The document examines how the behaviors of strategic account managers impact relationship outcomes like customer trust, role performance, and synergistic solutions. It proposes and tests a model showing that customer orientation positively impacts role performance and synergistic solutions, increasing customer trust, while selling orientation negatively impacts synergistic solutions and trust. Team selling is found to positively impact synergistic solutions and trust.

1. The impact of strategic account managers' behaviors on relational outcomes: An
empirical study
Paolo Guenzi a,
⁎, Laurent Georges b
, Catherine Pardo c
a
Department of Management – Institute of Marketing, Bocconi University and SDA Bocconi School of Management, Via Bocconi, 8, 20136 Milano, Italy
b
IUT-Tarbes, University Paul Sabatier Toulouse III, LCG Research Center, EA 2043, Toulouse, France
c
OCE – EM-Lyon, 23, Avenue Guy de Collongue BP 174, Lyon Ecully Cedex, France
a r t i c l e i n f o a b s t r a c t
Article history:
Received 10 August 2006
Received in revised form 17 July 2007
Accepted 17 September 2007
Available online 2 April 2008
This paper explores the impact of some behaviors of strategic account managers on the relational outcomes of
the relationships they are in charge of. Based on a review of literature on personal selling and strategic account
management, we contribute to a greater understanding of the role of specific strategic account managers'
behaviors in fostering synergistic solutions, role performance and customer trust. Results of the empirical
study clearly show that the use of customer orientation has a strong influence on customer trust by increasing
strategic account managers' role performance and stimulating synergistic solutions. Conversely, a selling
orientation negatively affects synergistic solutions, thus decreasing customer trust. Finally, team selling has a
positive impact on the attainment of synergistic solutions, thereby fostering customer trust. Based on these
findings, managerial and research implications are discussed.
© 2008 Elsevier Inc. All rights reserved.
Keywords:
Relational behaviors
Strategic account managers
Customer trust
Synergistic solutions
Team selling
PLS
1. Introduction
Strategic account management has recently been highlighted as a
major area of academic research (Leigh & Marshall, 2001; Workman,
Homburg & Jensen, 2003). Managers and academics alike increasingly
recognize that suppliers need to develop long-lasting relationships
with selected, high stake customers (Beverland, 2001; Homburg,
Workman & Jensen, 2002; Workman et al., 2003).
Despite this widespread interest in strategic account management
in general, individual-level behaviors that should be adopted by those
who are in charge of managing relationships with strategic accounts
remain an under-developed topic in academic research.
As pointed out by Sengupta, Krapfel and Pusateri (2000), many
different terms have been used to label these selected clients: large
accounts (Miller, Heiman & Tuleja, 1991), major accounts (Colletti &
Tubridy, 1987), national accounts (Shapiro & Moriarty, 1984), key
accounts (Pardo, 1997; Homburg et al., 2002; Workman et al., 2003)
and strategic accounts (Napolitano, 1997). In our study we use the
terms “strategic accounts” and “key accounts” interchangeably, to
encompass all terms suggested to describe those customers who, for
different reasons (e.g. their current and future quantity of purchases,
their lead user function, their reputation, etc.), are considered worthy
of special attention and treatment on the part of the selling company
(Walter, Ritter & Gemünden, 2001).
Similarly, we use the term “strategic account manager” or “keyaccount
manager” interchangeably, to refer to the person who is in charge of
managing the relationships with these strategic accounts. In previous
research, this position has been given different labels, such as key account
salesperson (Sengupta et al., 2000), key account representative (Schultz &
Evans 2002), or simply salesperson (Boles, Barksdale & Johnson, 1996).
Whatever the label used, there is a widespread recognition of the fact that
these individuals contribute greatly to the implementation of a relational
approach to strategic customers (Iacobucci & Ostrom, 1996; Mavondo &
Rodrigo, 2001; Weitz & Bradford, 1999).
Nevertheless, the majority of contributions to date have investigated
company-level relational behaviors (e.g. Leuthesser, 1997) and drivers of
key account relationships (e.g. Sengupta, Krapfel & Pusateri, 1997). Only a
few exceptions have made empirical analysis of the individual-level
behaviors that should be adopted by those who are in charge of managing
relationships with strategic accounts. Platzer (1984), and Wotruba and
Castleberry (1993), identified the most widespread and relevant activities
performed by strategic account managers. Boles, Barksdale and Johnson
(1996) listed eight classes of behavior, requested by decision-makers in
large accounts. Sengupta et al. (2000) studied the determinants of key
account salesperson effectiveness. More recently, Schultz and Evans
(2002) developed and tested a model of collaborative communication by
key account representatives.
To sum up, the existing literature provides a first set of rich and
interesting contributions but it has only scratched the surface of what
affects strategic account managers' outcomes. Much more needs to be
investigated if we want to fully understand how to manage a strategic
accounts sales force. In other words, just like a lot of attention has been
Industrial Marketing Management 38 (2009) 300–311
⁎ Corresponding author. Tel.: +39 02 58366820; fax: +39 02 58366893.
E-mail addresses: paolo.guenzi@sdabocconi.it (P. Guenzi),
Laurent.georges@iut-tarbes.fr (L. Georges), pardo@em-lyon.com (C. Pardo).
0019-8501/$ – see front matter © 2008 Elsevier Inc. All rights reserved.
doi:10.1016/j.indmarman.2007.09.011
Contents lists available at ScienceDirect
Industrial Marketing Management

2. focused on the individual-level determinants of salesperson performance,
we argue that a similar effort should be placed on the antecedents of
strategic account managers' outcomes.
In light of these considerations, the purpose of this paper is to present
and test a model of strategic account managers' contribution to fostering
customer trust. This model integrates previous research on strategic
account management and builds on the framework developed by Schultz
and Evans (2002) by incorporating individual-level behaviors and relating
them to outcome constructs which lead to customer trust. We decided to
start from this framework because it has a lotof merit fordifferent reasons.
First, as stated beforehand, it is one of the very few articles investigating
individual-level behaviors of strategic account managers. Second, it is
based on a well accepted relationship between an individual's behaviors
and his/her performance (Plank & Reid,1994; Biong & Selnes,1996). Third,
it incorporates a broad set of relational outcomes – synergistic solutions,
role performance and trust in strategic account representative – that
capture different facets of buyer–seller relational exchanges and can
reasonably result in sales and favor the development of long term
relationships.
Despite its relevant contribution, Schultz and Evans' study has
several limitations.
First, it only investigates a limited set of drivers of relational outcomes
in key account management, i.e. communication aspects (informality, bi-
directionality, frequency and strategic content). Obviously, many other
potentially relevant drivers deserve investigation. Our research examines
a completely different set of key account manager behaviors – customer
orientation, selling orientation and team selling – thus expanding existing
knowledge and integrating recent research in key account management
and salesperson's performance. Importantly, as we will explain later on,
these behaviors cover both the “individual” and the “collective” dimen-
sions of a key account manager's job.
Second, the original model assumes that the three relational
outcomes are at the same level. In contrast, based on the literature on
relationship marketing and relationship selling, we posit that
synergistic solutions and role performance act as mediating variables
between individual behaviors and customer trust, therefore testing a
causal order between relational outcomes.
A third limitation of Schultz and Evans' study is that a key construct
(trust) is measured by two items only that do not include the buyer's
evaluation of the vendor's benevolence. Hence, we used a four item
measure incorporating this relevant component, too.
A fourth limitation of the study is that the model was tested in one
company only. Our study focuses on key account relationships in
many different business-to-business industries.
The goal of our study is to address these limitations to increase
existing knowledge on key account management.
This paper is divided into four sections. The first part presents the
model, clarifies the different constructs examined, and develops a set
of hypotheses linking strategic account managers' behaviors to
relational outcomes. Next, we explain the method used to test the
model. The third section presents the results of the analysis. Finally,
we discuss theoretical and managerial implications, outline limita-
tions of the study and highlight future research opportunities.
2. Conceptual model, constructs and hypotheses
Fig. 1 shows the conceptual framework that is proposed and tested in
the study. It represents an attempt to identify structural characteristics of
customer trust towards the strategic account manager in a business to
business selling context and focuses on the point of view of the vendors.
Collecting data from this perspective was thought to be crucial as strategic
account managers are often in charge of relationships and set directions
for their own behaviors. As underlined by Schultz and Evans (2002),
strategic account managers' interpretations of their actual behaviors and
outcomes will determine possible changes in their sales strategies as
surveys of customers are not always available.
Specifically, the model posits strategic account manager behaviors
(customer orientation, selling orientation and team selling) as
antecedents to role performance and synergistic solutions. Trust in
the strategic account manager represents the final outcome of role
performance and synergistic solutions.
As stated beforehand, the model builds on the framework
developed by Schultz and Evans (2002). However, it incorporates 1)
a different set of relational behaviors as well as 2) a sequential path in
the outcome variables.
1) Whereas, Schultz and Evans (2002) focused on collaborative
communication, our model offers a different set of behaviors,
drawn from literature on relationship selling and key account
management. We focus our attention on three behaviors: customer
orientation, selling orientation and team selling. The first two
represent both dimensions of the Selling Orientation-Customer
Fig. 1. A conceptual framework of strategic account managers' contribution to customer trust.
301
P. Guenzi et al. / Industrial Marketing Management 38 (2009) 300–311

3. Orientation construct, initially developed by Saxe and Weitz (1982).
A number of empirical studies investigated sales-oriented and
customer-oriented behaviors, but we found no research that
explicitly examine how both dimensions of the SOCO scale affect
strategic account manager's performance. In fact, the existing
literature on strategic account management pays little attention to
the impact of these two constructs on the strategic account
manager's outcomes. In addition to this, given the emphasis placed
in the literature (e.g. Wotruba & Castleberry, 1993; Sengupta et al.,
2000) on the coordination role and integration tasks performed by
the strategic account manager, it is also important to understand
how this dimension might influence his/her outcomes. Therefore,
whereas, Schultz and Evans (2002) study focused on the individual-
level determinants of strategic account manager performance, we
also took into consideration – through the inclusion of the team
selling construct – the collective or organizational dimension of his/
her work. If customer orientation and selling orientation reflect the
strategic account manager's individual behaviors towards the
customer, team selling, by contrast, expresses the collective
dimension of the strategic account manager's position as it
represents his/her efforts to marshal and coordinate resources
from different people and departments in his/her organization.
2) As statedbySchultz and Evans(2002,pp. 29–30), oneof the limitations
of their work was that their model did not test causal relationships
between outcome constructs. Therefore, in order to enrich their
framework, we posit role performance and synergistic solutions as
antecedents of strategic account manager trust. From a theoretical
standpoint, this choice is based on literature on relationship marketing
and relationship selling. In fact, trust is probably the most important
outcome construct in relational literature, especially because it is the
building block for relationship commitment and has a long term
nature (e.g. Morgan & Hunt, 1994; Doney & Cannon, 1997; Weitz &
Bradford, 1999). For example, Berry (1996, p. 42) states that “trust [is]
perhaps thesinglemost powerful relationship marketingtool available
to a company” and, as highlighted by Gundlach and Murphy (1993, p.
41), “the variable most universally accepted as a basis of any human
interactionorexchangeistrust”.Similarly,trustisakeyconstructinthe
literature investigating relationship selling (e.g. Jolson, 1997; Wilson,
2000). In our context of analysis, customer trust develops thankstothe
capacity of the strategic account manager to cooperate with the buyer
(s) to accomplish joint solutions (i.e. synergistic solutions) and to fulfill
the different facets of his/her role (i.e. role performance). Moreover,
based on relational literature, relationship selling performance should
include both present and future indicators of the customer's relation-
ship with the salesperson. In this perspective, role performance and
synergistic solutions represent measures of present results reached
either individually or jointly. In other words, they assess the current
state of the strategic account manager's performance. Conversely,
customer trust provides a crucial insight into the future stability and
potential growth of the relationship. In fact, as highlighted by Swan,
Bowers and Richardson (1999), the concept of trust includes
expectations about the future and expresses the customer's will-
ingness to accept the risk of undesirable outcomes if the salesperson
lacks the ability or motivation to keep his/her promises.
The following paragraphs examine the conceptualization of each
construct in our model and develop hypotheses.
2.1. Strategic account managers' relational behaviors
The exogenous variables in the model can be defined as selling
behaviors or, as suggested by Crosby, Evans and Cowles (1990), as
behavioral tendencies exhibited by representatives of vendors affecting
their behavioral performance. One aspect of the strategic account
manager position is to act individually to manage the relationship with
the accounts. According to the literature, in dealing with customers, he
or she may adopt two distinct sets of behaviors referred as customer
and selling orientations (Saxe & Weitz,1982). However, it has also been
noted by manyauthors (Wotruba & Castleberry,1993; Weitz & Bradford,
1999) that the strategic account manager position is characterized by a
second aspect, reflecting the role of a coordinator of a sales team. Teams
are used because in a strategic account setting, the selling process
usually goes beyond the capabilities of any one individual (Workman
et al., 2003). As a result, strategic account managers are also in charge of
managing the activities of teams rather than simply managing their
ownpersonal activities (Weitz & Bradford,1999). We therefore included
in our study a third class of behaviors called team selling.
2.1.1. Customer orientation–selling orientation
Customer oriented selling can be interpreted as the implementation of
the marketing concept at the level of the individual salesperson. As such,
this selling approach is consistent with the building of long-lasting posi-
tive relationships between the buyer and the seller. Therefore, it is widely
recognized as an important class of relational selling behaviors (Flaherty,
Dahlstrom & Skinner, 1999; Keillor, Parker & Pettijohn, 2000; Martin &
Bush, 2003;Schultz &Good,2000),butquitesurprisinglyit hasnever been
investigatedina typicalrelationalcontextlikekeyaccountmanagement.It
is noteworthy that the SOCO scale incorporates two sub-scales, i.e. selling
orientation and customer orientation: although strongly (and negatively)
interrelated, these two factors have rarely been investigated separately. In
this study, we will develop and test opposing hypotheses for the two sub-
scales.Importantly,althoughSOCO has beenconceptualized inmany ways
(e.g. as an attitude, a measure of performance, etc.), it is best viewed as a
set of behaviors (Schwepker, 2003).
2.1.2. Team selling
Teamsellingimpliesthatmultiplecontactsareestablishedbetweenthe
supplier and the buyer (Cron & DeCarlo, 2006). It is important to underline
that such contacts usuallytake place and need tobe coordinated effectively
and efficiently even when formal sales teams do not exist in the selling
firm. In this study, this construct includes the strategic account manager's
ability to identify experts within his/her organization and deploy them to
help the customer. Although similar to the idea of entrepreneurial ability
offered by Sengupta et al. (2000), our conceptualization goes further and
incorporates the efforts made by the strategic account manager to
coordinate the resources mobilized. Team selling is usually adopted in
complex buyer–seller situations, where the customer requires special
treatment and the potential sale is large, i.e. typical conditions of
relationships with strategic and keyaccounts (Jackson, Widmier, Giacobbe,
&Keith,1999). As themembers of thesales teamusuallybelongtodifferent
departments, the necessity of a strong coordination needs to be
emphasized (Honeycutt, 1996). Therefore, strategic account managers are
typically described as captains or leaders of teams who are in charge of
selecting technicians and other specialists who then meet with specialists
on the buying side (Georges & Eggert, 2003).
2.2. Strategic account managers' relational outcomes
Consistently with the goal to extend the previous work by Schultz
and Evans (2002), our study explores three relational outcomes (role
performance, synergistic solutions and trust in the strategic account
manager) of long term buyer–seller interactions. Role performance
and synergistic solutions can be classified as pertaining to the
individual's effectiveness (i.e. role performance), on the one hand,
and the combined effort of the two parties (i.e. synergistic solutions),
on the other. As pointed out beforehand, trust in the strategic account
manager (i.e. a critical aspect of relationship success) is interpreted as
the final relational outcome variable.
2.2.1. Role performance
This construct describes the strategic account manager's individual
effectiveness in developing plans and providing expertise to the customer
302 P. Guenzi et al. / Industrial Marketing Management 38 (2009) 300–311

4. (Frazier & Rody, 1991). It represents the extent to which he/she perceives
that the relationship has been effective in achieving performance
objectives. In this way, role performance synthesizes his/her individual
effectiveness in solving the customer's problems, developing strategic
plans, and enhancing outcomes (Schultz & Evans, 2002, p. 25).
2.2.2. Synergistic solutions
In contrast with role performance, which covers the individual
performance of the strategic account manager, this construct
represents the combined effort of the two parties to be innovative
and accomplish joint solutions that could not be obtained by either
individual in the absence of the partner (Jap & Weitz, 1994; Schultz &
Evans, 2002). Implementing a relational strategy requires interactive,
two-way exchange processes between the seller and the buyer, aimed
especially at developing interdependence and co-production of value
(Möller & Wilson, 1995). Similarly, Wilson (1995) points out that
maintaining the buyer–seller relationship over time relies on mutual
goals and joint action, while Ganesan (1994) underlines that at the
heart of relational exchanges there are joint synergies resulting from
exploiting idiosyncratic assets and risk sharing.
2.2.3. Trust in the strategic account manager
In the present research, we define trust as the customer's belief that
the strategic account manager can be expected to show reliability and
integrity (Morgan & Hunt, 1994) and forbearance from opportunism
(Smith & Barclay,1997) in future interactions. Our conceptualization is
limited to the customer's trust in a person and does not take into
consideration trust in the selling organization. Adopting a long-term
perspective emphasizes the vital importance of trust, a construct
which synthesizes and represents both the output of past relations and
the input for future ones (Anderson & Narus, 1990; Morgan & Hunt,
1994). In short, trust is a focal construct in the analysis of relational
strategies (Ganesan, 1994; Doney & Cannon, 1997; Blois, 1999).
2.3. Hypotheses
It is generally recognized that customer orientation increases
performance (Saxe & Weitz, 1982; Swenson & Herche, 1994; Keillor
et al., 2000; Boles, Babin, Brashear, & Brooks, 2001; Brown, Mowen,
Donavan, & Licata, 2002) and effectiveness (Baldauf & Cravens, 1999).
However, to our knowledge, empirical research on this topic to date
has not investigated the impact of customer orientation on the specific
outcomes we take into account in this research. We argue that there
is a large body of evidence which links customer orientation to
relational-like outcomes. Humphreys and Williams (1996) and Goff,
Boles, Bellenger & Stojack (1997) have demonstrated that customer
orientation generates higher levels of customer satisfaction with the
salesperson, thus increasing his/her role performance. Jones, Busch
and Dacin (2003) showed that customer orientation reduces a
customer's propensity to switch to other suppliers. Boles, Barksdale
and Johnson (1996), Beverland (2001) and Liu and Leach (2001) found
that a salesperson's relational behaviors which are oriented toward
the customer improve the customer's perception of the quality of the
buyer–seller relationship. To sum up, we can conclude that customer
orientation increases the selling company's relational outcomes by
improving the quality of the customer's interpersonal relationship
with the sales force (Langerak, 2001). As customer orientation reflects
non-opportunistic behavior which stresses customer-focused solu-
tions and mutual benefits (Schwepker, 2003), we argue that it should
positively affect both the strategic account manager's role perfor-
mance and provision of synergistic solutions, thereby ultimately
increasing customer trust. Building on the above-cited theoretical and
empirical foundations, we hypothesize that:
H1. The strategic account manager's customer orientation is posi-
tively related to his/her role performance.
H2. The strategic account manager's customer orientation is posi-
tively related to his/her provision of synergistic solutions.
Interestingly, it has been pointed out that the SOCO scale consists of
two distinct, though related, subscales (Thomas, Soutar and Ryan, 2001).
Nevertheless, very few studies have examined simultaneously the impact
of customer orientation on the one hand, and the impact of selling
orientation on the other, on selected outcome variables. Among these
studies, Goff et al. (1997) posits and partially supports the existence of
opposing consequences of customer orientation and selling orientation on
customer satisfaction. Tam and Wong (2001) demonstrates that customer
orientation has a positive effect on both customer satisfaction and
customer trust, while selling orientation has a negative impact on both
outputs. Thus, we hypothesize that a selling orientation, compared to a
customerorientation,willhaveanopposite(i.e. negative)effectonthetwo
relational outcomes taken into account in this study:
H3. The strategic account manager's selling orientation is negatively
related to his/her role performance.
H4. The strategic account manager's selling orientation is negatively
related to his/her provision of synergistic solutions.
Cross-functional selling teams are necessary in strategic account
management since an individual salesperson does not possess the
knowledge or intrafirm influence to propose and implement a
program that has the potential for building a competitive advantage
for the seller–buyer dyad (Weitz & Bradford, 1999). This statement
clearly underlines the fact that synergistic solutions (i.e. a win–win
outcome for both members of the dyad) often result from team selling.
Based on this background we hypothesize:
H5. The strategic account manager's adoption of team selling is
positively related to synergistic solutions.
The management of a business relationship with a customer
encompasses a multiplicity of different tasks which require a wide
range of knowledge, skills, and abilities. Therefore, the ability of the
individual strategic account manager to be the selling team coordi-
nator and to work closely with colleagues from other departments is
widely recognized as a fundamental driver of his/her individual
performance (e.g. Millman, 1996; Weilbaker & Weeks, 1997; Wilson &
Millman, 2003). Hence we hypothesize that:
H6. The strategic account manager's adoption of team selling is
positively related to his/her role performance.
Although there is no general consensus on the causal ordering of
relational constructs, we argue that customer trust in the salesperson
is one of the ultimate goals of the relationship-building process, as it
leads to commitment (Morgan & Hunt, 1994). Therefore, in our
conceptualization, synergistic solutions and role performance are
most appropriately posited as predictors of trust. They stem from past
behaviors and refer to the customer's evaluation of his/her relation-
ship with the strategic account manager to date. By contrast, trust
reflects the customer's expectations about future behaviors. Finally,
customers will be more inclined to trust account managers who are
effective in terms of performance and develop synergistic solutions.
Based on this rationale, we hypothesize that:
H7. The strategic account manager's provision of synergistic solutions
is positively related to customer trust.
H8. The strategic account manager's role performance is positively
related to customer trust.
3. Method of the study
3.1. Data collection, questionnaire development and sample
Although it could be argued that the best informants for the model
tested in the study would be buyer–seller dyads, in light of the obvious
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P. Guenzi et al. / Industrial Marketing Management 38 (2009) 300–311

5. selection problems to obtain participation from dyads of respondents, the
survey respondents were all strategic account managers. A similar
approach was also adopted in recent studies on strategic account
management (see Sengupta et al., 2000; Schultz & Evans, 2002). In fact,
strategic account managers base their decisions and actions upon their
personal evaluations but also on their perceptions of the evaluations of
third parties (sales manager or customer). In keeping with Expectancy
Theory, strategic account managers will spend more effort on those
behaviors which, in their belief, lead to greater performance which, in
turn, should drive to greater rewards. In strategic account management,
performance is usually best interpreted in terms of relationship building.
Hence, both managers and academics need to understand what are the
strategic account managers’ beliefs and perceptions concerning the
linkages between behaviors and relational outcomes. This is why using
strategic account managers as respondents should be appreciated from
both a theoretical and a managerial perspective.
Strategic account managers were asked how often they perform
customer-oriented, selling-oriented and team selling behaviors. In
addition, for the different outcomes included in our model (i.e. role
performance, synergistic solutions and trust), we asked their percep-
tions about the evaluations of the strategic account.
Using self-reporting measures has some limitations. However
Spector (2006, p.225), based on the findings of many empirical
studies, claims that “evidence fails to support social desirability as a
general source of correlation inflating CMV when self-reports are
used”. In addition to this, Schultz and Evans (2002) argued that it is
appropriate to use the key account managers' self-report performance
assessment as a “proxy” interpretation of the key accounts' view
because in such close, long-term relationships the understanding
parties have of each other transcends the typical information available
in contexts characterized by single transactions (see Ickes, 1993).
Additionally, Schultz and Evans suggested that using self-reporting
measures is appropriate especially when (like in our case) this self-
assessment does not refer to objective criteria (e.g. quota, sales
volume, etc.), but rather to qualitative dimensions (e.g. trust). Finally,
it is important to underline that Schultz and Evans (2002, p.26) also
surveyed 40 key accounts in their study and found that “the customer
survey yielded virtually identical relationship results to those of the
vendor data”. Based on these arguments, we also conclude, just like
Schultz and Evans, that the use of key account managers to measure
the quality of the customer relationship is appropriate.
In addition to these considerations, consistently with the recom-
mendations made by Podsakoff et al. (2003), we used a number of
procedural and statistical remedies against the potential problems
associated with common method bias and single respondent bias.
First, we protected respondent anonymity by assuring complete
confidentiality. Second, we reduced item ambiguity by using well
established scales and by pre-testing the questionnaire. Third, we
used different scale formats and scale anchors (“never–always”;
“strongly disagree–strongly agree”; “very little–to a great deal”; etc.).
Fourth, we used Harman's one-factor test: a principal component
factor analysis on all the variables measured using the survey
instrument revealed six factors with eigenvalues greater than 1,
which together accounted for 73.8% of the total variance; also, the
first, largest factor did not account for a majority of the variance (28%).
Therefore, it can be concluded that common method bias is not likely
to be a serious concern in our study (Podsakoff & Organ, 1986).
To test our hypotheses, a cross-sectional survey was conducted in Italy.
Thequestionnairewasoriginallydeveloped inEnglish,asalltheconstructs
used in the research were based on studies in English-speaking countries.
The English version of the questionnaire was translated into Italian by one
expert translator and then translated back into English by a second; both
translators reconciled differences. Strategic account managers were
selected as respondents. The goal of the sampling process was to include
sales organizations fromvarious selling environments. Using a database of
former participants in executive education training programs in a major
Italian management school, 220 potential respondents were selected.
Although many differences arose in their job titles, they all stated they
were in charge of managing relationships with their company's strategic
accounts. They were informed by phone that they would be receiving the
questionnaire. Participants were also assured complete confidentiality.
Respondents provided data for a specific strategic account for which they
were responsible. If they handled several accounts, they were asked to
choose the one that best represented the above-cited definition of a
strategic account. Three weeks after the initial contact, non-respondents
were followed up by telephone. A total of 127 usable questionnaires were
obtained, thus achieving a response rate of 57.7%. In line with our
objectives, many different industries are represented, including industrial
goods (34%), consumer/durable goods (28.2%), services (29.1%), pharma-
ceuticals/medical (6.8%), and others (1.9%). Equally noteworthy is the fact
that the sample includes organizations which vary in size. The average
experience of the respondents participating in the study is 4 years in their
current position, just under 7 years with their current organization, and
10.5 years in a sales position. The average number of strategic accounts of
the selling firm is 37, and the average number of accounts managed per
strategic account manager is 7.7. Remuneration is mainly based on fixed
salary (79% of total). Commissions and bonuses are 7% and 12%
respectively. As for the characteristics of the working environment,
companies in the sample operate in highly competitive markets, where
the sales force is of paramount importance (whereas e-commerce is not
relevant), there is a wide variety of customers and sales trends are mainly
stable. Early and late respondents were compared to check for a possible
response bias (Armstrong & Overton,1977). A t-test of difference in means
on all the constructs used in the research model showed no significant
difference in means between earlyand late respondents (see Appendix A).
3.2. Measures
Based on a review of the literature, we used existing scales for each
construct, with the exception of team selling. In fact, although
Workman, Homburg and Jensen (2003) have recently offered a new
three-item scale to measure “use of teams”, no generally accepted
measure of team selling exists in the sales literature. Therefore,
following our review of the literature on this topic, a new five-item
survey instrument was developed. To measure the customer orienta-
tion and selling orientation, the ten items of the SOCO scale, as
proposed by Thomas, Soutar and Ryan (2001), were used. As for role
performance and synergistic solutions, we used the two scales
developed by Schultz and Evans (2002). Finally, regarding trust we
pooled the items used by Sengupta et al. (2000), which only refer to
the customer's perceptions about the strategic account manager's
honesty/benevolence, together with those adopted by Schultz and
Evans (2002) which, in contrast, express the customer's perceptions
about the reliability and competence of the counterpart. By doing this,
our measure is consistent with the traditional definition of inter-
personal trust in buyer–seller relationship, i.e. a situation where “the
industrial buyer believes and feels that he can rely on what the
salesperson says or promises to do in a situation where the buyer is
dependent upon the salesperson's honesty and reliability (Swan &
Nolan, 1985, p.40). In fact reliability and benevolence are the two key
facets of this construct (Swan, Bowers & Richardson 1999). Our choice
to treat interpersonal trust as a unidimensional construct including
items that tap both the credibility and benevolence aspects is
consistent with the approach adopted by Doney and Cannon (1997,
p.43), who note that “Although credibility and benevolence could be
conceptually distinct […] they may be so intertwined that in practice
they are operationally inseparable”. Moreover, in keeping with the
suggestion made by Swan, Bowers and Richardson, (1999), our scale
incorporates items at different level of abstraction, i.e. items which
refer to specific behaviors of the strategic account manager (e.g. “could
be trusted to make emergency decisions, if he/she could not be
reached”), to attributes broader than a specific behavior and to general
304 P. Guenzi et al. / Industrial Marketing Management 38 (2009) 300–311

6. trust measures (e.g. “do the job with integrity”).The guidelines used
were those outlined by Churchill (1979). First, all items were
submitted to five marketing scholars and three strategic account
managers to ensure content validity. Participants were asked to check
the clarity of each item and its capacity to reflect the underlying
construct. Second, the questionnaire was pre-tested with 20 strategic
account managers participating in a Strategic Account Management
Executive Program at a major Italian business school. After some
minor adjustments, the resulting items were included in the final
survey (see Appendix B for scale items).
3.3. Model estimation
The structural equation model (Model 1), represented by the path
diagram in Fig. 1, was estimated using a partial least square (PLS)
latent path model. PLS can accommodate small samples and it
provides measurement assessment which is crucial to our study, as we
have a fairly limited sample size (Wold, 1982). In addition, it avoids
some of the restrictive assumptions imposed by LISREL-like models
(Fornell & Bookstein, 1982). In fact, as stated by O'Loughlin and
Coenders (2004), ML-SEM assumes that observations are independent
and follow a multivariate normal distribution. PLS-SEM uses non-
parametric inference methods (such as bootstrapping or jackknifing)
and is free of these assumptions. Due to our limited sample size (127
cases), we decided to use PLS. Another advantage of the PLS approach
is that it provides measurement assessment which is critical to our
study as we develop new measures (Dawes and Lee, 1996). PLS has
also been chosen because it is ideal for the early stages of theory
development, as is the case in this research (Hulland, 1999). Finally,
according to Chin (1998b), using the resampling procedures (i.e.
bootstrap and jackknife) packaged in the SmartPLS software (version
2.0), one can calculate the standard deviation and generate an
approximate t-statistic. This overcomes the disadvantage of non-
parametric methods of having no formal significance tests for the
estimated parameters. Compared to jackknifing, the bootstrap
technique offers two advantages: (1) the possibility to calculate
confidence intervals other than those calculated from a normal
distribution, and (2) the possibility to use a larger number of samples
(Chin, 1998b). Due to these reasons, we adopted the bootstrap
technique. Bootstrapping was used to draw at random a bootstrap
set of 127 cases. The process was repeated 200 times to obtain stable
standard errors and low differences between entire sample estimates
and mean of subsamples (Léger, Politis & Romano, 1992).
4. Results
4.1. Data analysis
Following standard procedures (Churchill, 1979), several steps
were taken to ensure reliability and validity of the multi-item scales.
In the first step, reliability analysis was carried out by calculating
Cronbach's alphas. For all the constructs, Cronbach's alphas exceeded
the 0.7 threshold (Nunnally, 1978). In the second step, we conducted
principal component analysis on each construct to check for
unidimensionality. One item (custo2) measuring customer orientation
was dropped, due to low indicator loadings. The PLS analysis showed
satisfactory reliability, convergent validity as well as discriminant
validity among constructs (see Tables 1 and 2 for detailed results).
The PLS results are interpreted in two stages: by assessment of its
measurement model, and by assessment of its structural model
(Fornell & Larcker, 1981). Moreover, a path model can be evaluated at
three levels: the quality of the measurement model, the quality of the
structural model, and each structural regression equation (Tenenhaus,
Esposito Vinzi, Chatelin, & Lauro, 2005).
4.1.1. Measurement model
Following Cohen (1988) the epistemic relationships were specified
as reflective for all constructs, suggesting that the constructs are
manifest in or give rise to their measures. The properties of the
measurement model are provided in Table 1, and the means, standard
deviations and correlations among the constructs are shown in
Table 2. All factor loadings are higher than 0.65, suggesting
satisfactory item reliability. As indicated in Table 1, all composite
reliability indicators are satisfactory, since they are all above the 0.7
threshold recommended by Nunnally (1978).
Convergent validity was confirmed as the average variance in
manifest variables extracted by constructs (AVE) was at least 0.56,
indicative that more variance was explained than unexplained in the
variables associated with a given construct (Fornell & Larcker, 1981).
One criterion for adequate discriminant validity is that the correlation
of a construct with its indicators (i.e., the square root of the AVE)
should exceed the correlation between the construct and any other
construct (Fornell & Larcker 1981). The findings shown in Table 2
suggest discriminant validity: in fact all diagonal elements are greater
than the off-diagonal elements in the corresponding rows and
columns.
Overall, these measurement results are satisfactory and suggest
that it is appropriate to proceed with the evaluation of the structural
model.
Table 1
Properties of measurement Model 1
Construct Indicators Factor
loadingsa
Composite
reliabilityb
Average variance
extractedc
Customer orientation custo1 0.66 0.93 0.76
custo3 0.92
custo4 0.95
custo5 0.93
Selling orientation sello1 0.68 0.86 0.56
sello2 0.75
sello3 0.72
sello4 0.74
sello5 0.83
Team selling team1 0.86 0.90 0.75
team2 0.89
team3 0.86
team4 0.75
team5 0.86
Trust trust1 0.91 0.93 0.83
trust2 0.91
trust3 0.92
trust4 0.90
Synergistic solutions syne1 0.90 0.94 0.85
syne2 0.93
syne3 0.91
Role performance role1 0.76 0.86 0.71
role2 0.86
role3 0.84
a
A loading is significant when above 0.55 (Falk and Miller 1992, p. 81).
b
Scale reliability is considered satisfactory when the composite reliability is above
0.70 (Nunnally, 1978).
c
Convergent validity is considered satisfactory when the AVE is above 0.50 (Fornell &
Larcker, 1981).
Table 2
Construct means, standard deviations and intercorrelations for Model 1
Mean SD 1 2 3 4 5 6
1. Customer orientation 5.78 1.69 0.87
2. Role performance 5.27 0.97 0.40 0.84
3. Selling orientation 2.89 1.29 −0.28 −0.22 0.75
4. Synergistic solutions 5.51 0.98 0.44 0.50 −0.30 0.92
5. Team selling 6.04 1.01 0.43 0.32 −0.21 0.39 0.86
6. Customer trust 5.62 0.80 0.55 0.46 −0.30 0.54 0.32 0.91
Note: Bold numbers on the diagonal show the square root of the AVE; numbers below
the diagonal represent construct correlations.
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P. Guenzi et al. / Industrial Marketing Management 38 (2009) 300–311

7. Because, one of our goals is to test a causal order between
relational outcomes in the model, we need to examine if synergistic
solutions and role performance act as mediating variables between
individual behaviors and customer trust. We address this issue by
comparing alternative model formulations to our baseline model (i.e.
Model 1). In Model 2 role performance and synergistic solutions were
excluded and the three strategic account manager's behaviors were
directly linked to customer trust. Model 3 includes both the direct and
indirect paths from behaviors to customer trust.
We will first discuss the results of Model 1 and then compare them
to those of Model 2 and 3.
4.1.2. Structural model and hypothesis testing
Table 3 reports the standardized parameters for Model 1, which are
obtained from bootstrap simulation (Chin, 1998a). T-values confirm
the significance of hypotheses H1 (B=0.30), H2 (B=0.30), H4 (B=
−0.17), H5 (B=0.18), H6 (B=0.22), H7 (B=0.26) and H8 (B=0.41). One
hypothesis (H3) is non-significant (B=−0.10).
The structural model demonstrates predictive power as the
variance explained (R2
) in key endogenous constructs was 0.20 for
role performance, 0.27 for synergistic solutions, 0.34 for customer
trust. The findings show that our model (i.e. Model 1) explains a large
part of the variance in the endogenous variables, with an average R2
of
0. 27. Communality and redundancy coefficients are also presented in
Table 4. They can be used essentially in the same way as the R2
, since
they reflect the relative amount of explained variance for latent and
manifest variables.
An important part of model evaluation is the examination of fit
indexes reflecting the predictive power of estimated inner and outer
model relationships. As pointed out by Tenenhaus et al. (2005, p.173),
“… differently from SEM-ML, PLS path modeling does not optimize
any scalar function so that it naturally lacks of an index that can
provide the user with a global validation of the model (as it is instead
with χ2
and related measures in SEM-ML). The GoF represents an
operational solution to this problem as it may be meant as an index for
validating the PLS model globally”.
A general criterion for evaluating goodness-of-fit (GoF) is to
calculate the geometric mean of the average communality and the
average R2
(Tenenhaus et al., 2005). According to the results in Table 4,
GoF=√[(0.73)×(0.27)]=0.44, which can be considered as satisfactory
(Tenenhaus et al., 2005;).
Then, the blindfolding approach proposed by Wold (1982) was
followed to calculate the cv-communality and cv-redundancy indexes
(see Table 5). The cv-communality index (H2
) measures the quality of
the measurement model, whereas the cv-redundancy index (i.e.
Stone–Geisser's Q2
, which Tenenhaus et al. (2005, p. 174) call F2
)
measures the quality of the structural model.
As shown in Table 5, the measurement model (H2
=0.54) shows a
better quality than the structural one (F2
=0.16). However, also
endogenous constructs are correctly estimated with a minimum F2
of 0.13 for role performance and an average F2
of 0.16.
4.1.3. The mediating role of synergistic solutions and role performance:
comparing alternative models
To test a causal order between relational outcomes, we compared
Model 1 to Model 2 and 3. In Model 2, as shown in Table 3, the direct
path between customer orientation and customer trust is significant
(B=0.47) as well as the direct path between selling orientation and
customer trust (B=−0.15). However, team selling has no significant
direct effect on customer trust (B=0.10). In comparison with our initial
model (i.e. Model 1), excluding role performance and synergistic
solutions results in a drop of R2
to 0.30 for customer trust (see Table 4).
The goodness of fit index (GoF) stays stable (GoF=0.45) as no major
changes can be observed in term of communality. Table 5 shows a
similar average cv-communality for both models (H2
=0.54 for Model
1 and H2
=0.54 for Model 2) but a higher average cv-redundancy for
Model 2 (F2
=0.16 for Model 1 and F2
=0.22 for Model 2). These results
indicate, on average, a better quality of the prediction of customer
trust for Model 2. However, it is important to keep in mind the lower
explained variance (R2
) in comparison with Model 1.
In Model 3 (see Table 4), just like in Model 1, hypotheses H1
(B=0.29), H2 (B=0.30), H4 (B=−0.16), H5 (B=0.18), H6 (B=0.22), H7
(B=0.17) and H8 (B=0.28) are significant, whereas hypothesis H3 is
non-significant (B=−0.10). In this model the direct path between
customer orientation and customer trust is significant (B=0.33),
whereas team selling and selling orientation have no significant direct
impact on customer trust (B=0.01 and B=−0.08, respectively).
As indicated in Table 4, this third model shows significant increases
in the explained variance for customer trust (R2
=0.44) as well as a
significant increase in average redundancy (F2
=0.47). In comparison
Table 3
Parameter estimation of the PLS Models by the Bootstrap method
Construct Model 1a
Model 2a
Model 3a
Dependent variable: Role performance
Customer orientation 0.30b
3.20c⁎ – – 0.29 3.02⁎
Selling orientation −0.10 1.07 – – −0.10 1.55
Team selling 0.18 2.03⁎ – – 0.18 2.04⁎
Dependent variable: Synergistic
solutions
Customer orientation 0.30 3.23⁎ – – 0.30 3.43⁎
Selling orientation −0.17 1.94⁎ – – −0.16 2.14⁎
Team selling 0.22 3.12⁎ – – 0.22 2.98⁎
Dependent variable: Customer trust
Role performance 0.26 2.74⁎ – – 0.17 1.89⁎
Synergistic solutions 0.41⁎ 4.69⁎ – – 0.28 3.04⁎
Customer orientation – – 0.47 4.22⁎ 0.33 3.00⁎
Selling orientation – – −0.15 2.18⁎ −0.08 1.04
Team selling – – 0.10 1.28 0.01 0.07
⁎Sig. if above 1.64 for 1-tailed test.
a
Model 1: original model; Model 2: model without synergistic solutions and role
performance; Model 3: full model including direct paths between customer orientation,
team selling and customer trust.
b
Standardized path coefficients.
c
T-values.
Table 4
Explained variance (R2
), communality, redundancy and goodness-of-fit index for
Models 1, 2, 3 and 4
Construct Model 1a
Model 2 Model 3 Model 4
Trust 0.34b
(0.83)c
0.14d
0.30 (0.83) 0.20 0.44 (0.83) 0.21 0.43 (0.83) 0.22
Role
performance
0.20 (0.71) 0.11 – (–) – 0.20 (0.71) 0.11 0.20 (0.71) 0.11
Synergistic
solutions
0.27 (0.85) 0.15 – (–) – 0.27 (0.85) 0.15 0.27 (0.85) 0.15
Customer
orientation
– (0.77) – – (0.76) – – (0.76) – – (0.76) –
Selling
orientation
– (0.56) – – (0.56) – – (0.56) – – (0.56) –
Team selling – (0.75) – – (0.75) – – (0.75) – – (0.75) –
Average 0.27 (0.73e
) 0.13 0.30 (0.68) 0.20 0.30 (0.73) 0.47 0.30 (0.73) 0.47
GoFf
0.44 0.45 0.47 0.47
NOTE:
a
Model 1: original model; Model 2: model without synergistic solutions and role
performance; Model 3: full model including direct paths between customer orientation,
team selling and customer trust; Model 4: final model.
b
Explained variance.
c
Communality: Communality coefficients are equal to the squared correlations
between manifest variables and their associated latent variables.
d
Redundancy: Redundancy coefficients reflect the joint predictive power of the
inner and outer model relationships.
e
Computed as a weighted average of the different communalities with the weights
being the number of manifest variables per each construct (see Tenenhaus et al., 2005,
p. 180).
f
GoF=-
= [(average communality) × (average R2
)]. Average communality is computed
as a weighted average of the different communalities with the weights being the
number of indicators per latent variable ( Tenenhaus et al., 2005).
306 P. Guenzi et al. / Industrial Marketing Management 38 (2009) 300–311

8. with Models 1 and 2, results indicate for Model 3 a similar goodness-
of-fit index (GoF=0.47). Regarding the overall quality of the measure-
ment and prediction, no significant changes can be noticed (average
cv-communality=0.54 and average cv-redundancy=0.23).
Starting from these results, we evaluated the mediating role of both
synergistic solutions and role performance. According to Baron and
Kenny (1986), to establish mediation the following conditions must be
satisfied: (a) customer orientation, selling orientation and/or team
selling must have a significant effect on customer trust in Model 2, (b)
customer orientation, selling orientation and/or team selling must have
a significant effect on role performance and/or synergistic solutions in
Model 3, (c) role performance and/or synergistic solutions must have a
significant effect on customer trust in Model 3, and (d) the effect of
customer orientation, selling orientation and/or team selling on cus-
tomer trust must be lower in Model 3 than in Model 2. There is perfect
mediation if the direct effect of customer orientation, selling orientation
and team selling on customer trust is not significant in Model 3.
Regarding the relationship between customer orientation and
customer trust (see Table 3 for the path coefficients estimates of Models
2 and 3), we found that (a) customer orientation has a significant effect on
customer trust in the absence of role performance and synergistic
solutions (Model 2), (b) customer orientation has a significant effect on
roleperformanceand synergistic solutions(Model3),(c)roleperformance
and synergistic solutions have a significant effect on customer trust
(Model 3), and (d) the effect of customer orientation on customer trust is
reduced (but is still significant) in the presence of role performance and
synergistic solutions (Model 3). Therefore, we can conclude that the
relationship between customer orientation and customer trust is partially
mediated by role performance and synergistic solutions.
As for the relationship between selling orientation and customer trust,
there is no mediating effect of role performance as condition (b) set by
Baron and Kenny (1986) is not satisfied (i.e. there is no significant
relationship in Model 3 between selling orientation and role perfor-
mance). However, we found that all the four mediating conditions were
satisfied for synergistic solutions. Specifically (see Table 3), it can be seen
that (a) selling orientation has a significant effect on customer trust in the
absence of synergistic solutions (Model 2), (b) selling orientation has a
significant effect on synergistic solutions (Model 3), (c) synergistic
solutions has a significant effect on customer trust (Model 3), and (d)
the effect of selling orientation on customer trust is reduced in the
presence of synergistic solutions (Model 3). Furthermore, the path from
sellingorientationto customer trust is not significant (Model 3). Therefore,
we can conclude that the relationship between selling orientation and
customer trust is fully mediated by synergistic solutions.
Fig. 2. Final model of strategic account managers' contribution to customer trust.
Table 5
Blindfolding results: cv-communality (H2
) and cv-redundancy (F2
) for Models 1, 2, 3
and 4
Construct Model 1a
Model 2 Model 3 Model 4
Customer trust 0.69b
(0.14)c
0.69 (0.22) 0.69 (0.35) 0.69 (0.34)
Role performance 0.41 (0.13) – (–) 0.41 (0.13) 0.41 (0.12)
Synergistic solutions 0.65 (0.21) – (–) 0.65 (0.21) 0.65 (0.21)
Customer orientation 0.56 (–) 0.56 (–) 0.56 (–) 0.56 (–)
Selling orientation 0.32 (–) 0.33 (–) 0.33 (–) 0.33 (–)
Team selling 0.59 (–) 0.60 (–) 0.60 (–) 0.60 (–)
Average 0.54 (0.16) 0.54 (0.22) 0.54 (0.23) 0.54 (0.22)
NOTE:
The cv-communality index (H2
) has been described as a cross-validated R2
between the block
manifest variables and their own latent variable (Tenenhaus et al., 2005, p. 174). In other
words, the cv-communality measures the capacity of the path model to predict the manifest
variables directly from their own latent variable by cross-validation. It uses only the
measurement model. The mean of the cv-communality indexes can be used to measure the
global quality of the measurement model if they are positive for all blocks of variables.
The quality of each structural equation is measured, instead, by the cv-redundancy
index (i.e. Stone–Geisser's Q2
). Tenenhaus et al. (2005, p. 174) call it F2
. They define it as
a kind of cross-validated R2
between the manifest variables of an endogenous latent
variable and all the manifest variables associated with the latent variables explaining
the endogenous latent variable, using the estimated structural model. More specifically,
it measures the capacity of the path model to predict the endogenous manifest variables
indirectly from a prediction of their own latent variable using the related structural
relation, by cross-validation (Tenenhaus et al., 2005, p.181). The mean of the various cv-
redundancy indexes (F2
) related to the endogenous blocks can be used to measure the
global quality of the structural model, if they are positive for all endogenous blocks. The
model has predictive relevance if F2
N0 and, if F2
N1, the observed endogenous variables
can be perfectly predicted by the model (Fornell & Bookstein, 1982).
a
Model 1: original model; Model 2: model without synergistic solutions and role
performance; Model 3: full model including direct paths between customer orientation,
team selling and customer trust; Model 4: final model.
b
Cv-communality (H2
).
c
Cv-redundancy (F2
).
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P. Guenzi et al. / Industrial Marketing Management 38 (2009) 300–311

9. Finally, the relationship between team selling and customer trust is
not mediated by role performance nor by synergistic solutions as con-
dition (a) set by Baron and Kenny (1986) is not satisfied (i.e. the path
between team selling and customer trust is not significant in Model 2).
Fig. 2 depicts the final model (Model 4), as well as the path
coefficients, t-tests and R2. Additional results are provided in Tables 4
and 5. Our final model is identical to Model 3, except for the fact that
the non significant paths are not included.
5. Conclusion
By means of an empirical research on 127 firms, this article
explored how strategic account managers can contribute to the
development of customer trust in a relational context.
Our study provides insights into the complex interrelationships
between some of the strategic account manager's behaviors and
relevant relational outcomes. More specifically, our findings show that
strategic account managers can positively affect trust in two ways.
First, they can provide synergistic solutions by successfully improving
the combined effort of the two parties to accomplish innovative joint
solutions. Secondly, they can perform their task as expected by the
strategic account, thus attaining a good role performance. As shown in
Fig. 2, both causal paths are significant, with synergistic solutions having a
stronger impact (B=0.30) than role performance (B=0.17). Together, with
the direct impact of customer orientation, they explain almost half of the
variance in customer trust (R2
=0.43), indicating that we identified key
drivers of customer trust (see Fig. 2).
To enhance the attainment of synergistic solutions, strategic account
managers should increase their customer orientation and promote team
selling (B=0.30 and 0.22 respectively). Our findings suggest that
adopting a selling orientation significantly decreases the provision of
synergistic solutions (B=−0.16). As indicated in Fig. 2, taken together,
customer orientation, selling orientation and team selling explain nearly
one third of the variance in synergistic solutions (R2
=0.27).
To improve their role performance, strategic account managers
should be customer oriented and reinforce team selling, as both paths
are significant and positive (B=0.32 and B=0.19). No significant
impact on the strategic account manager's role performance emerged
for selling orientation (H3 is not supported). Because the variance
explained in role performance is quite limited (19%), additional
research is needed to better identify its drivers.
Our results also highlight the mediating effect of role performance and
synergistic solutions. Prior studies, such as the one developed by Schultz
and Evans (2002), have neither conceptually investigated nor formally
tested this mediating role. We extended prior research by testing this role.
Interestingly, we found differences. While the role performance construct
plays a (partially) mediating role between customer orientation and
customer trust, it does not play this role between selling orientation or
team selling and customer trust. Furthermore, synergistic solutions fully
mediate the relationship between selling orientation and customer trust
and partially mediate the one between customer orientation and
customer trust. However, synergistic solutions do not play a mediating
role between team selling and customer trust.
5.1. Research contribution
Homburg, Workman and Jensen (2000) identified strategic account
management as a highly important subject for academic research and
highlighted the scarcity of studies on this area. However, with very few
notableexceptions(Boles,Barksdale&Johnson,1996;Abratt&Kelly,2002)
the specific topic of strategic account managers' behaviors is almost
unexplored. In addition to addressing some important limitations in the
study by Schultz and Evans (2002), the theoretical contribution of our
research to current knowledge can be summarized as follows.
First, this research confirms the general assumption that strategic
account managers can significantly contribute to the creation of trust in
business relationships. More specifically, this study identifies two
relational outcomes which are antecedents of customer trust, and some
of their behavioral drivers. Findings of our study clearly show that the
adoption of some specific classes of strategic account managers' behaviors
(i.e. customer orientation, team selling) can contribute to the creation of
strong and long-lasting positive relationships with customers, by
increasing relational outcomes, thus finally fostering customer trust. Our
study also suggests that selling orientation significantly decreases
synergistic solutions and hence customer trust.
Second, our research is one of the very few empirical studies on selling
behaviors carried out in non-English speaking countries. This contribution
is appreciable, as cross-cultural validation of constructs has sometimes led
to controversial findings (e.g. Herche, Swenson & Verbeke, 1996).
Third, our study tests separately distinct hypotheses for the two
dimensions of the SOCO scale, and it finds evidence of opposite
impacts for each of them.
Finally, we developed and tested a new construct (team selling) which
is particularly relevant and consistent with the relational approach, as well
as with literature on strategic account management. Although the
association between team selling and relational outcomes has already
been postulated by anecdotal evidence and theoretical articles, the
importance of its empirical validation should not be underestimated.
5.2. Managerial contribution
This study provides sales managers with some evidence of those
behaviors strategic account managers should adopt to successfully
fulfill their role as contributors in building long-term relationships.
The general managerial implication is that companies willing to build
and foster long term relationships with their accounts should facilitate
and stimulate the adoption of these behaviors on the part of their
strategic account managers.
Our findings highlight the importance of team selling. Companies may
facilitate the adoption of team selling by improving cross functional
relationships in the selling firm. This implies increasing inter-functional
integration through appropriate changes at four different levels: company
culture, organization structure, integration mechanisms and personal
characteristics of individuals (Rouziés et al., 2005). Hence, companies
should first of all carefully select candidates for strategic account manager
positions, investigating their skills and attitudes (e.g. team playing).
Secondly, companies should design training programs specifically aimed
at helping strategic account managers to develop those skills, abilities and
competencies (e.g. conflict handling) which are necessary to successfully
interact with colleagues from different departments. Then, team-based
rewardsandincentives should beadopted in ordertoincreasecooperation
in teams(Yilmaz & Hunt, 2001). Finally,strategic account managersshould
be supported by integration mechanisms aimed at increasing cross-
functional collaboration and information exchange (Kahn and Mentzer,
1998).
Our findings also show the importance of synergistic solutions in a
strategic account management setting. Developing synergistic solu-
tions implies both understanding the customer's value system (which
in turn typically requires an investment in information systems) and
finding creative solutions to customer problems. In addition to critical
characteristics of the individual strategic account manager such as
creativity and entrepreneurship (Wilson & Millman, 2003) the latter
can be fostered by a corporate culture which stimulates risk taking and
empowerment (Anderson & Huang, 2006).
From a strategic standpoint, investing in the building of long term
relationships may imply the sacrifice of short-term outcomes. This has
important implications both for firms and individual key account
managers. Companies should modify their goal setting procedures as
well as their performance evaluation systems. Findings of our research
suggest that when designing reward schemes for strategic account
managers, sales managers may, at least in part, evaluate their behavioral
performance and measure indicators of relational performance, such as
308 P. Guenzi et al. / Industrial Marketing Management 38 (2009) 300–311

10. customer retention rate or customer satisfaction (Sharma,1997). Also, the
shift from short term to long term goals typically implies accepting a
higher level of risk, because investments on customer relationships often
pay off only in the long run. To better manage risk, companies and key
account managers should invest on customer portfolio analysis and
management to optimizethe allocationof scarceresources. Increasingrole
performance, building synergistic solutions and customer trust is costly,
and the return on such investments in relationships with customers is
often difficult to predict and hard to measure. Hence, the ability of key
account managers to invest discretionary resources on selected customers
with high potential and low risk becomes increasingly crucial (Pardo, Salle
& Spencer, 1995; Ryals & Knox, 2005).
To sum up, the emphasis on a trust-building, long-term oriented
relationship selling approach suggests the need to achieve greater
control over the actual implementation of relational behaviors on the
part of their strategic account managers (see for example Cravens et
al., 1993; Grant & Cravens, 1996). In turn, this may call for radical
changes in the organizational structure of the sales department, as
well as in sales force control systems. For example, companies may
design strategic account management structures or formal sales
teams. Similarly, firms may shift from an independent to an employee
sales force (Dishman, 1996; Ross, Dalsace & Anderson, 2005), or from
outcome-based to behavior-based sales force control systems.
5.3. Limitations and directions for future research
This study has several limitations.
First, the relatively small sample size can be regarded as a
limitation. In fact we did not take into account differences in strategic
account management typologies. Using larger samples should allow
researchers to explore the potential impact of the adoption of different
approaches in implementing strategic account management programs
(Homburg et al., 2002). By definition, however, strategic account
relationships are not numerous, which makes large-scale research in
this field difficult. Instead of neglecting empirical research and relying
on conceptual frameworks only, we recommend the application of
statistical methods that are particularly well suited for small samples
(e.g. PLS and the bootstrap method). In this way, complex models can
still be estimated in a stable manner.
Second, we focused on strategic account managers as key informants
and used self-reporting measures. Although we used a number of
procedural and statistical remedies against the potential problems
associated with common method bias and single respondent bias, future
studies on the topic should ideally use dyads of respondents.
Third, as this study is cross-sectional, assigning cause must be done
with caution. Since it is focused on a dynamic phenomenon
(i.e. relationships), a longitudinal study would be more appropriate
(Frankwick, Porter & Crosby, 2001). Finally, the measurement scales
adopted in this study, although used successfully in previous research
on the topic, may not fully capture all the facets of the underlying
constructs. Hence, in future research, more comprehensive measures
would be welcome.
Many research implications can be derived from this study. Future
research on the topic should broaden our framework by including
other classes of relational behaviors and possibly “transactional”
behaviors (e.g. hard selling techniques) which may decrease customer
trust (Hawes, Strong & Winick, 1996). The simultaneous consideration
of opposing behaviors could allow the comparison of their different
impacts on relevant relational outcomes.
Similarly, different measures of performance could also be considered,
e.g. by comparing the impact of relational behaviors on long-term versus
short-term performance indicators. In fact, relational behaviors may pay off
only in the long run, and may even be detrimental to immediate sales. In
our study we focused on “soft” outcomes. This could be regarded as a
limitation. However, it should be noted that hard measures may not be very
meaningful in KAM relationships, because vendors very often invest on
such relationships for other reasons (e.g. strengthening their image as
suppliers of top firms in the market, fostering innovation by acquiring their
customer's knowledge and capabilities, etc.) and because in many cases in
these relationships economic performance may be evaluated only in the
long run. Wengler, Ehret and Saab (2006) empirically found that the vast
majority of companies adopting KAM do not use hard measures of
performance neither to set goals nor to evaluate performance. Findings of
this study clearly show that performance evaluation is almost exclusively
basedonsoftoutcomeslikecustomertrustandcustomersatisfaction.Using
hard measures of performance in KAM research is very difficult and may
even be misleading. Future studies on the topic willing to incorporate hard
measures of performance should probablyalso investigate the goals behind
the adoption of KAM in the specific sample of vendors used in the analysis.
Moreover, there is a need to understand more clearly the
organizational and personal factors supporting the adoption of
relational behaviors on the part of strategic account managers. In
terms of organizational variables, we suggest focusing the attention
on the impact of sales force control systems and training programs on
strategic account managers' behaviors. As for personal variables, the
examination of the influence of personality traits and skills of strategic
account managers would be beneficial.
Finally, we stress the importance of making international comparisons,
by means of replications and extensions of research in different cultural
contexts.
Acknowledgments
The authors wish to thank the anonymous reviewers for their
helpful comments and suggestions.
Appendix A
T-test of difference in means of the constructs between early and late
respondents
Construct T Sig⁎
Customer orientation −0.91 0.39
Selling orientation −0.65 0.52
Team selling −0.29 0.77
Customer trust −0.63 0.54
Role performance 0.80 0.44
Synergistic solutions −0.36 0.72
Appendix B
Scale Items
Construct Measure description
Customer
orientationa
For each statement, please indicate how often you act as
described with the strategic account you selected…
I try to figure out the strategic account's needs (custo1)
I have the strategic account's best interest in mind (custo2)⁎
I take a problem solving approach in selling products or services
to the strategic account (custo3)
I recommend products or services that are best suited to solving
problems (custo4)
I try to find out which kinds of products or services would be
most helpful to the strategic account (custo5)
Selling
orientationa
For each statement, please indicate how often you act as
described with the strategic account you selected…
I try to sell as much as I can, rather than satisfying the strategic
account (sello1)
I find it necessary to stretch the truth in my sales presentations
(sello2)
I try to sell as much as I can to convince the strategic account to
buy, event if it is more than wise customers would buy (sello3)
I paint too rosy a picture of the products or services to make them
(continued on next page)
(continued on next page)
309
P. Guenzi et al. / Industrial Marketing Management 38 (2009) 300–311

11. Appendix B (continued)
Construct Measure description
sound as good as possible (sello4)
I make recommendations based on what I can sell and not on the
basis of the strategic account's long-term satisfaction (sello5)
Team sellingb
Please indicate how much you agree with the following
statements…
I help this strategic account to get in touch with the different
specialists of my firm when needed (team1)
I place different experts from my organization at the disposal of
this strategic account (team2)
I organize visits and meetings between the different departments
of both companies (supplier and strategic account) (team3)
I share information about this strategic account with my
colleagues from other departments (team4)
I spend time coordinating the different employees of my firm
involved in the relationship with this strategic account (team5)
Trustb
The strategic account you selected would say about you that…
You can be trusted to get the job done right (trust1)
You could be trusted to make emergency decisions, if nobody
could be reached (trust2)
You do your job with integrity (trust3)
You will not undertake any actions to harm this strategic account
interests (trust4)
Synergistic
solutionsb
The combined results of this person and me have resulted in…
Innovative solutions to problems (syne1)
Ways to get better results for both companies (syne2)
Accomplishments that neither of us could have achieved
individually (syne3)
Role
performancec
In your point of view, how much would the strategic account you
selected say you have helped him/her…
To solve problems (role1)
To develop strategic plans that enable both parties to win (role2)
To enhance outcomes (role3)
⁎Item deleted based on refinement procedures described in the text.
a
Measured on a 9 point scale ranging from “Never” to “Always”.
b
Measured on a 7 point scale ranging from “Strongly disagree” to “Strongly agree”.
c
Measured on a 7 point scale ranging from “Very little” to “A great deal”.
References
Abratt, R., & Kelly, P. M. (2002). Customer-supplier partnerships. Perceptions of a
successful key account management program. Industrial Marketing Management, 31
(5), 467−476.
Anderson, R. E., & Huang, W. (2006). Empowering salespeople: Personal, managerial,
and organizational perspectives. Psychology and Marketing, 23(2), 139−159.
Anderson, J. C., & Narus, J. A. (1990 January). A model of distributor firm and
manufacturer firm working partnerships. Journal of Marketing, 54, 42−58.
Armstrong, J. S., & Overton, T. S. (1977 August). Estimating nonresponse bias in mail
surveys. Journal of Marketing Research, 14, 396−402.
Baldauf, A., & Cravens, D. W. (1999 January). Improving the effectiveness of field sales
organizations. Industrial Marketing Management, 28, 63−72.
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in
social psychology research: conceptual, strategic and statistical considerations.
Journal of Personality and Social Psychology, 51(6), 1173−1182.
Berry, L. L. (1996 Spring). Retailers with a future. Marketing Management, 5, 39−46.
Beverland, M. (2001). Contextual influences and the adoption and practice of
relationship selling in a business-to-business setting: An exploratory study. Jour-
nal of Personal Selling and Sales Management, 21(3), 207−216.
Biong, H., & Selnes, F. (1996). The strategic role of the salesperson in established buyer–
seller relationships. Journal of Business-to-Business Marketing, 3(3), 39−78.
Blois, K. J. (1999). Trust in business to business relationships: An evaluation of its status.
Journal of Management Studies, 36(1), 197−215.
Boles, J. S., Barksdale, H. C., Jr., & Johnson, J. T. (1996). What national account decision
makers would tell salespeople about building relationships. Journal of Business and
Industrial Marketing, 11(2), 6−19.
Boles, J. S., Babin, B. J., Brashear, T. G., & Brooks, C. (2001). An examination of the relationships
between retail work environments, salesperson selling orientation–customer orientation
and job performance. Journal of Marketing Theory & Practice, 9(3), 1−13.
Brown, T. J., Mowen, J. C., Donavan, D. T., & Licata, J. W. (2002 February). The customer
orientation of service workers: Personality trait effects on self and supervisor
performance ratings. Journal of Marketing Research, 39, 110−119.
Chin, W. W. (1998). The partial least squares approach for structural equation modeling.
In G. A. Marcoulides (Ed.), Modern Methods for Business Research London: Laurence
Erlbaum Associates.
Chin, W. W. (1998 March). Issues and opinion on structural equation modeling. MIS
Quarterly, 22, 7−16.
Churchill, G. A. (1979 February). A paradigm for developing better measures of
marketing constructs. Journal of Marketing Research, 16, 64−73.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ:
Erlbaum 1988.
Colletti, J. A., & Tubridy, G. S. (1987 August). Effective major account sales management.
Journal of Personal Selling and Sales Management, 7, 1−10.
Cravens, D. W., Ingram, T. N., LaForge, R. W., & Young, C. E. (1993). Behaviour-based and
outcome-based salesforce control systems. Journal of Marketing, 57(4), 47−59.
Cron, W., & DeCarlo, T. (2006). Sales Management (9th ed.). Hoboken, NJ: Wiley & Sons.
Crosby, L. A., Evans, K. R., & Cowles, D. (1990 July). Relationship quality in services
selling: An interpersonal influence perspective. Journal of Marketing, 54, 68−81.
Dawes, P. L., & Lee, D. Y. (1996). Communication intensity in large-scale organizational high
technology purchasing decisions. Journal of Business-to-BusinessMarketing3 (3),pp. 3–34.
Dishman, P. (1996 September). Exploring strategies for companies that use manufacturers'
representatives as their sales force. Industrial Marketing Management, 25, 453−461.
Doney, P. M., & Cannon, J. P. (1997 April). An examination of the nature of trust in buyer–
seller relationships. Journal of Marketing, 61, 35−51.
Falk, R. F., & Miller, N. B. (1992). A Primer for Soft Modeling. Akron, Ohio: The University of
Akron Press.
Flaherty, T. B., Dahlstrom, R., & Skinner, S. J. (1999 Spring). Organizational values and
role stress as determinants of customer-oriented selling performance. Journal of
Personal Selling and Sales Management, 19, 1−18.
Fornell, C., & Bookstein, F. L. (1982). A comparative analysis of two structural equation
models: LISREL and PLS applied to market data. In C. Fornell (Ed.), A Second
Generation of Multivariate Analysis. New York: Praeger.
Fornell, C., & Larcker, D. F. (1981 February). Evaluating structural equation models with
unobservable variables and measurements errors. Journal of Marketing Research, 18,
39−50.
Frankwick, G., Porter, S. S., & Crosby, L. A. (2001 Spring). Dynamics of relationship
selling: A longitudinal examination of changes in salesperson–customer relation-
ship status. Journal of Personal Selling and Sales Management, 21, 135−147.
Frazier, G. L., & Rody, R. C. (1991 January). The use of influence strategies in interfirm
relationships in industrial products channels. Journal of Marketing, 55, 52−69.
Ganesan, S. (1994 February). Determinants of long-term orientation in buyer–seller
relationships. Journal of Marketing, 58, 1−19.
Georges, L., & Eggert, A. (2003). Key account manager's role within the value creation process
of collaborative relationships. Journal of Business-to-Business Marketing, 10(4), 1−22.
Goff, B. G., Boles, J. S., Bellenger, D. N., & Stojack, C. (1997 Summer). The influence of
salesperson selling behaviors on customer satisfaction with products. Journal of
Retailing, 73, 171−183.
Grant, K., & Cravens, D. W. (1996 September). Examining sales force performance in
organizations that use behavior-based sales management processes. Industrial
Marketing Management, 25, 361−371.
Gundlach, G. T., & Murphy, P. E. (1993). Ethical and legal foundations of relational
marketing exchanges. Journal of Marketing, 57(4), 35−46.
Hawes, J. M., Strong, J. T., & Winick, B. S. (1996 September). Do closing techniques
diminish prospect trust? Industrial Marketing Management, 25, 349−360.
Herche, J., Swenson, M. J., & Verbeke, W. (1996 July). Personal selling constructs and
measures: Emic versus Etic approaches to cross-national research. European Journal
of Marketing, 30, 83−97.
Homburg, C., Workman, J. P., & Jensen, O. (2000 Fall). Fundamental changes in
marketing organization: The movement toward a customer-focused organizational
structure. Journal of the Academy of Marketing Science, 28, 459−478.
Homburg, C., Workman, J. P., & Jensen, O. (2002 April). Configurational perspective on
key account management. Journal of Marketing, 66, 38−60.
Honeycutt, E. D., Jr. (1996 September). Introduction to the special issue on selling and
sales management. Industrial Marketing Management, 25, 323−325.
Hulland, J. (1999). Use of Partial Least Squares (PLS) in strategic management research:
A review of four recent studies. Strategic Management Journal, 20, 195−204.
Humphreys, M., & Williams, M. R. (1996 Summer). Exploring the relative effects of
salesperson interpersonal process attributes and technical product attributes on
customer satisfaction. Journal of Personal Selling and Sales Management, 16, 47−57.
Iacobucci, D., & Ostrom, A. L. (1996 February). Commercial and interpersonal
relationships: Using the structure of interpersonal relationships to understand
individual-to-individual, individual-to-firm, and firm-to-firm relationships in
commerce. International Journal of Research in Marketing, 13, 53−72.
Ickes, W. (1993). Empathic accuracy. Journal of Personality, 61, 587−610.
Jackson, D. W., Jr., Widmier, S. M., Giacobbe, R., & Keith, J. E. (1999 March). Examining the
use of team selling by manufacturers' representatives. Industrial Marketing
Management, 28, 155−164.
Jap, S. D., & Weitz, B. A. (1994). Functional, relational, and strategic long-term, buyer–
supplier relationships. Working Paper.
Jolson, M. A. (1997 Fall). Broadening the scope of relationship selling. Journal of Personal
Selling and Sales Management, 17, 75−88.
Jones, E., Busch, P., & Dacin, P. (2003 April). Firm market orientation and salesperson
customer orientation: Interpersonal and intrapersonal influences on customer
service and retention in business-to-business buyer–seller relationships. Journal of
Business Research, 56, 323−340.
Kahn, K. B., & Mentzer, J. T. (1998). Marketing's integration with other departments.
Journal of Business Research, 42(1), 53−62.
Keillor, B. D., Parker, R. S., & Pettijohn, C. E. (2000). Relationship-oriented characteristics
and individual salesperson performance. Journal of Business and Industrial Market-
ing, 15(1), 7−22.
Langerak, F. (2001 September). Effects of market orientation on the behaviors of
salespersons and purchasers, channel relationships, and performance of manu-
facturers. International Journal of Research in Marketing, 18, 221−234.
Léger, C., Politis, D., & Romano, J. P. (1992 November). Bootstrap technology and
applications. Technometrics, 34, 378−398.
310 P. Guenzi et al. / Industrial Marketing Management 38 (2009) 300–311

12. Leigh, T. W., & Marshall, G. W. (2001 Spring). Research priorities in sales strategy and
performance. Journal of Personal Selling and Sales Management, 21, 83−93.
Leuthesser, L. (1997 May). Supplier relational behavior: An empirical assessment. In-
dustrial Marketing Management, 26, 245−254.
Liu, A. H., & Leach, M. P. (2001 Spring). Developing loyal customers with a value-adding sales
force: Examining customer satisfaction and the perceived credibility of consultative
salespeople. Journal of Personal Selling and Sales Management, 21, 147−157.
Martin, C. A., & Bush, A. J. (2003). The potential influence of organizational and personal
variables on customer-oriented selling. Journal of Business and Industrial Marketing,
18(2), 114−132.
Mavondo, F. T., & Rodrigo, E. M. (2001 May). The effect of relationship dimensions on
interpersonal and interorganizational commitment in organizations conducting
business between Australia and China. Journal of Business Research, 52, 111−121.
Miller, R. B., Heiman, S. E., & Tuleja, T. (1991). Successful Large Account Management.
London: Kogan Page.
Millman, T. F. (1996 December). Global key account management and systems selling.
International Business Review, 5, 631−645.
Möller, K., & Wilson, D. T. (1995). Business marketing: An Interaction and network
perspective. Boston, MA: Kluwer.
Morgan, R. M., & Hunt, S. D. (1994 July). The commitment-trust theory of relationship
marketing. Journal of Marketing, 58, 20−38.
Napolitano, L. (1997 Fall). Customer–supplier partnering: A strategy whose time has
come. Journal of Personal Selling and Sales Management, 17, 1−8.
Nunnally, J. C. (1978). Psychometric Theory. New York: McGraw-Hill.
O'Loughlin, C., & Coenders, G. (2004 November/December). Estimation of the European
customer satisfaction index: Maximum likelihood versus partial least squares;
Application to postal services. Total Quality Management, 15, 1231−1255.
Pardo, C. (1997 Fall). Key account management in the business to business field: The key
account's point of view. Journal of Personal Selling and Sales Management, 17, 17−26.
Pardo, C., Salle, R., & Spencer, R. (1995). The Process of key accountization of the firm – A
case study. Industrial Marketing Management, 22(2), 123−134.
Plank, R. E., & Reid, D. A. (1994). The mediating role of sales behaviors: an alternative
perspective of sales performance and effectiveness. Journal of Personal Selling &
Sales Management, 14(2), 43−56.
Platzer, L. C. (1984). Managing National Accounts. Conference Board Report. New York:
The Conference Board Inc.
Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in Organizational Research:
Problems and Prospects. Journal of Management, 12(4), 531−544.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method
biases in behavioral research: A critical review of the literature and recommended
remedies. Journal of Applied Psychology, 88(5), 879−903.
Ross, W. T., Dalsace, F., & Anderson, E. (2005). Should you set upyourown sales force or should
you outsource it? Pitfalls in the standard analysis. Business Horizons, 48(1), 23−36.
Rouziès, D., Anderson, E., Kohli, A. K., Michaels, R. E., Weitz, B. A., & Zoltners, A. A. (2005).
Sales and marketing integration: A proposed framework. Journal of Personal Selling
and Sales Management, 25(2), 113−122.
Ryals, L. J., & Knox, S. (2005). Measuring risk-adjusted customer lifetime value and its
impact on relationship marketing strategies and shareholder value. European
Journal of Marketing, 39(5/6), 456−472.
Saxe, R., & Weitz, B. A. (1982 August). The SOCO scale: A measure of the customer
orientation of salespeople. Journal of Marketing Research, 19, 343−351.
Schultz, R. J., & Good, D. J. (2000). Impact of consideration of future sales consequences
and customer-oriented selling on long-term buyer–seller relationships. Journal of
Business and Industrial Marketing, 15(4), 200−215.
Schultz, R. J., & Evans, K. R. (2002 Winter). Strategic collaborative communication by key
account representatives. Journal of Personal Selling and Sales Management, 22, 23−31.
Schwepker, C. H., Jr. (2003 Spring). Customer-oriented selling: A review, extension, and
directions for future research. Journal of Personal Selling and Sales Management, 23,
151−171.
Sengupta, S., Krapfel, R. E., & Pusateri, M. A. (1997 Fall). Switching costs in key account
relationships. Journal of Personal Selling and Sales Management, 17, 9−16.
Sengupta, S., Krapfel, R. E., & Pusateri, M. A. (2000 Fall). An empirical investigation of key
account salesperson effectiveness. Journal of Personal Selling and Sales Management,
20, 253−261.
Shapiro, B. P., & Moriarty, R. T. (1984). Support systems for national account
management programs: Promises made, promises kept.Marketing Science Institute
Report(84–102) 38 pages.
Sharma, A. (1997 Spring). Customer satisfaction-based incentive systems: Some
managerial and salesperson considerations. Journal of Personal Selling and Sales
Management, 17, 61−70.
Smith, J. B., & Barclay, D. W. (1997). The effects of organizational differences and trust on
the effectiveness of selling partner relationships. Journal of Marketing, 61(1), 3−21.
Spector, P. E. (2006). Method variance in organizational research. Truth or urban
legend? Organizational Research Methods, 9(2), 221−232.
Swan, J. E., Bowers, M. R., & Richardson, L. D. (1999). Customer trust in the salesperson:
An integrative review and meta-analysis of the empirical literature. Journal of
Business Research, 44(2), 93−107.
Swan, J. E., & Nolan, J. J. (1985). Gaining customer trust: A conceptual guide for the
salesperson. Journal of Personal Selling and Sales Management, 5(4), 39−48.
Swenson, M. J., & Herche, J. (1994). Social values and salesperson performance: An
empirical examination. Journal of the Academy of Marketing Science, 22(3), 283−289.
Tam, J. L. M., & Wong, Y. H. (2001). Interactive selling: A dynamic framework for services.
Journal of Services Marketing, 15(5), 379−396.
Tenenhaus, M., Esposito Vinzi, V., Chatelin, Y. M., & Lauro, C. (2005). PLS path modelling.
Computational Statistics & Data Analysis, 48, 159−205.
Thomas, R. W., Soutar, G. N., & Ryan, M. M. (2001). The selling orientation-customer
orientation (S.O.C.O.) scale: A proposed short form. Journal of Personal Selling and
Sales Management, 21(1), 63−69.
Walter, A., Ritter, T., & Gemünden, H. G. (2001). Value creation in buyer–seller
relationships – Theoretical considerations and empirical results from a supplier's
perspective. Industrial Marketing Management, 30(4), 365−377.
Weilbaker, D. C., & Weeks, W. A. (1997). The evolution of national account management: A
literature perspective. Journal of Personal Selling and Sales Management, 17(4), 49−59.
Weitz, B. A., & Bradford, K. D. (1999). Personal selling and sales management: A relationship
marketing perspective. Journal of the Academy of Marketing Science, 27(2), 241−254.
Wengler, S., Ehret, M., & Saab, S. (2006). Implementation of key account management: Who,
why, and how? An exploratory study on the current implementation of Key account
management programs. Industrial Marketing Management, 35(1), 103−112.
Wilson, D. T. (1995). An integrated model of buyer–seller relationships. Journal of the
Academy of Marketing Science, 23(4), 335−345.
Wilson, D. T. (2000). Deep Relationships: The case of the vanishing salesperson. Journal
of Personal Selling and Sales Management, 20(1), 53−61.
Wilson, K., & Millman, T. F. (2003). The global account manager as political
entrepreneur. Industrial Marketing Management, 32(2), 151−158.
Wold, H. (1982). Soft modeling: The basic design and some extensions. In K. G. Jöreskog
& H. Wold (Eds.), Systems under indirect observation: causality, structure, prediction.
Amsterdam: North Holland Publishing.
Workman, J. P., Homburg, C., & Jensen, O. (2003). Intraorganizational determinants of
key account management effectiveness. Journal of the Academy of Marketing Science,
31(1), 3−21.
Wotruba, T. R., & Castleberry, S. B. (1993). Job analysis and hiring practices for national
account marketing. Journal of Personal Selling and Sales Management, 13(3), 49−65.
Yilmaz, C., & Hunt, S. D. (2001). Salesperson cooperation: The influence of relational,
task, organizational, and personal factors. Journal of the Academy of Marketing
Science, 29(4), 335−357.
Paolo Guenzi is an Associate Professor of Marketing at Bocconi University and SDA
Bocconi School of Management, Milan, Italy. His main research interests include sales
management and relationship marketing. He has published in international journals
such as Journal of Business Research, European Journal of Marketing, International
Journal of Service Industry Management, Journal of Marketing Management, Interna-
tional Journal of Sport Marketing & Sponsorship.
Laurent Georges is an Associate Professor of Marketing at IUT-Tarbes, Toulouse,
France. His main research interest is key account management and relationship
marketing. He has published in international journals such as Industrial Marketing
Management and Journal of Selling and Major Account Management.
Catherine Pardo is an Associate Professor of Business-to-Business Marketing at EM-Lyon,
France, member of the OCE – EM Lyon (Organisations, Careers and new Elites) research
centre. Her research interests include key account management and marketing
organization.
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