the perceived pressure to reduce costs of buying a buyer perceives within the organization emerges as a likely determinant of that buyer's propensity to use the Internet for corporate purchasing.

Final]y, opinion leaders and personal influence have been identified as components of diffusion theory (Gatignon and Robertson 1985). Diffusion research suggests that individuals with greater access to relevant personal information sources are better able to evaluate and adopt innovations (Gatignon and Robertson 1989). Within the context of industrial purchasing, personal influence should manifest itself as the perceived influence of other departments--the extent to which buyers' purchase decisions are affected by other organizational members. Previous research contends that members of various departments within an organization, such as production/operations and marketing/sales/customer service, influence buyers' purchase decisions (Parasuraman 1981). To meet the needs of various departments, a professional buyer may exert more investigative effort in purchasing when users of a product are more involved in the purchasing process. Buyers who perceive a stronger influence from other departments therefore may be more likely to adopt the Internet, using it to gather product information and compare product features and prices.

To summarize, previous research combined with anecdotal evidence highlight three organizational variables likely to influence a buyer's propensity to use the Internet for industrial purchasing: supplier support of online purchase systems, perceived pressure to reduce costs of buying, and perceived influence of other departments. We expect that the more support provided by suppliers in terms of user education and price incentives to use online buying, the more a buyer feels pressure to reduce the costs associated with purchasing, and the more a buyer's decision is influenced by others in the organization, the more likely that buyer will intend to use the Internet for organizational purchase activities.

Market Conditions. The third class of variables investigated in RQ3 (Figure 1) relates to the market conditions the buying organization faces. Three variables are considered: market turbulence (i.e., the changing customer demands facing an industry), the competitive intensity of an industry, and technological turbulence (i.e., the degree to which an industry is experiencing rapid technological change) (Jaworski and Kohli 1993). The importance of these variables is established in theories of the knowledge and learning organization, which propose that information is a key resource in establishing and sustaining organizational competitiveness (Garvin 1993; Senge 1990). Organizations operating in more turbulent markets and experiencing rapid technological changes are more likely to enact product line modifications to satisfy changing customer preferences (Jaworski and Kohli 1993). For these organizations, satisfying changing preferences and remaining competitive will require rapid access to information and the ability to process orders quickly. Other research and theory in the area of organizational strategy suggest that higher levels of competitive intensity lead to greater resource allocations and more aggressive pricing policies, which in turn lead to more rapid diffusion (Brown 1981; Robertson and Gatignon 1986). Because the Internet facilitates rapid access to information, thereby compressing the purchasing cycle, and because a new technology may be adopted more rapidly under conditions of intense competition, we expect that a buyer's propensity to use the Internet for organizational purchasing activities will be influenced positively by market turbulence, technological turbulence, and competitive intensity.

Methodology

To investigate RQ1, RQ2, and RQ3, we collected both qualitative and quantitative data. To gather qualitative data we interviewed a convenience sample of organizational buyers. We gathered quantitative data using a mail-out survey to a national, random sample of purchasing professionals. The details regarding the qualitative investigation and the quantitative study are presented in the following sections.

Qualitative Investigation

To add richness to our understanding of Internet use in organizational purchasing activities, five professional buyers were interviewed. Each buyer held a position of either purchasing agent or purchasing director. The informants had worked in purchasing for six to 25 years. All of the respondents reported at least some Internet usage experience ranging from e-mail to information gathering to ordering, and all reported their experiences as positive. Respondents in our qualitative investigation represented a variety of industries, including electronics manufacturing, glass manufacturing, metalworking, food manufacturing, and education.

We used a semi-structured interview format for each of the interviews. Semi-structured depth interviews allow the researcher to develop a deeper understanding of the buyer's perspective through the respondent's own interpretations of his/her experiences. This method provides a powerful means for understanding an individual's view of the world and as well taps beliefs and daffy experiences (Fontana and Frey 1994; McCracken 1988).

Respondents were provided with a brief description of the research project. Respondents were then asked about their experiences with the Internet, the types of buying situations in which they were using e-commerce, and if and how their buying habits and relationships with suppliers had changed since they began using the Internet for corporate purchasing activities. Data collected through the depth interviews provided a rich background for exploring buyers' perceptions of the utility of the Internet in B2B purchasing activities. A list of uses and benefits relevant to these buyers was compiled.

Survey

A survey instrument was developed using both published scales and incorporating new items where necessary. Appendix A summarizes the items employed on the research instrument. Four measures were developed specifically for this study. These measures drew upon insight gained from the qualitative interviews and from related concepts in appropriate literatures. Specifically, we devised a three-item propensity to use the Internet measure, a two-item perceived pressure to reduce costs of buying measure, a three-item supplier support of online purchasing systems measure and a four-item measure for perceived communication convenience of the Internet (see Appendix A). As part of our development process, six professionals reviewed the items in these four measures before their inclusion in the survey. The professionals participating in this process included academic experts, purchasing agents, and a sales manager, each with knowledge and experience in the area of B2B online purchasing. Factor loadings and Cronbach's alpha reliabilities computed for each scale can be seen in the Appendix.

Questionnaires were mailed to a national random sample of 1000 members of the National Association of Purchasing Management. To encourage a favorable response, the initial mailing was followed by a reminder post card exactly one week later. Completed, usable surveys were received from 232 purchasing professionals (23% response rate). To assess nonresponse bias, data were divided into quartiles based on the timeliness with which questionnaires were returned to the authors. Analysis of variance was used to identify potential differences between quartiles. No evidence was found to suggest differences in the study variables relative to timeliness, nor did evidence suggest differences in the demographic profiles of respondents (Armstrong and Overton 1977).

Respondents were largely males (66.7%) between the ages of 40 and 49 (40.7%) with at least some college training (95.9%). Most respondents held the title of materials or purchasing manager (34.3%) or purchasing agent (26.1%) and worked for relatively large companies reporting revenues in excess of $100 million annually (55.1%). Years of purchasing experience ranged from one to 40, with an average of 14 years. Similar results were found for years at current employer, with a range from one to 39 and average of just under 10 years. Of the 232 purchasing professionals responding, 77.5% reported at least some experience in using the Internet for corporate-related purchasing activities.

Results

The findings are structured around our three research questions. Specifically, we examine the:

RQ1: Manner in which purchasing professionals are using the Internet (RQ1a) and the benefits that are important to them (RQ1b);

RQ2: Usefulness of demographic and organizational characteristics in predicting Internet use for corporate purchasing activities;

RQ3: Individual buyer, organizational, and market factors influencing buyers' propensity to use the Internet for industrial purchasing activities.

RQ1: B2B Internet Use and Benefits

To investigate how purchasing professionals are utilizing the Internet for corporate-related purchasing activities (RQ1a), respondents were asked to rate the frequency with which they use the Internet for the activities listed in Table 1. A principal components analysis supported the intuition-based classification of four categories of activities: information gathering activities, interorganizational information exchange activities, online ordering activities, and bidding and payment activities. Review of the mean values for each activity reveals e-mail is the most frequently used activity overall, followed by three activities related to information gathering: gathering product information, searching for new suppliers, and gathering external customer information. Online ordering activities occur with moderate frequency. Accessing supplier documents, gathering external customer information, online customer support, and electronic data interchange (EDI) are occurring with somewhat less frequency. Thus, it appears the Internet is regularly used for communication and for gathering new supplier and customer information. Additionally, at this point, it seems that the Internet is more useful as an information-gathering tool than as an online transactional tool.

To gain some insight regarding those buying situations for which the Internet is most useful, buyers currently using the Internet were asked to indicate the types of buying situations in which they are using the Internet: routine reorders, reorders with slight modifications, reorders with major modifications, simple new purchases, and complex new purchases. A relatively large percentage of respondents reporting online corporate purchasing activities occurring during simple new purchases (53.4%) and routine reorders (44.4%), thereby suggesting the Internet is used in less complex purchase situations. A much smaller percentage of the sample reported using the Internet during reorders with slight modifications (13.8%) and complex new purchases (12.9%), with only 4.7% using the Internet for reorders with major modifications.

Subsequently, we asked the buyers in our sample to rate the importance of certain Internet benefits to their job as a purchasing professional (RQ1b). Benefits were classified into one of four categories: ease of use, ease of comparing prices and products, ease of information exchange and access, and reduction of paper and time. As shown in Table 1, it appears that respondents believed Internet-based sources provided most of the a priori expected benefits. Thus, professional buyers perceive the Internet as facilitating access to information, providing a ready basis for comparison, and saving time in the purchasing process.

RQ2: Buyers' Characteristics and Organizational Structural Characteristics as Determinants of Buyers' Internet Usage

If demographic characteristics of the buyer or organizational characteristics related to the organization's structure are useful in predicting online usage behavior among organizational buyers, then sales organizations can more easily identify users and tailor their sales strategies accordingly. To explore the usefulness of these variables in distinguishing users from nonusers, a logistic regression model was evaluated. Logistic regression is a statistical technique that can be used to predict the presence or absence of an outcome, such as Internet usage, based on the values of a set of categorical predictor variables (Christensen 1997; Menard 1995). Four buyer demographic characteristics were proposed as predictors of Internet usage: education level, gender, age, and years of purchasing experience. Three structural characteristics related to the organization were investigated as predictors of Internet usage by buyers: number of employees, annual corporate sales revenue, and number of product categories bought by the buyer's department. Each of these variables was operationalized as a categorical measure. The dependent variable was dichotomous in nature, measuring whether the buyer was an Internet nonuser (`0') or user (`1'). This categorization was based on buyers' self-reports.

Table 2 summarizes findings of the logistic regression analysis. To determine how well the personal and organizational characteristics model fits the data, the model chi-square and [R.sup.2.sub.L] were evaluated. The model chi-square gives an indication of how well the model fits if all independent variables are included. A significant chi-square suggests the model accounts for usage behavior to some nonrandom extent. Alternatively, [R.sup.2.sub.L] provides an indication of how much inclusion of the independent variables reduces the badness of fit of the model, with larger values indicating better fit (Menard 1995). As shown in Table 2, the model chi-square of 30.17 (p = .035) suggests that information about the independent variables facilitates predictions of buyers' Internet use. The [R.sup.2.sub.L] value of .16 suggests some systematic association between the dependent and the set of independent variables.

Next, we examined how well the model classifies respondents into users and nonusers. The [[lambda].sub.p] statistic captures the proportion of cases correctly or incorrectly classified by the model; higher values of [[lambda].sub.p] indicate better predictive efficiency (Menard 1995). The model [[lambda].sub.p] value of .08 provides evidence that the demographic and structural characteristics are relatively inefficient in predicting Internet usage by buyers. Table 2 shows that although 95 percent of users were correctly classified, only 26 percent of nonusers were correctly classified (1).

Most appropriate to our purposes was an evaluation of the contribution of the independent variables in determining how the demographic and structural variables relate to Internet usage among organizational buyers. Given the low ability of the model to predict nonusage, most of the independent variables were not useful predictors, and our expectations were not supported. However, two variables do seem to be useful. Wald statistics reported in Table 2 suggest that years of purchasing experience (Wald = 10.23, p = .02) and gender (Wald = 7.35, p = .01) both are predictive of buyers' Internet usage. Calculating the probabilities of these significant individual variables yields interesting results (2). As expected, the probability that a user is male is relatively high: .92. Also as expected, the probability that a buyer uses the Internet for corporate purchasing activities increases with the years of experience (prob. = .75 for 1-6 and 7-12 years, prob. = .86 for 13-20 years).

RQ3: Determinants of Buyers' Propensity to Use the Internet

We used regression analysis to examine the influence of buyers' persona] perceptions of technology, the conditions within their organizations, and market conditions on Internet usage intent. As shown in Table 3, the expected relationships among the variables were partially supported. Five of the nine proposed variables appear to influence propensity to use the Internet among organizational buyers. With respect to personal perceptions of technology, the results indicate that the more organizational buyers perceive themselves as innovative and the more they perceive the Internet as a convenient tool, the more likely those buyers are to report positive intentions of using the Internet for corporate purchasing activities. Regarding organizational conditions, the results suggest that the more pressure buyers feel to lower costs, the more influence they perceive from other organizational members during purchase decisions, and the more support they perceive is being provided by suppliers, the more likely they are to report positive intentions of using the Internet for industrial purchasing activities. Interestingly, market condition factors did not have a significant influence on buyers' intent to use the Internet for industrial purchasing. Similarly, buyers' perceived skill as Internet users appears to have little impact on their willingness to purchase online.

Discussion

What role might the sales force play as business buyers adopt the Internet as a tool? In exploring this question, we took the perspective of the organizational buyer, assessing personal, organizational, and market characteristics that may help salespeople and sales managers understand the needs of their customers. We have investigated how organizational buyers use the Internet and what benefits they seek. As well, we analyzed the reported factors impacting buyers' Internet usage intent. In this section we will expand further the implications of our findings for the sales force.

Individual Buyer Characteristics

Consistent with findings from research on consumer use of the Internet, demographic variables have limited use in identifying and understanding Internet purchase behavior (Bellman, Lohse, and Johnson 1999). In examining individual characteristics of the buyer, we found limited support exists for gender and purchasing experience as distinguishing users from nonusers. Specifically, it appears that males and buyers with greater purchasing experience are somewhat more prone to want to use the Internet in professional purchasing activities. More importantly, buyers' perceptions of their own innovativeness and their perception of the Internet as a convenient communication and purchasing tool are more strongly related to buyers' propensity to use the Internet. As the direct link to customers, salespeople may need to explore these latter characteristics of their buyers and look beyond simple demographic variables.

Buyers who sought convenience through the Internet were more inclined to intend to use it. Other findings support the desire for convenience as a driver of Internet use. Respondents reported their primary use of the Internet revolved around e-mail communication, information gathering and supplier searches. Several buyers participating in our qualitative research noted how the ability to research vendors and products on the Web as well as the ability to send and receive e-mail with sales representatives have made the buying process more efficient and buyer-seller relationships more effective.

Thus, it appears at present that buyers view the Internet as an information gathering tool, supplementing rather than replacing the salesperson's efforts. As a consequence, salespeople might consider the importance of corresponding regularly with buyers via the Internet, sending substantive information and responding to buyers' requests quickly. A salesperson's expeditious response could pay dividends, as noted by an electronics equipment buyer we interviewed:

   I can now send off an e-mail or message to three or four suppliers on a
   particular part that you might be in trouble on or really need some
   attention and get immediate feedback and, you know, the quickest person on
   the keyboard sometimes wins the order.

Organizational Characteristics

Our findings suggest that of the variables we investigated, organizational characteristics have the most impact on Internet usage intent. Not surprisingly, the extent to which the buyer feels pressure to reduce costs is significant in their propensity to use the Internet for purchasing activities. This is consistent with the focus in the trade press on cost reductions as organizations move the purchasing function online. Although price pressures are a factor as buyers go online, the sales force must continue to offer valuable benefits to customers. For example, Web sites need to support the benefits respondents reported as most important: the ease of accessing and exchanging information, the ability of comparing prices and products, the reduction of order processing time and paper flow as well as the overall convenience of the Internet. Salespeople who understand and are prepared to help train and support their customers in their online purchasing efforts will be better positioned to gain the loyalty of these buyers. For example, one office furniture manufacturer uses the Internet to speed delivery and cut costs, but the salesperson still plays a critical role, using 3D software to help customers design their new offices. These salespeople help move customers beyond the price concern to the benefits of custom furniture--delivered on time (Rocks 2000).

Our results indicate that the more a buyer is influenced by other organizational members, the more likely that buyer intends to turn to the Internet in their purchasing activities. Sales managers will need to assure a broad range of easily accessed information is available on their Web site. With salespeople serving as a conduit and training resource for their customers, these buyers are more likely to become comfortable with the technology. Certainly, our findings corroborate the value of supplier support in terms of encouragement, guidance and incentives to use the Internet. With this support, buyers report increased propensity to use the Internet in purchasing activities. Well-trained, technologically-savvy sales-people may play a critical role in providing this guidance.

Buyers report using the Internet mainly for routine reorders and simple new purchases. Because electronic exchanges do not differentiate the product well, the sales force can still add value in more complex situations (Ansberry 2000). B2B companies that sell complicated products or services still need their salespeople to help buyers make an educated decision (Kaydo 1999; Rocks 2000). Also, if buyers are using the Internet for these simple reorders and can get their routine questions answered online or check the status of an order, a salesperson can focus on relationship development and customer care as well as have more time for prospecting and qualifying (Garner 1999; Kaydo 1999; Robinson 1999).

Implications for Future Research

This study serves as an initial effort to discern how industrial buyers view the Internet. Sales organizations would benefit from more detailed explorations of buyers' expectations, fears, and needs regarding the use of the Internet for online purchasing. It might be useful, for example, to compare buyers' expectations of online purchasing with those of salespeople, and to understand how buyers and sellers are preparing for electronic commerce. As the use of the Internet becomes more prevalent in B2B situations, researchers should reexamine organizational buying models to determine the nature of any changes that might occur.

Researchers might also consider variables not addressed in the present study. For example, B2B Internet use is expected to be more prevalent in certain industries, such as office and factory supplies, mechanical and electronic components, and medical/laboratory supplies (Blackmon 2000). Within these industries, an established infrastructure may facilitate more rapid adoption of this tool; future research might explore the influence of industry practices on industrial buyers' propensity to conduct purchasing activities online. As highlighted in the quote from a buyer in our qualitative study, the Internet can play a role in reducing time in the purchasing cycle. Hence, buyer's perceived need to reduce order cycle time might be an important organizational variable to investigate. And although our results did not reveal a relationship between perceived Internet skill and propensity to use the Internet, it seems plausible that a buyer's previous experience with conducting corporate purchasing activities online might influence Internet use. Researchers should consider these market, organizational, and buyer characteristics in future investigations.

Finally, the scales developed for this study also require further investigation. Although steps were taken to ascertain face validity in an industrial purchasing context, the items are ad hoc in the sense that they were not subjected to traditional scale validation activities recommended by Campbell and Fiske (1959). The Cronbach's alpha values for two of these scales, supplier support of online purchase systems and propensity to use the Internet, do exceed the alpha level of .70 established as acceptable in preliminary research (Nunnally and Bernstein 1994; Peterson 1994). A third scale, perceived communication convenience, approaches this level of acceptability (alpha = .69). The low alpha associated with perceived pressure to reduce costs of buying (alpha = .52) may reflect the number of items in the scale. Certainly, the study points toward the need to refine and reevaluate these scales.

Appendix
Measures

Variable/                                            Factor
Source of Measure      Items                        Loadings   [alpha]

Perceived              I like to continue doing
Innovativeness (a)       the same old things
--Novak and Hoffman      rather than trying new
(2000)                   and different
                         things. (R)                  .34        .80
                       I like to experience
                         novelty and change in my
                         daily routine.               .55
                       I like a job that offers
                         change, variety, and
                         travel, even if it
                         involves some danger.        .58
                       I am continually seeking
                         new ideas and
                         experiences.                 .62
                       I like continually
                         changing activities.         .70
                       When things get boring, I
                         like to find some new
                         and unfamiliar
                         experience.                  .75
                       I prefer a routine way of
                         life to an unpredictable
                         one full of change. (R)      .77

Perceived Internet     I am extremely skilled at
Skil (a)                 using the Internet.          .90        .90
--Novak, Hoffman,      I consider myself
Yung (2000)              knowledgeable about good
                         search techniques on the
                         Internet.                    .96
                       I know somewhat less about
                         using the Internet than
                         most users. (R)              .65
                       I know how to find what I
                         am looking for on the
                         Internet.                    .82

Perceived              With the Internet I will
Communication            be able to reduce the
Convenience (b)          time I spend with
--Newly developed        suppliers' salespeople.      .66        .69
                       Compared to traditional
                         communication sources,
                         I can get my questions
                         answered more
                         effectively using the
                         Internet.                    .67
                       With suppliers who have
                         online services, my job
                         as a purchasing
                         professional is easier.      .65
                       I prefer speaking directly
                         with my suppliers'
                         personnel to get help
                         and information. (R)         .42

Supplier Support of    Most of my suppliers
Online Purchasing        encourage me to use
Systems (b)              their Internet sites.        .64        .71
--Newly Developed      My suppliers provide
                         effective guidance in
                         the use of their
                         Internet sites.              .66
                       Many of my suppliers offer
                         incentives for using
                         their Internet sites.        .74

Perceived Pressure     I feel pressure to reduce
to Reduce Costs of       dramatically the price I
Buying (b)               pay for products in my
--Newly Developed        company.                     .58        .52
                       The primary reason I use
                         the Internet is to
                         reduce the price I pay
                         for goods and services.      .59

Perceived Influence    Indicate the extent to
of Other                 which your purchasing
Departments (c)          decisions, regarding the
--Parasuraman            choice of vendors and
(1981)                   products, are influenced
                         by recommendations by
                         others in your
                         organization:
                         production/operations
                           departments                .67        .66
                         marketing/sales/customer
                           service departments        .34
                         materials/parts/supplies
                           departments                .81
                         engineering/design
                           departments                .47
                         finance/accounting
                           departments                .42

Market Turbulence      In our kind of business,
(b)                      customers' product
--Jaworski and           preferences change quite
Kohli (1993)             a bit over time.             .69        .75
                       Our customers tend to look
                         for new products all the
                         time.                        .84
                       We are witnessing demand
                         for our products and
                         services from customers
                         who never bought them
                         before.                      .57
                       New customers tend to have
                         product-related needs
                         that are different from
                         those of our
                         existing customers.          .52
                       Sometimes our customers
                         are very
                         price-sensitive, but on
                         other occasions, price
                         is relatively
                         unimportant. (d)
                       We cater to many of the
                         same customers that we
                         used to in the past. (d)

Technological          The technology in our
Turbulence (b)           industry is changing
--Jaworski and           rapidly.                     .84        .90
Kohli (1993)           Technological changes
                         provide big
                         opportunities in our
                         industry.                    .88
                       A large number of new
                         product ideas have been
                         made possible through
                         technological
                         breakthroughs in our
                         industry.                    .84
                       Technological developments
                         in our industry are
                         relatively minor. (R)        .76
                       It would be difficult to
                         forecast where the
                         technology in our
                         industry will be in the
                         next 2 to 3 years. (d)

Competitive            Competition in our
Intensity (b)            industry is cut-throat.      .61        .79
--Jaworski and         There are many "promotion
Kohli (1993)             wars" in our industry.       .71
                       Anything that one
                         competitor can offer,
                         others can match
                         readily.                     .64
                       Price competition is the
                         hallmark of our
                         industry.                    .66
                       One hears of a new
                         competitive move almost
                         every day.                   .68
                       Our competitors are
                         relatively weak. (d)

Propensity to Use      I would like to be able to
the Internet (b)         use the Internet more in
--Newly developed        purchasing activities.       .64        .71
                       I am more likely to
                         repurchase from a
                         supplier that offers
                         online purchasing.           .67
                       I plan to use the Internet     .74
                         more in purchasing
                         activities within the
                         next year.

(a) Items scored on a five-point scale ranging from "completely false"
(1) to "completely true" (5).

(b) Items scored on a five-point scale ranging from "strongly disagree"
(1) to "strongly agree" (5).

(c) Items scored on a five-point scale ranging from "no extent" (1) to
"very large extent" (5).

(d) This item was eliminated, based on low inter-item correlations
achieved during standard scale refinement procedures.

(R) Reverse-scored items.
Figure 1
Research Questions and Variables of Interest

RQ1:                            RQ2:                  RQ3:

How are purchasing       Do personal          To what extent do
professionals using      characteristics or   various individual,
the Interact? (RQ1a)     organizational       organizational, or
What are the perceived   structural           market variables
key benefits of online   characteristics      influence propensity
buying activities?       predict buyers'      to use online
(RQ1b)                  Internet usage?      resources in
                                              purchasing?

                             Personal Characteristics of Buyer

B2B Internet             Demographics:        Perceptions of
Use and Benefits         * Age                Technology:
(Current)                * Gender             * Innovativeness
                         * Education          * Internet Skills
                         * Purchasing         * Comm. Convenience
                           Experience

                               Organizational Characteristics

                         Structural           Organizational
                         Demographics:        Influences:
                         * # Product          * Supplier Support of
                           Categories Bought    Online Purchasing
                         * Number of          * Pressure to Reduce
                           Employees            Costs
                         * Sales Revenue      * Influence of Other
                                                Departments

                                              Market Conditions

                                              * Market Turbulence
                                              * Competitive
                                                Intensity
                                              * Technological
                                                Turbulence

                         Outcome:             Outcome:
                         Internet Usage       Propensity to Use
                         (Current)            the Internet
                                              (Future)
Table 1
Internet Use Activities and Benefits Reported by Buyers

                                                 Std.
Internet Use Activities (RQ1a)        Mean (a)   Dev.

Information Gathering Activities:
 a1. Gathering product/component        3.28     1.03
     information
 a2. Searching for new suppliers        3.24      .97
 a3. Gathering information              2.94     1.09
     regarding current suppliers
 a4. Gathering competitive              2.56     1.26
     information for your company
 a5. Gathering external customer        2.32     1.23
     information for your company

Interorganizational Information
Exchange Activities:
 a6. E-mail                             3.96     1.11
 a7. Providing information to           2.61     1.13
     suppliers (specs, order
     policies, etc.)
 a8. Accessing supplier documents       2.37     1.25
     (blueprints, layouts, specs,
     etc.)
 a9. Electronic Data Interchange        2.21     1.26
a10. Discussion groups with other       1.55     1.02
     customers
a11. Just-in-time inventory             1.51     1.05
     planning

Online Ordering Activities:
a12. Online ordering                    2.47     1.20
a13. Online order status checks         2.45     1.17
a14. Online customer support            2.29     1.09

Bidding and Payment Activities:
a15. Online payments                    1.41      .80
a16. Conducting reverse auctions        1.18      .59

                                                 Std.
Internet Benefits (RQ1b)              Mean (b)   Dev.

Ease of Use:
 b1. Availability of current            4.44      .81
     information
 b2. Easy movement around               4.31      .85
     Internet sites
 b3. Easy online ordering               3.92     1.30
 b4. Ability to ask questions           3.78     1.12
     online

Ease of Comparing Prices and
Products:
 b5. Ability to obtain a lower          4.09      .97
     price for products purchased
 b6. Ability to compare prices          3.92     1.00
     from several suppliers easily
 b7. Ability to compare products        3.87     1.03
     from several suppliers easily
 b8. Ability to obtain information      3.71      .98
     that educates me on product
     uses

Ease of Information Exchange and
Access:
 b9. Increasing speed of                4.30      .79
     information from suppliers
b10. Increasing speed of                4.04      .93
     information to suppliers
b11. Ability to exchange                3.40     1.17
     information with colleagues
b12. Ability to customize content       3.22     1.17
     of supplier Internet sites

Reduction of Paper and Time:
b13. Reducing paper flow                4.34      .84
b14. Reducing order processing time     4.31      .86

                                      Correlation Matrix of Internet
                                              Use Activities
Internet Use Activities (RQ1a)           a1       a2     a3     a4

Information Gathering Activities:
 a1. Gathering product/component        1.0
     information
 a2. Searching for new suppliers        .58      1.0
 a3. Gathering information              .67      .47    1.0
     regarding current suppliers
 a4. Gathering competitive              .47      .39    .55    1.0
     information for your company
 a5. Gathering external customer        .42      .36    .51    .58
     information for your company

Interorganizational Information
Exchange Activities:
 a6. E-mail                             .29      .19    .27    .22
 a7. Providing information to           .25      .24    .29    .25
     suppliers (specs, order
     policies, etc.)
 a8. Accessing supplier documents       .45      .28    .33    .28
     (blueprints, layouts, specs,
     etc.)
 a9. Electronic Data Interchange        .07      .07    .10    .15
a10. Discussion groups with other       .27      .21    .35    .20
     customers
a11. Just-in-time inventory             .28      .18    .35    .28
     planning

Online Ordering Activities:
a12. Online ordering                    .34      .33    .32    .35
a13. Online order status checks         .33      .29    .31    .35
a14. Online customer support            .39      .33    .37    .27

Bidding and Payment Activities:
a15. Online payments                    .27      .20    .30    .43
a16. Conducting reverse auctions        .18      .20    .23    .29

                                      Correlation Matrix of Internet
                                                 Benefits
Internet Benefits (RQ1b)                 b1       b2     b3     b4

Ease of Use:
 b1. Availability of current            1.0
     information
 b2. Easy movement around               .62      1.0
     Internet sites
 b3. Easy online ordering               .42      .43    1.0
 b4. Ability to ask questions           .47      .48    .46    1.0
     online

Ease of Comparing Prices and
Products:
 b5. Ability to obtain a lower          .37      .30    .31    .31
     price for products purchased
 b6. Ability to compare prices          .33      .37    .19    .28
     from several suppliers easily
 b7. Ability to compare products        .37      .36    .18    .28
     from several suppliers easily
 b8. Ability to obtain information      .32      .35    .03    .30
     that educates me on product
     uses

Ease of Information Exchange and
Access:
 b9. Increasing speed of                .54      .46    .33    .43
     information from suppliers
b10. Increasing speed of                .35      .37    .24    .30
     information to suppliers
b11. Ability to exchange                .29      .27    .10    .30
     information with colleagues
b12. Ability to customize content       .42      .41    .37    .32
     of supplier Internet sites

Reduction of Paper and Time:
b13. Reducing paper flow                .34      .23    .28    .30
b14. Reducing order processing time     .41      .26    .43    .28

                                      Correlation Matrix of Internet
                                              Use Activities
Internet Use Activities (RQ1a)           a5       a6     a7     a8

Information Gathering Activities:
 a1. Gathering product/component
     information
 a2. Searching for new suppliers
 a3. Gathering information
     regarding current suppliers
 a4. Gathering competitive
     information for your company
 a5. Gathering external customer        1.0
     information for your company

Interorganizational Information
Exchange Activities:
 a6. E-mail                             .15      1.0
 a7. Providing information to           .42      .31    1.0
     suppliers (specs, order
     policies, etc.)
 a8. Accessing supplier documents       .47      .15    .53    1.0
     (blueprints, layouts, specs,
     etc.)
 a9. Electronic Data Interchange        .12      .17    .22    .23
a10. Discussion groups with other       .46      .30    .40    .42
     customers
a11. Just-in-time inventory             .38      .25    .36    .30
     planning

Online Ordering Activities:
a12. Online ordering                    .33      .24    .19    .26
a13. Online order status checks         .37      .14    .28    .35
a14. Online customer support            .37      .19    .37    .30

Bidding and Payment Activities:
a15. Online payments                    .37      .19    .18    .17
a16. Conducting reverse auctions        .34      .08    .34    .20

                                      Correlation Matrix of Internet
                                                 Benefits
Internet Benefits (RQ1b)                 b5       b6     b7     b8

Ease of Use:
 b1. Availability of current
     information
 b2. Easy movement around
     Internet sites
 b3. Easy online ordering
 b4. Ability to ask questions
     online

Ease of Comparing Prices and
Products:
 b5. Ability to obtain a lower          1.0
     price for products purchased
 b6. Ability to compare prices          .54      1.0
     from several suppliers easily
 b7. Ability to compare products        .50      .86    1.0
     from several suppliers easily
 b8. Ability to obtain information      .36      .45    .56    1.0
     that educates me on product
     uses

Ease of Information Exchange and
Access:
 b9. Increasing speed of                .33      .30    .30    .33
     information from suppliers
b10. Increasing speed of                .29      .27    .32    .30
     information to suppliers
b11. Ability to exchange                .27      .36    .43    .46
     information with colleagues
b12. Ability to customize content       .34      .36    .35    .37
     of supplier Internet sites

Reduction of Paper and Time:
b13. Reducing paper flow                .42      .32    .33    .24
b14. Reducing order processing time     .47      .42    .43    .23

                                      Correlation Matrix of Internet
                                              Use Activities
Internet Use Activities (RQ1a)           a9      a10    a11    a12

Information Gathering Activities:
 a1. Gathering product/component
     information
 a2. Searching for new suppliers
 a3. Gathering information
     regarding current suppliers
 a4. Gathering competitive
     information for your company
 a5. Gathering external customer
     information for your company

Interorganizational Information
Exchange Activities:
 a6. E-mail
 a7. Providing information to
     suppliers (specs, order
     policies, etc.)
 a8. Accessing supplier documents
     (blueprints, layouts, specs,
     etc.)
 a9. Electronic Data Interchange        1.0
a10. Discussion groups with other       .24      1.0
     customers
a11. Just-in-time inventory             .27      .62    1.0
     planning

Online Ordering Activities:
a12. Online ordering                    .19      .21    .36    1.0
a13. Online order status checks         .22      .26    .35    .64
a14. Online customer support            .26      .31    .35    .36

Bidding and Payment Activities:
a15. Online payments                    .25      .26    .31    .35
a16. Conducting reverse auctions        .06      .41    .28    .25

                                      Correlation Matrix of Internet
                                                 Benefits
Internet Benefits (RQ1b)                 b9      b10    b11    b12

Ease of Use:
 b1. Availability of current
     information
 b2. Easy movement around
     Internet sites
 b3. Easy online ordering
 b4. Ability to ask questions
     online

Ease of Comparing Prices and
Products:
 b5. Ability to obtain a lower
     price for products purchased
 b6. Ability to compare prices
     from several suppliers easily
 b7. Ability to compare products
     from several suppliers easily
 b8. Ability to obtain information
     that educates me on product
     uses

Ease of Information Exchange and
Access:
 b9. Increasing speed of                1.0
     information from suppliers
b10. Increasing speed of                .66      1.0
     information to suppliers
b11. Ability to exchange                .34      .43    1.0
     information with colleagues
b12. Ability to customize content       .40      .44    .38    1.0
     of supplier Internet sites

Reduction of Paper and Time:
b13. Reducing paper flow                .36      .34    .30    .35
b14. Reducing order processing time     .34      .25    .35    .40

                                      Correlation Matrix of Internet
                                              Use Activities
Internet Use Activities (RQ1a)          a13      a14    a15    a16

Information Gathering Activities:
 a1. Gathering product/component
     information
 a2. Searching for new suppliers
 a3. Gathering information
     regarding current suppliers
 a4. Gathering competitive
     information for your company
 a5. Gathering external customer
     information for your company

Interorganizational Information
Exchange Activities:
 a6. E-mail
 a7. Providing information to
     suppliers (specs, order
     policies, etc.)
 a8. Accessing supplier documents
     (blueprints, layouts, specs,
     etc.)
 a9. Electronic Data Interchange
a10. Discussion groups with other
     customers
a11. Just-in-time inventory
     planning

Online Ordering Activities:
a12. Online ordering
a13. Online order status checks         1.0
a14. Online customer support            .40      1.0

Bidding and Payment Activities:
a15. Online payments                    .33      .22    1.0
a16. Conducting reverse auctions        .22      .16    .43    1.0

                                      Correlation Matrix of Internet
                                                 Benefits
Internet Benefits (RQ1b)                b13      b14

Ease of Use:
 b1. Availability of current
     information
 b2. Easy movement around
     Internet sites
 b3. Easy online ordering
 b4. Ability to ask questions
     online

Ease of Comparing Prices and
Products:
 b5. Ability to obtain a lower
     price for products purchased
 b6. Ability to compare prices
     from several suppliers easily
 b7. Ability to compare products
     from several suppliers easily
 b8. Ability to obtain information
     that educates me on product
     uses

Ease of Information Exchange and
Access:
 b9. Increasing speed of
     information from suppliers
b10. Increasing speed of
     information to suppliers
b11. Ability to exchange
     information with colleagues
b12. Ability to customize content
     of supplier Internet sites

Reduction of Paper and Time:
b13. Reducing paper flow                1.0
b14. Reducing order processing time     .74      1.0

(a) Activities were rated on a five-point scale ranging from "never"
(1) to "always" (5).

(b) Benefits were rated on a five-point scale ranging from "not
important" (1) to "very important" (5).
Table 2
Logistic Regression Results: Exploring Determinants of Buyers'
Internet Usage

Wald's Measure of Significance of the Independent Variables

Personal                    B               Wald         df    p [less
Demographics                                                   than or
                                                              equal to]

Years of Purchasing
  Experience:                              10.23         3       .02
        1-6                1.57             4.17         1       .04
        7-12               1.65             4.71         1       .03
        13-20              2.40            10.07         1       .00
        20+                                              0
Age of Buyer:                               1.72         3       .63
        20-29              -.86              .73         1       .39
        30-39               .02              .00         1       .98
        40-49              -.47              .65         1       .42
        50+                                              0
Education:                                   .73         3       .87
        high school
          graduate         -.20              .04         1       .84
        some college        .47              .49         1       .49
        college
          degree            .09              .03         1       .86
        college
          graduate                                       0
Gender: Male               1.41             7.35         1       .01
        Female                                           0
Structural
  Demographics
Number of Employees:                        5.15         2       .08
        less than
        100                -.94             1.93         1       .16
        100-499           -1.40             5.14         1       .02
        500+                                             0
Annual Sales Revenue                        1.58         4       .81
        < $5 million        .94              .77         1       .38
        > $5-$25
          million          -.08              .01         1       .92
        > $25-$200
          million           .44              .42         1       .52
        > $100-$500
          million           .15              .05         1       .82
        > $500
          million                                        0
No. of Product
  Categories Bought                         1.03         2       .60
        < 25                .27              .17         1       .68
        25-99               .47             1.02         1       .31
        100+                                             0
Constant                    .59              .48         1       .48

Goodness-of-Fit
Measures
Model Chi-Square       Significance   [R.sup.2.sub.L=]
= 30.17                   = .035            * 16

Measures of
Predictive
Efficiency             [[lambda].sub.p] = .08

Classification Table:                      Predicted

                          Observed    0           1          Percent
                                                             Correct

                        Nonuser: 0   10          29           25.64%

                           User: 1    7         127           94.78%

                                          Overall Percent:    79.19%
Table 3
Variables Influencing Buyers' Propensity to Use the Internet

Global Test of Model Fit: F= 15.04, p=.O00, Adjusted [R.sup.2] = .39

Category of Variables       Variable                     Standardized
                                                             Beta

Personal Perceptions        Perceived Innovativeness          .16
of Technology               Perceived Internet Skill          .04
                            Perceived Communication
                            Convenience                       .42

Organizational Influences   Supplier Support of Online
on Use of the Internet by   Purchasing Systems                .12
Industrial Buyers           Perceived Pressure to
                            Reduce Costs of Buying            .15
                            Perceived Influence of
                            Other Departments                 .15

Market Conditions           Market Turbulence                -.11
                            Technological Turbulence          .09
                            Competitive Intensity            -.01

Category of Variables       Variable                          t

Personal Perceptions        Perceived Innovativeness         2.57
of Technology               Perceived Internet Skill          .62
                            Perceived Communication
                            Convenience                      6.51

Organizational Influences   Supplier Support of Online
on Use of the Internet by   Purchasing Systems               2.02
Industrial Buyers           Perceived Pressure to
                            Reduce Costs of Buying           2.42
                            Perceived Influence of
                            Other Departments                2.58

Market Conditions           Market Turbulence               -1.85
                            Technological Turbulence         1.45
                            Competitive Intensity            -.22

Category of Variables       Variable                     p [less than
                                                         or equal to]

Personal Perceptions        Perceived Innovativeness          .01
of Technology               Perceived Internet Skill          .54
                            Perceived Communication
                            Convenience                       .00

Organizational Influences   Supplier Support of Online
on Use of the Internet by   Purchasing Systems                .04
Industrial Buyers           Perceived Pressure to
                            Reduce Costs of Buying            .02
                            Perceived Influence of
                            Other Departments                 .01

Market Conditions           Market Turbulence                 .07
                            Technological Turbulence          .15
                            Competitive Intensity             .83

Appendix A summarizes measure items.

Endnotes

(1) In previous studies, researchers in marketing have reported correct classification percentages ranging from 65% to 92.95% (e.g., Domke-Damonte 2000; Erramilli and D Souza 1995; Samiee and Anckar 1998; Sonmez and Graefe 1998).

(2) Probabilities were calculated by converting logits. For example, the probability that a user was male was calculated by multiplying the beta coefficient for gender (1.41) by the value for males (1) and subtracting the constant (-.59) to obtain the logit value [logit(USER) = 1.41 (1) -.59 = 2.3898]. The logit was then translated into a probability [[e.sup.2.3898]/(1 + [e.sup.2.3898]) = .92] (Menard 1995). The constant and beta coefficients can be found in Table 2.

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Karen Norman Kennedy (Ph.D., University of South Florida) is Assistant Professor of Marketing at University of Alabama at Birmingham. Her research interests include customer orientation, organizational change, e-commerce, sales, and measurement issues. She has published in Industrial Marketing Management, Journal of Marketing Education, Psychological Reports, Journal of Social Behaviour and Personality, and various conference proceedings.

Dawn R. Deeter-Schmelz (Ph.D., University of South Florida) is Assistant Professor of Marketing at Ohio University. Her research interests include customer service teams, sales and industrial marketing, e-commerce, and measurement issues. She has published in the Journal of Personal Selling & Sales Management, Industrial Marketing Management, Journal of Marketing Theory and Practice, Journal of Marketing Education, and Journal of Business Logistics, among others.

We would like to thank the editor, Jeff Sager, and the anonymous JPSSM reviewers for their helpful comments. We also gratefully acknowledge the contribution of Donald A. McBane for reading an earlier version of this manuscript.