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Identifying effective hunters and farmers in the salesforce: a dispositional–situational framework

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In business-to-business markets, hunting for new customers and farming existing customers are critical to achieve sales goals. Although practitioners suggest that salespeople have a preference for either hunting or farming, academic research has yet to examine when and why salespeople become oriented toward hunting or farming, and whether a simultaneous engagement in both (i.e., being ambidextrous) is efficient or damaging. In Study 1, the authors identify the link between regulatory focus and salesperson hunting and farming orientations. In Study 2, they demonstrate that (1) a promotion (prevention) focus is more strongly related to salesperson hunting (farming) orientation than is a prevention (promotion) focus, and (2) ambidextrous salespeople generate higher profits when they are customer oriented. In Study 3, the authors show that salesperson expectations about hunting success and the extent to which compensation plans are based on customer acquisition activities can change the direction of the relationship between regulatory focus and salesperson hunting and farming orientations. The authors discuss the implications of these findings for research and management of customer acquisition and retention at the salesperson level.
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ORIGINAL EMPIRICAL RESEARCH
Identifying effective hunters and farmers in the salesforce:
a dispositionalsituational framework
Thomas E. DeCarlo &Son K. Lam
Received: 1 July 2014 /Accepted: 8 January 2015
#Academy of Marketing Science 2015
Abstract In business-to-business markets, hunting for new
customers and farming existing customers are critical to
achieve sales goals. Although practitioners suggest that sales-
people have a preference for either hunting or farming, aca-
demic research has yet to examine when and why salespeople
become oriented toward hunting or farming, and whether a
simultaneous engagement in both (i.e., being ambidextrous) is
efficient or damaging. In Study 1, the authors identify the link
between regulatory focus and salesperson hunting and farm-
ing orientations. In Study 2, they demonstrate that (1) a pro-
motion (prevention) focus is more strongly related to salesper-
son hunting (farming) orientation than is a prevention
(promotion) focus, and (2) ambidextrous salespeople generate
higher profits when they are customer oriented. In Study 3, the
authors show that salesperson expectations about hunting suc-
cess and the extent to which compensation plans are based on
customer acquisition activities can change the direction of the
relationship between regulatory focus and salesperson hunting
and farming orientations. The authors discuss the implications
of these findings for research and management of customer
acquisition and retention at the salesperson level.
Keywords Salesperson hunting orientation .Salesperson
farming orientation .Customer relationship management .
Sales management .Regulatory focus
Salespeople affect firm performance in a number of ways,
most importantly by generating sales from maintaining and
enhancing existing customer relationships (i.e., Bfarming^ac-
tivities, or customer retention) and/or prospecting for new
customers (i.e., Bhunting^activities, or customer acquisition).
Each of these activities is critical for firm success in business-
to-business (B2B) markets (Moncrief et al. 2006; Sabnis et al.
2013). However, achieving a balance between hunting and
farming activities is difficult because not only are the strategic
investments of attracting new customers versus managing re-
lationships with existing ones very different from one another
(Blattberg and Deighton 1996), but they also exert diverse
effects on financial outcomes (Reichheld 1996). As an exten-
sion of prior research on the trade-offs between firm-level
customer acquisition and retention in the business-to-
consumer domain, recent research has started to examine this
issue at the individual salesperson level in the business-to-
business domain (Carter et al. 2014). However, three research
gaps remain.
First, despite the widespread recognition of the need to
strategically balance both of these sales activities, research to
date has focused on the benefits and costs associated with
either farming (e.g., Palmatier et al. 2007)or hunting (e.g.,
Sabnis et al. 2013). By failing to simultaneously examine
farming and hunting behaviors, extant research is limited in
its ability to provide insight into whywhen left to their own
discretionsalespeople develop a preference for farming over
hunting, and vice versa. The issue becomes more pronounced
when companies adopt a generalist (e.g., territory manager)
go-to-market model where B2B salespeople have discretion in
determining the strategies they use to achieve sales goals
(Zoltners et al. 2004). Given that almost 85% of B2B
salesforces adopt this model (Cron and DeCarlo 2010,p.
156), understanding why salespeople tend to gravitate toward
one or the other activities when managing a territory holds
significant theoretical and managerial importance. In fact,
Both authors contributed equally.
T. E. DeCarlo
Collat School of Business, University of Alabama at Birmingham,
219 BEC, 1150 10th Avenue South, Birmingham, AL 35294-4460,
USA
e-mail: tdecarlo@uab.edu
S. K. Lam (*)
Terry College of Business, University of Georgia, 133 Brooks Hall,
Athens, GA 30602-6258, USA
e-mail: sonlam@uga.edu
J. of the Acad. Mark. Sci.
DOI 10.1007/s11747-015-0425-x
such a study could help explain why, as suggested by practi-
tioners, the specialist organizational model with designated
hunters and farmers generally fails and why there is a high
attrition rate among hunter reps (Hancock et al. 2011).
Second, little is known about how the trade-offs salespeo-
ple experience in engaging in both of these activities (i.e.,
ambidexterity in customer engagement) may affect sales per-
formance. Recent research on customer service representa-
tivesambidextrous behavior indicates that engaging in poten-
tially conflicting tasks such as generating sales while provid-
ing services reduces efficiency but enhances customer satis-
faction and conversion rates (Jasmand et al. 2012). Carter et al.
(2014) show that the effect of salesperson acquisition time
allocation on sales revenues is moderated by management
control variables, such as salesperson financial incentives,
customer portfolio variables, and firm cross-functional coor-
dination capabilities. However, it remains unclear how the
inherent trade-off and potential synergy salespeople experi-
ence between hunting and farming will influence profit mar-
gins, an indicator of both sales revenues and cost efficiency.
Third, research has yet to identify factors that can alter a
salespersons inclination toward hunting or farming. This un-
derstanding is important, because it provides guidance to man-
agers who, for strategic reasons, may need to shape salesper-
son behaviors away from or toward such tendencies.
By addressing these important research gaps, we make a
number of contributions to the literature. First, we conceptu-
alize, develop measurement scales for, and provide the initial
empirical evidence of the nomological validity of two new
customer engagement orientation constructs, namely salesper-
son hunting and farming orientation. Practitioners commonly
use these terms to describe salesperson proclivities toward
these two activities, yet academics have lagged behind in their
conceptualdevelopment. The scales we develop will be useful
for future academic examination of salespeoples customer
engagement orientation.
Second, we shed light on why salespeople adopt a certain
customer engagement orientation. On the basis of in-depth
interviews and regulatory focus theory (Higgins 2002), we
develop a theoretical model positing that salespeople tend to
self-regulate when striving toward goal attainment using two
regulatory systems, namely promotion or prevention focus,
which will influence the extent to which they adopt a hunting
or farming orientation. Self-regulating through a promotion
focus involves strong motivations to attain desired end states,
prompting individuals to seek out new opportunities during
goal pursuit. In contrast, a prevention focus increases ones
inclination to avoid mistakes in reaching a goal because of
an increased sensitivity to negative outcomes (Lanaj et al.
2012). We posit and find that these general regulatory foci
are related to hunting and farming orientations, which are
situated, context-specific regulatory foci representative of dif-
ferent approaches by which salespeople attain performance
goals. In doing so, we demonstrate that managers can identify
hunters and farmers in their salesforce by measuring salesper-
son regulatory foci.
Third, we integrate expectancy theory (Vroom 1964)and
regulatory focus theory (e.g., Higgins 2002;Shahetal.1998)
to examine and extend the understanding of the boundary
conditions of the effect of regulatory fit on salesperson out-
comes. To this end, we establish salesperson expected hunting
success and acquisition-based compensation plans as situa-
tional factors that not only have a direct impact on salesperson
customer engagement orientations, but also interact with
salesperson regulatory foci to jointly alter these orientations.
Finally, we extend prior research on firm-level ambidexterity
(OReilly and Tushman 2008)andtheemergingresearchon
individual-level ambidexterity among boundary spanners (e.g.,
Carter et al. 2014; Jasmand et al. 2012). Specifically, we add to
the literature by showing that salesperson ambidexterity in cus-
tomer relationship management depends on a salespersonslev-
el of customer orientation. Furthermore, we extend prior firm-
level research on the influence of ambidexterity on innovation
by showing the influence of ambidexterity on a different out-
come, at the individual level, and in the new context of bound-
ary spanning activities. In doing so, our work also contributes
to previous research on customer orientation and goal orienta-
tions held by salespeople (e.g., Sujan et al. 1994).
Our study is organized as follows. We first review the
background literatures on individual orientations in sales re-
search, present a qualitative study on personality traits that
drive hunters and farmers in the salesforce, and discuss our
dispositionalsituational approach. Then, we present the re-
search hypotheses and findings from two empirical studies.
We conclude with a discussion about the theoretical and man-
agerial implications.
Conceptual background
Salesperson orientations
In contrast to firm-level orientations such as market orienta-
tion and strategic orientations, our research focuses on indi-
vidual, salesperson-level orientations involving hunting and
farming. Two streams of research emerge from a literature
review of individual orientations as predictors of salesperson
performance, as summarized in Table 1. The first research
stream focuses on salesperson customer orientation in sales-
personcustomer interactions. Customer orientation refers to
Bthe degree to which salespeople practice the marketing con-
cept by trying to help their customers make purchase decisions
that will satisfy customer needs^(Saxe and Weitz 1982,p.
344). This research suggests that customer orientation has a
positive, although weak, effect on salesperson performance
and dismisses selling orientation as undesirable (Franke and
J. of the Acad. Mark. Sci.
Tab l e 1 Prior research on individual orientations in the sales literature
Communication orientation Selling orientation and
customer orientation
Learning orientation and performance orientation Hunting orientation and farming orientation
Representative study Williams and Spiro (1985) SaxeandWeitz(1982);
Harris et al. (2005)
Sujan et al. (1994); Harris et al. (2005);Kohlietal.
(1998); VandeWalle et al. (1999)
Current study
Focus Salesperson-customer interaction Salesperson-customer interaction Salesperson goal achievement Salesperson-customer interaction and Salesperson
goal achievement
Background literature/
Theoretical lens
Communication orientation as
a trait: Leadership styles,
Salesperson task, self and
interaction orientations
Selling and customer orientation as
a state (Saxe and Weitz 1982)
Selling and customer orientation
as a trait (Harris et al. 2005)
Learning and performance orientation as a trait
(Sujan et al. 1994;Harrisetal.2005)
Conceptualized both as a trait and a state
(VandeWalle et al. 1999;Kohlietal.1998)
Basic personality type: regulatory focus affecting
salesperson hunting and farming orientation
as a surface trait
Focal antecedents Not examined Firm/Business unit variables (e.g.,
market orientation)
Individual variables (e.g., learning
orientation, performance
orientation)
Sales manager variables (e.g., feedback,
supervisory orientation)
Salesperson variables (e.g., self-efficacy, salesperson
traits such as competitiveness, need for learning,
openness to experience)
Regulatory focus and situational variables
Covariates: Firm variables (e.g., market share,
competitive intensity), territory characteristics
(e.g., sales growth), salesperson variables (e.g.,
time left in the quota cycle, quota achievement
in the current quota cycle, prior sales growth,
sales experience)
Focal outcomes Sales volume Job satisfaction, Customer
satisfaction with salesperson
Job satisfaction, Working hard (e.g., hours worked),
Working smart (adaptive selling and sales
planning), Self-assessed performance, Volume
of units sold
Profit margins produced by individual salesperson
J. of the Acad. Mark. Sci.
Park 2006; Saxe and Weitz 1982). The second research stream
considers salespeoples performance goal achievement using
the construct of goal orientation (Harris et al. 2005; Kohli et al.
1998; Sujan et al. 1994). Goal orientation includes learning
orientation, which has a positive relationship with cus-
tomer orientation, and performance orientation, which
positively affects selling orientation (Harris et al.
2005). These research streams suggest that salespeople
have, or develop, a particular orientation toward their
job, which can explain performance outcomes. Moreover,
they lend support to our fundamental argument that salespeo-
ple may hold different customer engagement orientations to-
ward hunting and farming and that these orientations could
influence performance.
Customer acquisition and retention orientation
at the salesperson level: hunting and farming orientation
At the firm level of analysis, customer acquisition and reten-
tion represent two important strategies in customer relation-
ship management (Blattberg and Deighton 1996). As a paral-
lel at the salesperson level of analysis, customer acquisition
involves hunting activities used in securing initial orders from
new customers, including prospecting, generating leads, pre-
call planning, and delivering salespresentations. Retention, on
the other hand, entails farming behavior used in selling to
existing customers, such as building long-term relationships,
creating efficiencies in order-taking, and increasing share of
wallet through cross-selling and up-selling efforts (Honeycutt
et al. 2009;Moncriefetal.2006).
For most B2B firms, the salesforce is typically well posi-
tioned to approach potential new customers as well as to sell to
current customers. However, the relatively high rejection rates
make closing new accounts for B2B salespeople very difficult
(e.g., Ingram et al. 2013). This theme is captured by Hancock
et al. (2011, p. 2) observation that B[e]ven though the
salesforce is typically best placed to find and approach poten-
tial clients, individual reps may shun the uncomfortable task
of cold-calling in favor of selling to customers they know
well.^Thus, the process associated with hunting for new ac-
counts is generally considered a higher-risk endeavor
than farming activities with existing customers (e.g.,
Blattberg and Deighton 1996). Furthermore, hunting ac-
tivities are generally evaluated in terms of Bwins,^such
as how many new accounts salespeople acquire, where-
as farming activities in terms of Blosses,^such as how
many existing customers defect. However, the personal
characteristics that underlie hunters and farmers are un-
known. Therefore, we take a grounded-theory approach
by conducting an exploratory study to help develop our
research model on salesperson hunting and farming
orientations.
Study 1: the exploratory study
We conducted in-depth interviews with seven sales and hu-
man resource managers to gain a better theoretical understand-
ing of the personal characteristics that represent hunters and
farmers. The participants were identified through the recruit-
ment office from a large southeastern university with inter-
views lasting 30 min to an hour each. Participants were select-
ed from different B2B companies located in disparate parts of
the United States. We continued the purposive sampling pro-
cedure and modified the interview script until we reached a
saturation point in terms of learning about the phenomenon
(i.e., the characteristics of hunting and farming) (Glaser and
Strauss 1967). All participants had greater than 10 years of
experience in recruiting and hiring salespeople. One of the
authors conducted all interviews, which were recorded and
transcribed verbatim. Two coders identified and categorized
the personality traits that are related to salesperson preference
for hunting for new customers and farming existing cus-
tomers. The intercoder reliability was 95%. We present repre-
sentative comments from managers in Table 2.
These comments were then compared with established
constructs in the literature. Two key findings emerge. First,
the comments suggest that in personal selling, hunters and
farmers possess distinct trait-like individual motivations
toward hunting and/or farming activities. Comments such
as risk-taker, desire to win, and positive outcome focus
were consistently mentioned for hunters, whereas farmer-
related comments centered on traits such as a preference
for routine, an amiable personality, and less aggressive-
ness. Second, the data revealed a relatively high corre-
spondence between the motivational traits that are predic-
tive of salesperson hunting and farming orientation and
promotion focus and prevention focus in regulatory focus
theory, respectively.
Predictors of salesperson hunting and farming orientations
Trait-base d predi ct ors In line with the results from Study 1, we
propose that salespeople develop preferred customer engage-
ment orientations that reflect their proclivity for engaging in
either hunting or farming activities to achieve sales goals. Given
that personal traits are organized hierarchically (broad/basic per-
sonality narrower/surface trait levels behavioral response;
Allport 1961), we also posit that salespeoples workplace regu-
latory focus, a more general personal trait, is predictive of their
customer engagement orientation, a more situated surface trait.
Accordingly, we define salesperson hunting orientation as a
situated regulatory focus in which a salesperson is inclined to
prospect for new customers in order to achieve sales goals and
salesperson farming orientation as a situated regulatory focus in
which a salesperson prefers to leverage relationships with
existing customers to attain sales goals. We also posit that
J. of the Acad. Mark. Sci.
although salespeople possess hunting and farming orientations
that are driven by their regulatory focus, these orientations may
change due to situational factors (c.f., Lanaj et al. 2012).
1
Situational predictors Because it is managerially relevant to
understand why salespeople avoid hunting activities (Hancock
et al. 2011), we also examine how situational factors can influ-
ence salespeople to develop a hunting orientation. Consistent
with this view, sales researchers have examined the interactive
effects associated with a variety of individual and organization-
al variables in predicting firm and salesperson performance
(e.g., Sujan et al. 1994; Sabnis et al. 2013). However, research
has yet to examine how regulatory focus may interact with
situational cues to predict salesperson behaviors. This possibil-
ity is, however, suggested by the concept of regulatory fit,
which indicates that the influence of ones regulatory orienta-
tion on behavior may be impacted by situational factors (För-
ster and Higgins 2005). Moreover, expectancy theory (Vroom
1964) also indicates motivation as jointly driven by expectan-
cy, instrumentality, and valence of both internal and external
stimuli. Therefore, our framework investigates the joint effects
involving, on the one hand, salesperson regulatory foci that
capture salesperson valence for particular types of behaviors
(e.g., hunting or farming activities) and outcomes and, on the
other, situational factors that capture salesperson expectancy
and instrumentality of the success and reward from those be-
haviors and outcomes (Vroom 1964). Together, these variables
jointly impact salespeoples customer engagement orientation.
We focus on two moderators, salesperson expected hunting
success and acquisition-based compensation plans.
1
Our research integrates prior research on individual orientations in
salespersoncustomer interactions with that in salesperson goal achieve-
ment. Consistent with the former, our hunting and farming orientation
constructs capture a salespersons concern for customers, but delineate
whether the concern is directed toward either existing or new customers
(i.e., main effects) or both (i.e., interaction effects). As is the case with
goal orientation, these constructs also represent how salespeople self-
regulate their behavior to pursue their performance goals.
Tabl e 2 Study 1: Practitionersrepresentative comments on hunter and farmer characteristics
Hunters Farmers
Order-getting personality, aggressive, self-motivated jumps in goes out
of his way to get new business.
Order taker, less flexible about generating revenue activities. Laid back
personality. Needs guidance, works better with a routinized customer
assignment. Intrigued with store operations, attention to detail, and
distribution side than selling to new customers.
The first thing they think about every day is kill or be killed. They
have a Type A driver personality. Typically, they are less analytical
and are risk takers. Very goal driven and evaluates success by their
results of new business generated.
Tend to be more analytical and more amiable.Theyaremore
project-oriented and more detailed. They are conservative by nature
and tend to avoid making mistakes.
They live for moment and then move on to next target. They tend to
strive to achieve a positive outcome with new accounts. They have
a personality thats OK with starting over each day.
Desire the relationship. They focus on doing the right thing with the
customer instead of I sold something. Most salespeople are farmers.
Aggressive, eager and not afraid, risk taker, high tenacity and nervous
energy. They have an attitude of Bgetitdone^, impatient.
Relationship builders, excels at follow up, trustworthiness is a key
personality trait. They have a drive to compete but not as much as the
hunter. They are less of a risk taker than hunters. In order to create value
for our firm, they need to do both.
Typically driver, task-oriented person, not emotional. They tend to
have a plan and want to achieve their goal through their plan.
Thick skinned. More determined than the average person.
Expressive types. But can develop new accounts if pushed. Amiable are
classic farmers, excellent relationship builders, have a pleasing
personality want to make others happy. They will struggle with getting
new accounts. Analytical personalities are also good with existing
accounts and make great farmers. They are typically efficient with their
time and interactions with customers, which is why existing customers
gravitate toward these people; they dont waste their time. They also
struggle with hunting tasks because they cant change or adapt. Dont
like to take risks and have a difficult time thinking outside of the box.
Tend to have more of a professional assertiveness and astrongdesire
to have a new win (for both the customer and the seller)
Ten d to maintain their base of customers.
Correspondence to regulatory focus theory: Promotion focus; Brisky^
bias; advancement and accomplishment concerns; ensure hits/
against errors of omission; sensitivity to presence or absence of
positive outcomes (i.e., gains); use of approach and eagerness
strategies.
Correspondence to regulatory focus theory: Prevention focus;
Bconservative^bias; safety and responsibility concerns; ensure against
errors of commission; sensitivity to absence or presence of negative
outcomes (i.e., losses); use of avoidance and vigilance strategies.
Interviewees include District Manager (Industrial distributor), Vice President of Sales (Financial services), VP of Sales (Office equipment manufacturer),
VP Human Resources (Electrical distributor), VP Human Resources (Electrical manufacturer), VP Human Resources (Electrical distributor), and a
Regional Sales Manager (Medical device company). Italics are added to emphasize the correspondence between practitionersperspectives and concepts
in regulatory focus theory
J. of the Acad. Mark. Sci.
Salesperson expected hunting success corresponds to the no-
tion of expectancy, the probability that extending an effort in
hunting will improve performance. We define expected hunt-
ing success as a salespersons near-term expectation of adding
new customers through prospecting. Acquisition-based com-
pensation plans captures instrumentality, the probability that
being successful in hunting will improve the compensation
salespeople receive. We define acquisition-based compensa-
tion plans as the relative percentage of a salespersonstotal
annual compensation that is derived by his or her behavior and
outcome of acquiring new customers. Because customer
acquisition-based compensation plans are promotion-framed
task incentives, the valence for such incentives is captured by
salesperson promotion focus (e.g., Shah et al. 1998).
We conducted two studies to test our conceptual model.
Study 2 employs single-firm data to test dispositional anteced-
ents of hunting and farming orientations. We also examine the
joint effect of these two customer engagement orientations on
profit margins.
2
We develop two new scales to measure sales-
person hunting and farming orientations that facilitate empir-
ical examination of the above issues. In Study 3, between-firm
data are used to test two situational antecedents and modera-
tors of salesperson hunting and farming orientations at the
individual (expected hunting success) and firm (acquisition-
based compensation plans) levels. The conceptual framework
guiding our investigation is summarized in Fig. 1.
Study 2
Regulatory focus as an antecedent of salesperson hunting
and farming orientations
Regulatory focus represents a basic dispositional trait
reflecting the tendency of individuals to pursue goals through
one of two self-regulatory motivational systems (Higgins
2002). A promotion focus is an innate motivational state
reflecting an individuals sensitivity toward attaining positive
outcomes, leading to an Beagerness^to use relatively creative
and risky strategies (Crowe and Higgins 1997), such as ex-
ploring for new customers as a means of increasing sales. In
contrast, a prevention focus is a motivational state that reflects
a desire to avoid negative outcomes, resulting in the adoption
of loss-avoidant, Bvigilant^strategies for goal attainment such
as exploiting existing customer relationships to garner incre-
mental sales.
Importantly, regulatory focus should be predictive of sur-
face traits reflecting the behavioral mindsets adopted by an
individual (Higgins 2002) and, consequently, the work behav-
iors in which that person prefers to engage (Crowe and
Higgins 1997; Förster et al. 2003). These notions are support-
ed by research conducted in non-selling workplace contexts
indicating that these two self-regulatory goal systems are pre-
dictive of distinct strategic behavior inclinations (see Lanaj
et al. 2012 for a review). This ability of regulatory focus to
influence behavior arises because individuals generally prefer
to engage in goal-related activities that provide high levels of
Bfit^with their regulatory focus (Higgins 2002).
Because a promotion focus motivates employees to have
an exploratory orientation and heightened sensitivity for ac-
complishment toward their work environment (Lanaj et al.
2012), salespeople who are promotion-focused should adopt
a stronger customer engagement orientation geared toward
hunting for new customers. As noted earlier, prospecting for,
and successfully attaining, new accounts embodies a relatively
greater approach-focused strategy in making a new sale and
more perceived uncertainty than does selling to existing ac-
counts. In addition, a promotion persons focus is naturally
oriented toward achieving Bhits^and accomplishments that
have been shown to have downstream effects on decision
making and preferred job behaviors (Förster et al. 2003;Lanaj
et al. 2012). Thus, the higher level of fit between a promotion-
based regulatory focus and hunting orientation should facili-
tate greater levels of hunting behaviors.
Because hunting behaviors are relatively incompatible with
the loss- and risk-aversion tendencies possessed by salespeople
who are prevention oriented, all else equal, these individuals are
less likely to adopt strong hunting orientations. Further, because
individuals who are prevention focused tend to prefer more
predictable work tasks (Higgins 2002), they should be motivat-
ed to engage in farming-related activities aimed at generating
sales to known, relationship-based customers versus hunting
for new prospects. A prevention focus, therefore, should en-
courage the adoption of a farming orientation.
Research indicates thatprevention and promotion represent
independent dispositions (Lanaj et al. 2012), which makes it
possible for the same person to possess high or low levels of
each orientation (Förster et al. 2003). Thus, while a promotion
focus should generally motivate salespeople to adopt a hunt-
ing orientation and a prevention focus should typically en-
courage a farming orientation, some individuals may be both
hunting and farming oriented (i.e., ambidextrous in that they
equally prefer both hunting and farming activities). In hunting
endeavors, salespeople might engage in some farming activi-
ties when the customers have just been acquired. For example,
ambidextrous salespeople may attempt to identify new oppor-
tunities for cross-selling or up-selling existing customers.
Thus, promotion (prevention) focus will also be related to
salesperson farming (hunting) orientation. Nevertheless,
2
We did not include the product term of hunting orientation and farming
orientation as the dependent variable to capture salesperson ambidexterity
because the product term cannot distinguish between a Bhigh hunting ×
low farming^ambidexterity from a Blow hunting × high farming^com-
bination, and between a Blow hunting x low farming^ambidexterity from
aBhigh hunting × high farming^combination.
J. of the Acad. Mark. Sci.
because individuals generally prefer to engage in goal-related
activities that provide high levels of Bfit^with their regulatory
focus (Higgins 2002), we hypothesize the relative strength of
association between a given regulatory focus and a customer
engagement orientation as follows:
H1a: Salesperson promotion focus is, ceteris paribus, more
positively related to a hunting orientation than is sales-
person prevention focus.
H1b: Salesperson prevention focus is, ceteris paribus,more
positively related to a farming orientation than is sales-
person promotion focus.
Interactions involving hunting and farming orientations
Two-way interaction between hunting orientation and farm-
ing orientation Prior research on regulatory focus suggests
that a high degree of fit between the goal-oriented activities
and a persons dominant regulatory focus significantly
increases a persons anticipation of task enjoyment, perceived
task success, and persistence in repeating the task (Freitas and
Higgins 2002). Extending these findings to the sales context,
we argue that because farming-oriented (hunting-oriented)
salespeople enjoy engaging with existing (new) customers,
they are more invested and persistent in meeting existing
(new) customer needs. We further argue that when salespeople
are expected to carry out both tasks, the dominant customer
engagement orientation will alter how salespeople implement
the other customer engagement task in their sales funnel man-
agement, defined as salesperson behavior to move customers
from prospects to established customers and maintain a pipe-
line of prospects and existing customers.
Because highly farming-oriented salespeople receive more
enjoyment from, and thus more persistent at, meeting existing
customer needs, their approach to sales funnel management
will likely center on extracting revenues and profits from
existing customers. As salesperson hunting orientation in-
creases from low to high, we expect highly farming-oriented
salespeople to incrementally prioritize prospecting new
Hunting
Orientation
Farming
Orientation
Covariates
Firm characteristics (Study 3)
Business unit characteristics (Study 2)
Managers’ human resource selection (Study 3)
Salesperson characteristics (Both studies)
Promotion
Focus
Prevention
Focus
Profit Margins
(Company record)
Outcome (Study 2)
Covariates
Job satisfaction (Study 2)
Demographics (Study 2)
H1a
H1b
H2
Situational Factors (Study 3)
Expected hunting success (Expectancy)
Acquisition-based compensation plan
(Instrumentality)
General Regulatory Focus Situated Regulatory Focus
H5a , H5b
H7a , H7b
H4
H6
Customer
Orientation
H3
Salesperson Ability
(Valence)
Performance Outcome
Fig. 1 Conceptual framework. Notes: The dotted paths are also estimated in the empirical model. Profit margins are company archival data
J. of the Acad. Mark. Sci.
customers from whom they can subsequently extract revenues
and profits. Because salespeople who are high on both hunting
and farming orientation will be more selective and efficient in
their funnel management, they will generate higher profit mar-
gins than those who focus on farming but fail to replenish their
pipelines of new prospects.
In contrast, low farming-oriented salespeople receive less
enjoyment from exploiting relationships with existing cus-
tomers. As a result, these salespeople are less likely to fully
leverage, from a profit perspective, their prior investments in
developing relationships with existing customers. When
coupled with a strong hunting orientation, a weak farming
orientation should further exacerbate a salespersonsmotiva-
tion to seek new customer relationships. Success in gaining
first-time orders from new customers often requires significant
incentives (e.g., trial orders and/or price cuts; Dwyer et al.
1987), resulting in sales that produce relatively lower profit
margins. As salesperson hunting orientation increases from
low to high, we expect hunting orientation to dominate sales-
person behavior such that these low farming-oriented sales-
people incur incrementally higher acquisition costs and lower
sales revenues from existing customers. Therefore, we
hypothesize:
H2: There is a two-way interaction between salesperson hunt-
ing orientation and farming orientation on profit margins
such that the relationshipbetween hunting orientation and
profit margins is positive when farming orientation is
high, but negative when farming orientation is low.
Three-way interaction among hunting orientation, farming
orientation, and customer orientation It remains unclear
when salesperson ambidexterity in customer engagement ori-
entation, that is pursuing both hunting and farming orienta-
tions, poses as an advantage or a physical and mental con-
straint. In firm-level research on innovation, Kyriakopoulos
and Moorman (2004) show that the trade-off between explo-
ration and exploitation does not occur when the firm is market
oriented. At the individual level, however, not only is there a
lack of understanding of individual motivations that influence
boundary spannersambidexterity (Jasmand et al. 2012), but
there has been debate about the degree to which employees
can succeed when assigned seemingly contradictory tasks
(e.g., Gupta et al. 2006). To help shed light on this debate,
we posit that while salespeoples customer engagement orien-
tations determine their investment and perseverance in dealing
with existing and/or new customers, customer orientation pro-
vides salespeople with the ability and knowledge to under-
stand and solve customer problems to become successful in
such activities.
Specifically, when an ambidextrous salesperson is also
highly customer oriented, we expect greater efficiency in man-
aging the sales funnel of both new and existing customers,
resulting in a positive synergistic effect on profits. Further-
more, customer orientation provides salespeople with pro-
found customer knowledge, a form of resource slack, that
relieves ambidextrous salespeople from the mental and phys-
ical constraints of engaging with both new and existing cus-
tomers (c.f., Kyriakopoulos and Moorman 2004;Vossetal.
2008). Conversely, when salespeople experience an imbal-
ance among the three orientations, we expect their perfor-
mance will suffer for at least two reasons. First, low
customer-oriented salespeople will experience greater physi-
cal and mental constraints because they lack the skills to ef-
fectively perform either hunting or farming activities. Second,
high customer-oriented salespeople who are not ambidextrous
(e.g., high hunting orientation but low farming orientation, or
vice versa) will be suboptimal in extracting profits from their
sales funnel, such as missing out on cross-selling and up-
selling opportunities or overinvesting in new prospects that
they fail to subsequently nurture and retain. Thus, we
hypothesize:
H3: There is a three-way interaction between salesperson
hunting orientation, farming orientation, and customer
orientation on profit margins such that the relationship
between hunting orientation and profit margins is more
positive when both farming orientation and customer ori-
entation are high.
Procedures and sample
B2B salespeople from a publicly-traded industrial distribution
firm with over 1,200 profit center locations (i.e., stores) na-
tionwide were selected for the study. According to executives,
the large network of stores is strategically important in pro-
viding a high level of localized inventory support to each
stores territory. The distributor offers over 325,000 different
SKUs of industrial products to the marketplace and employs
both inside and outside, territory-based salespeople. The mar-
ket is highly competitive, with the sponsoring distributor hav-
ing a 2% market share. The outside salesforce, which is the
focusofthisstudy,isthecompanys primary revenue-
generating function and is responsible for managing all as-
pects of customer relationships by actively working an
assigned territory for prospects, making sales presentations,
closing sales, and managing current customers. The
salesforce is compensated using a salary plus commission
plan, with the variable portion of the performance scorecard
based on a combination of average profit margins earned,
growth of current customer sales revenues, and number of
new customers closed during the month. Importantly, all
salespeople have the freedom to invest their time in activities
associated with prospecting for new customers (i.e., hunting)
or building existing relationships with current customers
J. of the Acad. Mark. Sci.
(i.e., farming).
3
The firm also provides its salespeople the
freedom to determine the final sales price to customers.
We approached executives at the firm for their participa-
tion, offering them a report of the overall results and custom-
ized analyses for their internal purposes. The company pro-
vided us with the email addresses of 1,174 salespeople from
the Southeast, Midwest, and Southwest regions involving 22
different states and salesperson profit margins from company
records. Salespeople were e-mailed anintroductory letter from
top management indicating their support for the project. These
individuals were subsequently emailed an invitation to partic-
ipate in the online study thatincluded a brief description of the
study, a promise of anonymity, and a Web link to access the
survey. A second request was e-mailed 2 weeks later. No
incentives for participation in the study were provided.
We received complete responses from 514 salespeople. To
ensure the stability of the performance data, we focused on
salespeople who worked at the same store for at least 6 con-
secutive months, 3 months before and 3 months after the
study. Because of promotions, changing stores, and salesper-
son departures during the 6 month study period, 157 salespeo-
ple were eliminated from the study, resulting in a final sample
of 357 salespeople (or 30.4% response rate). About 43% of
salespeople were 30 years old or younger, and 11.8% were
female. The salespeople had a mean sales experience of
69.75 months, company tenure of 44.34 months, and industry
experience of 56.30 months. The vast majority (85.7%) of
respondents held an undergraduate degree or higher. There
were no statistically significant differences between early
and late respondents on model and demographic variables.
To check for nonresponse bias, we used demographic vari-
ables from company records to compare characteristics be-
tween those responded and those who did not and also found
no differences (Armstrong and Overton 1977).
Measures
Scales We developed multi-item scales assessing hunting and
farming orientations by following Churchills(1979)recom-
mended procedures. First, we developed an initial pool of
items from our exploratory research efforts and then refined
the wording of several items based on suggestions from dis-
tributor salespeople and academic experts. We then pretested
the scale using a small sample of the focal firmssalespeople
(N=49) who did not participate in the main study. Following
this pretest, we made minor wording changes to the scales.
The final measures consist of four items for each customer
engagement orientation. We measured salesperson promotion
focus and prevention focus by adapting a scale from Neubert
et al. (2008) to fit with a work-related context. The firm cal-
culated profit margins by subtracting costs of goods sold from
total sales revenues a salesperson generates. To test for evi-
dence of causality and to smooth out abnormality, we used the
average profit margins of 3 consecutive months following the
survey. A 3-month lag was deemed sufficient to observe the
outcome from salesperson hunting and farming activities in
the industrial distribution context.
Controls For antecedents to salesperson hunting and farming
orientation, we controlled for two business unit variables
(store size, prior store sales growth) and several salesperson
variables (prior salesperson sales growth, sales experience,
age, education, and job satisfaction). Gender was not included
in Study 2 due to the predominantly male sample. We includ-
ed two growth-related variables as covariates because sales-
people are likely to become either more hunting oriented (to
achieve long-term growth) or more farming oriented (to main-
tain short-term growth) when the business is growing. We
calculated prior salesperson and store sales growth as the av-
erage of sales growth of the salesperson and each store, re-
spectively, in the 3 months prior to our survey. Store size, a
proxy of the market power of the company in the territory, is
based on the companys categorization of the average sales
revenue of each store. For outcomes, we controlled for sales-
person job satisfaction, measured using three items from
Hackman and Oldhams(1975)scale.Appendix 1 contains a
list of all the key measurement scales.
Analytical strategy
While we collected the data from multiple stores, the majority
(90%) of the stores had only one outside salesperson. There-
fore, we used salespeople as the level of analysis. Because it
includes latent variable interactions, we specified the structur-
al equation model to be estimated by a numerical integration
algorithm, using Mplus 7 (Muthén and Muthén 19982012).
This method has been shown to be superior to many other
alternative techniques (Klein and Moosbrugger 2000). It does
not produce standard fit indexes as in a traditional main-
effects only structural model; rather, this method produces fit
indices in the form of log-likelihood (LL), Akaikesinforma-
tion criterion (AIC) and Bayesian information criterion (BIC).
We compared main effects and models with interactions
using 2LL, with the differences in the number of free
parameters between the two models as the degrees of
freedom. In the model specification, we allow the resid-
uals of hunting orientation and farming orientation to be
correlated.
To reduce common method biases, we followed Podsakoff
et al. (2012)s recommendations. First, as a procedural
3
One District Sales Manager said, BThey [salespeople] have various
quotas, such as sales volume, profit margin and number of new accounts,
but its up to the salesperson as to how they achieve those goals each
month.^Salespeople agreed, BI like working for this company because
they let me make my own decisions on how to manage my territory.^
J. of the Acad. Mark. Sci.
remedy, we used a variety of scale types and reversed the
wording on several items. Second, we conducted the
Harmans single-factor test, which indicated that the single-
factor model had a significantly worse model fit than the mul-
tifactor measurement model. In the principal components fac-
tor analysis including all corresponding items without rota-
tion, the highest variance explained by one factor is 28.6%.
Third, as a more stringent test, we specified a structural model
that included a common method factor with all of the mea-
sures as indicators and all the salesperson-reported variables
of our theoretical model. The common method factor is
constrained to be unrelated to all the constructs (Podsakoff
et al. 2012). In this model, the path coefficients remain stable,
providing further evidence that the empirical results are not
affected by common method bias.
Measurement model
We assessed reliability and validity for each measure using
exploratory and confirmatory factor analyses. The exploratory
factor analysis showed that the new scales of hunting and
farming orientations were well-behaved and did not cross load
heavily onto unintended factors. The confirmatory factor anal-
ysis (CFA) model indicated a good fit (comparative fit index
[CFI]=0.95, Root Mean Square Error of Approximation
[RMSEA]=0.06; χ
2
=678.44, d.f. = 215, χ
2
/d.f. = 3.15;
Bagozzi and Yi 2012). For all the constructs, no Cronbach
alpha values were lower than 0.70. The average variance ex-
tracted (AVE) was at least 0.50 for all the constructs, with the
only exception of farming orientation (AVE=0.45). All of the
constructs also possessed discriminant validity, given that the
AVE exceeds the squared correlations between all pairs of
constructs (Fornell and Larcker 1981). The correlation matrix,
reliability indices, and variable descriptive statistics appear in
the lower triangle in Table 3.
We also assessed whether there is discriminant validity
among hunting orientation, farming orientation and customer
orientation. The five-item customer orientation scale adapted
from Thomas et al. (2001) exhibited good scale properties
with a Cronbach alpha of 0.97 and AVE of 0.87. An explor-
atory factor analysis without rotation of all the items from the
three constructs showed that the items loaded on three distinct
factors. We then tested discriminant validity among the three
constructs by conducting a series of nested chi-square analy-
ses. The results show that constraining the correlation of any
pair of these variables to one resulted in models with a poorer
fit with a significant increase in the chi-square statistics (Δχ
2
[d.f. =1]=359.71; 353.05; and 1,005.39, p<0.00 for the farm-
ing orientationcustomer orientation, farming orientation
customer orientation,and hunting orientationcustomer orien-
tation pairs, respectively). All the three constructs also satisfy
the stringent test of discriminant validity because the AVE
Tabl e 3 Means, standard deviations, and intercorrelation matrix
Variable 123456789101112
1. Promotion focus 1 0.48 0.27 0.21 0.21 0.05 0.08 0.25 0.00 0.04
2. Prevention focus 0.41 1 0.22 0.39 0.17 0.03 0.11 0.22 0.08 0.09
3. Hunting orientation 0.21 0.21 1 0.11 0.10 0.12 0.39 0.33 0.16 0.04
4. Farming orientation 0.14 0.14 0.11 1 0.10 0.01 0.18 0.32 0.18 0.16
5. Customer orientation 0.37 0.62 0.14 0.20 1
6. Profit margin (%) 0.02 0.03 0.05 0.01 0.01 1
7. Quota completed in quota cycle (%) 1 0.19 0.07 0.30 0.02 0.07
8. Time left in the quota cycle (months) 1 0.03 0.08 0.08 0.19
9. Expected hunting success 1 0.32 0.14 0.11
10. Supervisor selection 10.040.08
11. Acquisition-based compensation plan (%) 10.11
12. Company market share (%) 1
M (Study 2) 6.10 5.19 4.72 6.05 6.30 51.61
SD (Study 2) 0.99 1.19 1.32 0.77 1.07 5.31
Cronbach alpha (Study 2) 0.83 0.88 0.92 0.78 0.97 _
a
AVE (Study 2) 0.66 0.65 0.74 0.45 0.87 _
a
M (Study 3) 5.09 5.85 4.91 5.77 70.86 2.94 4.95 5.21 50.32 40.79
SD (Study 3) 1.22 1.31 1.29 0.98 26.75 2.68 1.36 1.18 18.52 25.71
Cronbach alpha (Study 3) 0.76 0.93 0.88 0.83 _
b
_
b
_
b
0.77 _
b
_
b
AVE (Study 3) 0.59 0.74 0.65 0.55 _
b
_
b
_
b
0.53 _
b
_
b
For Study 2: |r|0.12 significant at p<0.05; Study 3: |r|0.16 significant at p<0.05 (two-tailed). Correlations for Study 2 (N=357) appear below the
diagonal and those for Study 3 (N=200) appear above the diagonal.
a
company data,
b
single item. For Study 2: profit margin is in%
J. of the Acad. Mark. Sci.
exceeds the squared correlations between all pairs of
constructs (Fornell and Larcker 1981). The zero-order
correlations between farming orientationcustomer orien-
tation and hunting orientationcustomer orientation are
0.20 and 0.14, respectively. Thus, there is concrete ev-
idence of discriminant validity among the three con-
structs, hunting orientation, farming orientation and cus-
tomer orientation.
4
Results
We report the empirical results of Study 2 in Table 4.We
present the unstandardized coefficients from the main-effects
model first (the baseline model, Model 1) followed by those
from the models with a two-way interaction (Model 2) and a
three-way interaction (Model 3).
Main-effects only model To test H1a and H1b, we first esti-
mated a main-effects model. We found that salesperson pro-
motion focus is positively related to hunting orientation (γ=
0.176, p<0.01), and salesperson prevention focus is positively
related to farming orientation (γ=0.201, p<0.01). Neither the
relationship between salesperson prevention focus and hunt-
ing orientation nor that between promotion focus and farming
orientation is significant. We examined whether the relation-
ship between promotion focus and hunting orientation is
stronger than that between prevention focus and hunting ori-
entation (H1a) and the relationship between prevention focus
and farming orientation is stronger than that between promo-
tion focus and farming orientation (H1b) by imposing two
constraints to the model. The Wald test with two constraints
is significant (χ2[d.f.=2]=6.50, p<0.05), indicating the rela-
tive strength of each regulatory focus in predicting salesperson
hunting and farming orientation. Thus, H1a and H1b are
supported.
Full model with the interaction effects We added the two-way
interaction effect between hunting orientation and farming
orientation to test H2. Unlike Model 1, the effects of hunting
and farming orientation on profit margins in Model 2 are con-
ditional effects. We found that the interaction was positive and
significant (β=1.154, p<0.05), but the main effects of both
hunting and farming on profit marginsare not significant. This
result and the interaction plot in Fig. 2show support of H2. To
test H3, we added all the lower-order interactions and a three-
way interaction among hunting, farming, and customer orien-
tations to Model 2 and found it to be significant in predicting
profit margins (β=1.298, p< 0.05, Model 3). As Table 4
shows, the full model with interactions had a better model fit
than the main-effects only model.
Additional analysis As a robustness test to see whether the
interaction effect between hunting orientation and farming
orientation is confounded by their quadratic effects on profit
margins (Ganzach 1997), we added the quadratic terms of
these independent variables to the model. None of these terms
have any significant effects on profit margins. In addition, an
assumption we made is that salespeople will devote more time
toward hunting (farming) with greater hunting (farming) ori-
entation. We measured salesperson hunting and farming time
allocation by asking salespeople how they normally allocate
their time to a battery of multiple selling activities during a
week. We found a significant correlation between a composite
measure of time allocated toward hunting activities and hunt-
ing orientation (0.17, p<0.05) and farming orientation (0.09,
p<0.10). These intuitive relationships further support our
theorization.
We also examined whether job satisfaction predicts sales-
person hunting and farming orientation. We found that sales-
people who are satisfied with the job are more likely to be
hunting oriented (γ=0.238, s.e. = 0.064, p<0.01), but there is
no significant relationship between job satisfaction and farm-
ing orientation (γ=0.042, s.e. = 0.029, p>0.10). The qua-
dratic term of job satisfaction on profit margins is not signif-
icant (β=0.058, s.e. = 0.152, n.s.). The inclusion of these
additional paths does not influence the results in the more
parsimonious model that we reported.
As a test of the robustness of the time lag, we reestimated
the entire model with profit margins for each of the 3 months
after the survey instead of an average of all the 3 months after
the survey. We also included the average of profit margins of
the 3 months prior to the survey to control for unobserved
explanatory variables (Wooldridge 2003). The results of all
these analyses show that the hypotheses are again supported
in the predicted direction.
Moderated mediation analysis The results suggest that the
profit impact of promotion focus is mediated by hunting ori-
entation and moderated by farming and customer orientations.
We conduct a moderated mediation analysis using the PRO-
CESS model (Hayes 2013). In the presence of hunting orien-
tation as the mediator, the direct effect from promotion focus
on profit margins is not significant. As the confidence inter-
vals in Appendix 2 shows, the conditional indirect effect is
negative when the salesperson is not farming oriented but
highly customer oriented, but positive when the salesperson
is farming oriented and highly customer oriented.
4
We also found discriminant validity among hunting orientation, farming
orientation, and competitor orientation. The zero-order correlations be-
tween farming orientationcompetitor orientation and hunting orienta-
tioncompetitor orientation are 0.13 and 0.35, respectively. In addition,
one of the measurement items in the farming orientation scale has a factor
loading that is lower than 0.60. We decide to keep this item in our analysis
for theoretical completeness; removing it actually makes the path coeffi-
cients stronger than the ones we reported in the BResults^section.
J. of the Acad. Mark. Sci.
Tab l e 4 Study 2: Empirical results
Dependent variables
Predictors Hunting orientation Farming orientation Profit margins
Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 Model 1 Model 2 Model 3
Promotion focus (H1a) 0.176*** (0.066) 0.178*** (0.066) 0.180*** (0.066) 0.018 (0.031) 0.018 (0.031) 0.018 (0.031)
Prevention focus (H1b) 0.117 (0.096) 0.114 (0.096) 0.118 (0.098) 0.201*** (0.069) 0.200*** (0.070) 0.203*** (0.071)
Hunting orientation 0.261 (0.252) 0.178 (0.321) 0.069 (0.304)
Farming orientation 0.168 (0.513) 0.037 (0.669) 0.489 (0.754)
Customer orientation 0.015 (0.259) 0.001 (0.261) 0.099 (0.389)
Hunting orientation ×
Farming orientation (H2)
1.154** (0.491) 1.055** (0.493)
Hunting orientation ×
Customer orientation
0.215 (0.365)
Farming orientation ×
Customer orientation
0.361 (0.830)
Hunting Ori. × Farming Ori. ×
Customer orientation (H3)
1.298** (0.617)
Control variables
Business unit variables
Business unit size
(store size)
0.074 (0.107) 0.044 (0.112) 0.035 (0.121) 0.012 (0.054) 0.012 (0.055) 0.009 (0.055)
Business prior sales growth 0.001 (0.004) 0.001 (0.004) 0.001 (0.004) 0.003 (0.003) 0.003 (0.003) 0.003 (0.003)
Salesperson variables
Salesperson prior sales
growth
0.004** (0.002) 0.004** (0.002) 0.004** (0.002) 0.001 (0.001) 0.001 (0.001) 0.001 (0.001)
Sales experience 0.001 (0.001) 0.001 (0.001) 0.001 (0.001) 0.001*** (0.000) 0.001*** (0.000) 0.001*** (0.000) 0.004 (0.006) 0.003 (0.006) 0.003 (0.006)
Age 0.087 (0.067) 0.097 (0.069) 0.099 (0.070) 0.010 (0.034) 0.009 (0.036) 0.010 (0.033) 0.013 (0.224) 0.011 (0.227) 0.001 (0.227)
Education 0.129* (0.067) 0.113 (0.071) 0.107 (0.074) 0.033 (0.042) 0.036 (0.041) 0.035 (0.038) 0.256 (0.240) 0.293 (0.234) 0.327 (0.237)
Job satisfaction 0.163 (0.257) 0.124 (0.243) 0.144 (0.240)
Model fit information Model 1: LL=11,519.92; Model 2: LL= 11,516.06; Model 3: LL= 11,512.75
Change in model fit Model 1 to Model 2: 2LL= 7.72 (df=1, p< 0.01)
Change in model fit Model 2 to Model 3: 2LL= 6.62 (df=3, p< 0.10)
*p<0.10, ** p<0.05, *** p<0.01. Unstandardized coefficients are reported with standard errors in parentheses. We report coefficients of the main-effects only model first (Model 1), the model with a two-
way interaction second (Model 2), and the model with a three-way interaction third (Model 3)
J. of the Acad. Mark. Sci.
Discussion
Discussion of findings Study 2 provides strong support for
our theorizing. In addition to the hypothesized antecedents
to salesperson hunting and farming orientation, we also found
significant effects of salesperson prior sales growth and edu-
cation level on hunting orientation but not farming orientation.
Both of the conditional effects of hunting and farming orien-
tation on profit margins are not significant while their interac-
tion effect on profit is positive. This cross-over, two-way
interaction, illustrated in Fig. 2, Panel A, is important because
it suggests that the relationship between hunting orientation
and profit margins can be negative when farming orientation
is low, but positive when farming orientation is high.
The three-way interaction is plotted in Fig. 2, Panel B. It
indicates that the interaction in Fig. 2, Panel A occurs when
salespeople are highly customer oriented. When salespeople
are not customer oriented, however, there is no interaction
effect between salesperson hunting orientation and farming
orientation in predicting profit margins. Customer-oriented
48
49
50
51
52
53
54
55
Low Hunting Orientation High Hunting Orientation
Profit Margins (%)
Low Farming Orientation
High Farming Orientation
45
47
49
51
53
55
57
59
Low Huntin
g
Orientation Hi
g
h Huntin
g
Orientation
Profit Margins (%)
(1) High Farming Orientation, High Customer Orientation
(2) High Farming Orientation, Low Customer Orientation
(3) Low Farming Orientation, High Customer Orientation
(4) Low Farming Orientation, Low Customer Orientation
a
b
Fig. 2 Study 2: Joint impact of
hunting and farming orientations
on profit margins
J. of the Acad. Mark. Sci.
salespeople who are farming oriented produce higher profit
margins when they are also hunting oriented. Furthermore,
relative to salespeople who are not customer oriented, the
relationship between hunting orientation and profit margins
is more negative among salespeople who are highly customer
oriented but not farming oriented.
Study limitations A main limitation of Study 2, a single-
firm study, is that there is no significant variation among
salespeople with regard to factors such as the compensa-
tion plan and expected hunting success in the remaining
time of the current quota cycle. More broadly, it did not
control for between-firm situational factors that might in-
fluence salespeoples customer engagement orientation.
We address these issues in Study 3 with a between-firm
dataset.
Study 3
Since salespeople tend to shy away from hunting activities,
we focus on salesperson hunting orientation as the depen-
dent variable in Study 3. The primary goal of Study 3 is to
extend Study 2 by examining two between-firm situational
factors that influence the relationship between salespeoples
regulatory focus and their hunting orientation: salesperson
expected hunting success and acquisition-based compensa-
tion plans. As we explained earlier, these two variables cap-
ture expectancy and instrumentality components of sales-
person motivation to engage in hunting, respectively. For
completeness, we also include farming orientation as anoth-
er dependent variable.
Expected hunting success
Main effect Classic motivation theories, such as expectan-
cy theory (Vroom 1964), hold that strong a priori expec-
tations of task success often results in a self-fulfilling
prophecy as people anticipate putting forth the appropriate
task-related effort necessary to achieve the goal (also
known as the Btypical shifts^phenomenon). The implica-
tion is that, all else equal, stronger hunting success expec-
tations should enhance salesperson hunting-oriented activ-
ities. This prediction is also supported, in part, by Higgins
et al.s(2001) findings suggesting that when people hold
promotion-related success expectations about a goal, they
tend to adopt an eagerness orientation that is normally
attributed to a promotion focus. As a result, greater hunt-
ing success expectations should motivate salespeople to
adopt a stronger hunting orientation.
H4: Salespeoples expected hunting success is positively re-
lated to their hunting orientation.
Interaction effect between promotion focus and expected hunt-
ing success in predicting hunting orientation While expectan-
cy theory predicts an increase in motivation to hunt under
strong expectations of task success, empirical work in regula-
tory focus theory suggests that ones regulatory focus can play
an important moderating role in shaping an individuals
goal-related behaviors when the situation matches with the
regulatory focus (Crowe and Higgins 1997; Higgins et al.
2001). We reconcile these two seemingly contradictory pre-
dictions by drawing from research on situation strength
(Mischel 1977), which indicates that when the situation is
weak, or considered not salient to task accomplishment,
personal factors will be more predictive of peoplesbehav-
ior, as suggested in regulatory focus research. In contrast,
when the situation is perceived as salient or strong, the
predictive value of personality trait is attenuated and the
situation becomes more predictive of individual behavior,
as suggested in expectancy theory.
All else equal, promotion-focused people tend to engage in
more risky behaviors than prevent-focused people to achieve
performance goals (Lanaj et al. 2012) and are more persistent in
continuing to complete difficult tasks following failure (Crowe
and Higgins 1997). Extending this notion to our context, sales-
people with a strong promotion focus would be inherently mo-
tivated to implement riskier strategies to attain achievement-
related goals, such as prospecting for new customers. Thus, in
situations wherein expectations of hunting success are unfavor-
able, we expect promotion-oriented salespeople to be more
likely to assume a hunting orientation. Conversely, when ex-
pected hunting success is high, the effect of the situation is
strong. Under these conditions, salespeople are likely to adopt
a stronger hunting orientation, regardless of the extent to which
they are promotion-focusedsimilar to our main effect predic-
tion above (H4). Therefore, we hypothesize:
H5a: The relationship between promotion focus and hunting
orientation becomes stronger and positive when expect-
ed hunting success is low than when it is high.
Interaction effect between prevention focus and expected
hunting success in predicting hunting orientation Regulatory
focus theory suggests that prevention focus and expected
hunting success will jointly influence salesperson hunting ori-
entation under certain situations. Given the underlying tenden-
cy of prevention-focused individuals to adopt more Bvigilant^
strategies during goal pursuit and avoid mistakes in goal at-
tainment (Higgins et al. 2001), prevention-focused salespeo-
ple holding lower expectations of future hunting success
J. of the Acad. Mark. Sci.
should exhibit significantly weaker tendencies to engage in
hunting activities. Higgins et al.s(2001) findings also suggest
that strong situational inducements can temporarily alter a
persons regulatory focus from promotion to prevention and
vice versa. Thus, the presence of positive expectations regard-
ing future hunting success should encourage salespeople to
temporarily assume hunting orientations as they develop
strategies to make quota. Consistent with our earlier
argument, the influence of such expectations on the
adoption of a hunting orientation should occur even
for prevention-oriented salespeople who might otherwise
be farming oriented. Again, our prediction is also con-
sistent with research on situation strength, attributing a
weaker role to dispositional variables (here, regulatory
focus) in the presence of salient situational factors (c.f.
Mischel 1977).
H5b: The relationship between salesperson prevention focus
and hunting orientation becomes stronger (weaker) and
positive (negative) when expected hunting success is
high (low).
Acquisition-based compensation plans
Main effect Both expectancy theory and regulatory focus the-
ory inform the same prediction. Under high customer acqui-
sitionbased compensation plans, salespeople are provided a
strong extrinsic incentive that underscores the instrumentality
component of salesperson motivation to engage in hunting.
Acquisition-based compensation plans also provide an incen-
tive that emphasizes the Bwin,^which directly prompts the
adoption of an eagerness strategy of hunting orientation. As
a result, we expect high customer acquisitionbased pay plans
to be positively related to salesperson hunting orientation.
H6: Customer acquisitionbased compensation plans are pos-
itively related to salesperson hunting.
Interaction effect between promotion focus and acquisition-
based compensation plans A key attribute of promotion-
focused people is that they are chronically predisposed to
self-regulate to attain Bhits^by engaging in greater task
diversity to ensure goal attainment (Förster and Higgins
2005). Promotion-oriented people are also more prone to
focus on Bmaximal goals^that are in the upper range of
performance outcomes (Pennington and Roese 2003). As a
result, they tend to have a natural inclination to engage in
risker activities in attaining goals (Crowe and Higgins
1997). In combination, these studies suggest that as pro-
motion focus becomes stronger, salespeople will be more
likely to engage in a greater variety of behaviors that
include hunting activities to ensure they reach performance
goals, even when the reward system does not place an
emphasis on such behavior. In other words, we expect a
positive relationship between promotion focus and hunting
orientation under low acquisition-based compensation
plans.
However, under a high acquisition-based compensation
plan, the inducement of the external factor (i.e., acquisition-
based compensation) should temporarily alter the effect of
regulatory focus on customer engagement orientation behav-
iors. Specifically, for both high and low promotion focus
salespeople, we expect a greater emphasis on hunting activi-
ties. This prediction is in line with our earlier discussion re-
garding the potential for the strength of a situation to over-
power the influence of a personal factor. Accordingly, we do
not anticipate a significant moderating relationship between
promotion focus and salesperson hunting orientation under a
high acquisition-based compensation plan. Thus, we
hypothesize:
H7a: The relationship between salesperson promotion focus
and hunting orientation becomes stronger and positive
for low acquisition-based compensation plans.
Interaction effect between prevention focus and acquisition-
based compensation plans Following our previous discus-
sion, customer acquisitionbased compensation plans provide
a signal to salespeople that hunting activities are critical to
successfully achieving performance goals. Thus, high
acquisition-based compensation plans are likely to make hunt-
ing activities more extrinsically attractive to prevention-
focused salespeople who otherwise do not enjoy engaging in
such activities. Importantly, prevention-focused salespeople
tend to have a strong sense of vigilance of obligation for meet-
ing performance standards. That is, their concern for duty and
obligation enhances their sensitivity to negative outcomes,
such as not meeting minimum goals (Lanaj et al. 2012). The
external inducement of a high customer acquisitionbased
compensation plan should engender a prevention-focused
salespersons sense of vigilance to engage, at least temporarily,
in a different type of regulatory focus (i.e., promotion focus) to
avoid not meeting performance standards. Thus, we expect
high acquisition-based compensation plans to have a positive
moderating effect on the relationship between prevention focus
and hunting orientation. This again is in line with the strength
of the situation argument. In contrast, under low acquisition-
based compensation, such external motivation is less likely to
be experienced by prevention-focused salespeople, and there-
fore their prevention focus will dictate their disinclination for
hunting. Therefore, we expect a negative relationship between
prevention focus and a hunting orientation under a low
acquisition-based pay plans.
J. of the Acad. Mark. Sci.
H7b: The relationship between salesperson prevention focus
and hunting orientation becomes stronger (weaker) and
positive (negative) for high (low) acquisition-based
compensation plans.
Study procedures and sample
Study 3 participants were randomly selected from a nation-
wide panel of salespeople provided by a market research firm
that adheres to the ESOMAR International Code on Market
and Social Research. Participants were e-mailed an invitation
to the online study that included a brief description of the
study, a promise of anonymity, and a Web link to access the
survey. A filter question was used to exclude participants who
were not (1) responsible for both hunting and farming, (2)
quota-based, and (3) B2B sales executives responsible for
generating revenue. After 2 weeks of data collection, re-
sponses were garnered from 225 salespeople. Of these re-
sponses, we excluded 25 respondents who did not correctly
answer the quality check question, which was placed halfway
through the questionnaire (BFor quality purposes, please click
Poor-Extremely Lowfor this question^). The resulting sam-
ple involved 200 participants (73% female; 65.5% below
50 years of age), the majority of whom (74%) had some col-
lege education or higher. The sample composition is provided
in Appendix 3.
Measures
The measures for regulatory foci, hunting orientation, and
farming orientation were identical to the ones we used in
Study 2. We measured salesperson expected hunting success
by asking salespeople to rate their likelihood ofbeing success-
ful in hunting for new customers in the current quarter (1 = not
at all, 7 = very high). Acquisition-based compensation was
measured by asking salespeople to report the percentage of
their compensation that is based on hunting versus farming
activities and outcomes.
To address an alternative explanation that the relationship
between regulatory focus and salesperson hunting orientation
results from supervisorsselection, we added a three-item
scale to measure the supervisor selection. We also controlled
for (1) the time left in the current quota cycle (measured in
months), (2) quota achievement in the current quota cycle (%),
(3) firm market share (%), (4) competitive intensity (measured
with three items adapted from Jaworski and Kohli 1993), (5)
salesperson experience in sales, and (6) demographic vari-
ables. Information about these additional measures is avail-
able in Appendix 1. We report the correlation matrix and reli-
ability indices in the upper triangle in Table 3.
Measurement model
We validated the measurement model before estimating
the structural model. The results showed that the CFA
model exhibited good fit (CFI=0.94, RMSEA =0.07;
χ
2
=416.62, d.f. = 174, χ
2
/d.f. = 2.39; Bagozzi and Yi
2012). All the scales have an internal consistency reli-
ability index (Cronbach alpha) that is greater than 0.70.
In addition, all measures possessed AVE that was above
the recommended threshold of 0.50 and exhibited dis-
criminant validity based on Fornell and Larckers(1981)
recommendation to compare the squared correlation and
the AVE of each pair of constructs. We also adopted the
procedural and statistical remedies for common method
biases as we did in Study 2. We found that in the
principal components factor analysis that includes all
corresponding items without rotation, the highest vari-
ance explained by one factor is 27.5%. The paths coef-
ficients remain stable even when we include a common
method factor in the structural model. Therefore, we
concluded that these biases were not a major concern.
Furthermore, the focus of Study 3 is on interaction ef-
fects, making respondentshypothesis-guessing highly
unlikely. Podsakoff et al. (2012, p. 565) also note that
method bias can only deflate and not inflate quadratic
and interaction effects.
Results
Tab le 5provides the empirical results of Study 3. For each
dependent variable, we present the unstandardized coeffi-
cients from the main effects model first (the baseline model,
Model 4), and those from the full model second (Model 5).
Similar to Study 2, we allow for the residuals of hunting and
farming orientations to be correlated. In the main effects mod-
el, the effect of expected hunting success on salesperson hunt-
ing orientation is positive and significant (γ=0.323, p<0.01),
supporting H4. We also found support for H6, which predicts
a positive effect of acquisition-based compensation plans on
hunting orientation (γ=0.011, p< 0.01). Although not hypoth-
esized, we also found that expected hunting success does not
influence salesperson farming orientation at all, but
acquisition-based compensation plan does have a negative
effect on farming orientation (γ=0.01, p<0.05).
In the full model with interaction effects (Model 5), we
found support for the predicted interactions between expected
hunting success and regulatory focus. Specifically, the inter-
action between promotion focus and expected hunting success
is negative (β=0.333, p<0.05, H5a) while that between pre-
vention focus and expected hunting success is positive and
significant (β=0.233, p<0.01, H5b). The results also show a
significant interaction between regulatory focus and
acquisition-based compensation plans. Specifically, the
J. of the Acad. Mark. Sci.
interaction between promotion focus acquisition-based compen-
sation plans is negative (β=0.014, p<0.05, H7a) while that
between prevention focus and acquisition-based compensation
plansispositive(β=0.007, p<0.10, H7b). Thus, both H7a and
H7b are supported. As Table 5shows, the full model significant-
ly fits the data better than the main-effects only model.
Additional analysis
Industries as clusters In Study 3, individual responses are
from multiple industries and might be interdependent. How-
ever, we found no significant between-industry variance for
salesperson hunting orientation (χ
2
[d.f. = 20]= 24.79, n.s.),
but a significant, albeit very small (ICC1=0.02), between-
industry variance for salesperson farming orientation (total
variance= 0.97, between-industry variance=0.02, χ
2
[d.f. =
20]= 35.94, p<0.02). In comparison with the general thresh-
old in multilevel models (e.g., Schneider et al. 1998), this
between-industry variance is not considered a threat to our
findings. Nevertheless, as a robustness test, we retested the
hypotheses with a two-level model wherein level 1 included
all the individual responses nested within industries at level 2.
We found that the results remain robust as hypothesized.
Mediation or moderation Research in expectancy theory sug-
gests that salesperson traits can influence their evaluation of
expectancies (Teas 1981). We examine this possibility by
regressing expected hunting success on salesperson regulatory
focus. We found that both promotion focus and prevention
focus are unrelated to expected hunting success; therefore,
we can rule out this alternative model specification.
Additional covariates Prior research suggests that extraver-
sion might predict how comfortable salespeople are in
interacting with new versus existing customers (e.g., Barrick
and Mount 1991). Therefore, we included extraversion, mea-
sured with a four-item scale adapted from Donnellan et al.
(2006), as a covariate in predicting salesperson hunting and
Tabl e 5 Study 3: Empirical results
Dependent variables
Predictors Hunting orientation Farming orientation
Model 4 Model 5 Model 4 Model 5
Promotion focus (H1a) 0.136*(0.075) 2.880***(0.992) 0.002 (0.071) 0.632 (0.896)
Prevention focus (H1b) 0.106 (0.066) 1.573***(0.521) 0.237**(0.096) 0.979**(0.500)
Expected hunting success (H4a,b) 0.323***(0.068) 0.336***(0.066) 0.075 (0.065) 0.065 (0.050)
Acquisition-based compensation plan (H6a,b) 0.011***(0.004) 0.008**(0.004) 0.010** (0.004) 0.011***(0.003)
Promotion focus × Expected hunting success (H5a) 0.333**(0.155) 0.151 (0.132)
Prevention focus × Expected hunting success (H5b) 0.233*** (0.085) 0.116 (0.075)
Promotion focus × Acquisition-based comp. plan (H7a) 0.014**(0.006) 0.005 (0.010)
Prevention focus × Acquisition-based comp. plan (H7b) 0.007*(0.004) 0.004 (0.006)
Control variables
Manager and firm variable
Market share 0.001(0.003) 0.002 (0.003) 0.005*(0.003) 0.006**(0.002)
Supervisor selection 0.265** (0.118) 0.146 (0.117) 0.286***(0.098) 0.244** (0.101)
Competitive intensity 0.023 (0.087) 0.008 (0.080) 0.079 (0.082) 0.028 (0.060)
Salesperson variables
Time left in quota cycle 0.041 (0.026) 0.031 (0.027) 0.009 (0.020) 0.009 (0.018)
Quota achievement in the current quota cycle 0.003 (0.004) 0.003 (0.004) 0.001 (0.003) 0.002 (0.002)
Sales experience 0.028***(0.010) 0.027***(0.009) 0.001 (0.008) 0.001 (0.007)
Gender (1 = Female) 0.188 (0.202) 0.325*(0.179) 0.073 (0.150) 0.065 (0.143)
Age 0.076 (0.086) 0.040 (0.080) 0.113 (0.074) 0.129 (0.063)
Education 0.058 (0.085) 0.067 (0.077) 0.081 (0.057) 0.085 (0.055)
Model fit information Model 3: LL=6,302.90; AIC=12,797.82; BIC=13,114.46
Model 4: LL=6,285.85; AIC=12,779.71; BIC=13,122.73
Change in model fit: 2LL=34.10 (df=8, p<0.01)
*p<0.10, ** p<0.05, *** p<0.01. Unstandardized coefficients are reported with standard errors in parentheses. We report coefficients of the main-
effects only model first (Model 4), and the full model second (Model 5)
J. of the Acad. Mark. Sci.
farming orientation. This scale has a Cronbach alpha of 0.74.
There was no significant zero-order correlation between ex-
traversion and hunting orientation (ρ=0.083, n.s.)orfarming
orientation (ρ=0.13, n.s.). We also included extraversion in
our analysis and found no significant effect on either hunting
orientation (γ=0.143, s.e. = 0.140) or farming orientation
(γ=0.099, s.e. = 0.104).
Discussion
We plot the interactions associated with H5 and H7 in
Fig. 3. When salespeople have low expected hunting suc-
cess, the relationship between promotion focus and hunt-
ing orientation is significantly positive (Fig. 3, Panel A),
while prevention- focused salespeople become even less
likely to become hunting oriented (Panel B). In contrast,
when salespeople have high expectations about their
hunting success, the relationship between promotion focus
and hunting orientation is not significant whereas that be-
tween prevention focus and hunting orientation becomes
positive. Figure 3, Panel C, shows that when the firm does
not reward salespeople based on hunting, salesperson pro-
motion focus is highly predictive of salesperson hunting
orientation. In contrast, when the firm rewards salespeople
largely based on hunting, then a promotion focus is not
related to hunting orientation. Figure 3, Panel D suggests
that acquisition-based compensation plans are effective in
making prevention-focused salespeople become more
hunting oriented. The relationship between a prevention
focus and hunting orientation is downward when the firms
compensation plan does not place an emphasis on hunting.
Interestingly, the interaction pattern in H5a is similar to that
in H7a, and the interaction effect in H5b is similar to that in
H7b. This similarity has two implications. First, compensation
4
4.5
5
5.5
6
6.5
7
Low Promotion Focus High Promotion Focus
Hunting Orientation
Low Expected Hunting Success
High Expected Hunting Success
4
4.5
5
5.5
6
6.5
7
Low Prevention Focus Hi
g
h Prevention Focus
Hunting Orientation
Low Expected Hunting Success
High Expected Hunting Success
4
4.5
5
5.5
6
6.5
7
Low Promotion Focus High Promotion Focus
Hunting Orientation
Low Acquisition-Based Compensation
High Acquisition-Based Compensation
5
5.5
6
6.5
7
Low Prevention Focus High Prevention Focus
Hunting Orientation
Low Acquisition-Based Compensation
High Acquisition-Based Compensation
ac
bd
Fig. 3 Study 3: Interaction plots with hunting orientation as the dependent variable
J. of the Acad. Mark. Sci.
pay plans, an extrinsic firm-level factor, appears to be a sub-
stitute for expected hunting success, an individual factor, in
altering the effect of general regulatory focus (i.e., work-
related promotion and prevention focus) on situated regulato-
ry focus (i.e., hunting and farming orientations). Second, it
shows that expectancy theory and the strength of a powerful
situation (e.g., high expected hunting success, high
acquisition-focused compensation plans) is able to explain
the non-significant relationship between promotion focus
and hunting orientation in Panel A and C. In weaker situations
(e.g., low expected hunting success, low acquisition-focused
compensation plans), regulatory fit theory is at work to ex-
plain the positive effect of promotion focus on hunting orien-
tation. Finally, in the full model with interaction effects, the
main effect of supervisor selection, a control variable, is sig-
nificant and positive in predicting farming orientation. How-
ever, its relationship with hunting orientation is not signifi-
cant. We also found that market share is positively related to
farming orientation, whereas salesperson experience in sales
is positively related to hunting orientation.
General discussion
Discussions of salesperson hunting and farming activities are
commonplace among practitioners (e.g., Bowen 2012). A
reoccurring theme in such discussions is that salespeople often
over-focus on farming, which runs counter to firmsstrategic
imperatives on recruiting new customers. Yet, research has not
investigated why some salespeople prefer farming over hunting
and vice versa. Along these lines, research to this point has failed
to (1) theoretically develop and provide nomological evidence
of salespeoples customer engagement orientation, (2) elucidate
why salespeople prefer to engage in a particular type of custom-
er engagement when doing so may be contrary to firm objec-
tives, (3) understand how managers can align salespeoplescus-
tomer engagement orientation and strategic imperatives, and (4)
how to leverage salesperson ambidexterity when they enjoy
engaging with both existing and new customers to achieve sales
goals. Our research addresses these important gaps by examin-
ing antecedents and moderating factors that influence salesper-
son hunting and farming orientations. We next discuss the the-
oretical and managerial implications of our findings.
Summary of findings and theoretical implications
Salespeoples customer engagement orientation On the basis
of in-depth interviews and two empirical studies, we are the
first to propose two new constructs, salesperson hunting ori-
entation and farming orientation. We then integrate expectan-
cy theory and regulatory focus theory to show that the nomo-
logical validity of these constructs includes regulatory focus,
compensation plans, and expected hunting success as personal
and situational antecedents with profit margins as an
efficiency-based consequence. While prior research has pri-
marily focused on salesperson time allocation to hunting ac-
tivities and performance (Carter et al. 2014;Sabnisetal.
2013), our study sheds light on not only the antecedents but
also the situational factors that might alter salespeoplescus-
tomer engagement orientation. Our findings therefore contrib-
ute to the literature on salesperson orientation and more spe-
cifically to the emerging research on customer acquisition and
retention at the individual salesperson level of analysis.
Joint effects of customer engagement orientation on profit
margins Our research is the first to demonstrate the influence
of regulatory focus on both subjective (customer engagement
orientations) and objective (profit margins) salesperson per-
formance outcomes. We empirically demonstrate that in the
generalist sales organization model where salespeople have
discretion in how to allocate their effort on either existing or
new customers to achieve sales goals, a high farming orienta-
tion coupled with a low hunting orientation can be as subop-
timal in profit generation as a high hunting orientation com-
bined with a low farming orientation. On the surface, this
finding may seem somewhat counterintuitive vis-a-vis the
combination of low hunting orientation and low farming ori-
entation. However, regulatory fit theory provides the most
direct explanation. According to our model, a salesperson
low on both hunting and farming indicates s/he does not enjoy
doing either activity; therefore the person is ambivalent about
performing one activity over the other. As a result, it appears
that these salespeople will conduct a more profitable mix of
customer engagement activities than those that prefer farming
over hunting activities. While this finding may be unique to
the industrial distribution industry, our data lend support to the
notion that current customers may leverage the salesperson
relationship to extract greater discounts and less profitable
sales (e.g., Dwyer et al. 1987). In addition, our finding is also
consistent with Johnson and Selnes (2004),who found that the
key to increasing overall customer portfolio profitability lies
in the ability to successfully acquire new customers.
In contrast, high hunting and farming orientations signifi-
cantly increased profit margins. These results suggest that am-
bidextrous salespeople who are high on both hunting and
farming orientations are better able to achieve efficiencies in
managing their customer portfolio, as evidenced by higher
profit margins. Study 2 also demonstrated that ambidextrous
salespeople who are highly customer-oriented have the skills
to overcome the physical and mental constraints to produce
significantly greater profit margins.
Taken together, our results enrich the current understanding
of salesperson ambidexterity (e.g., Carter et al. 2014;Jasmand
et al. 2012) by examining the effect of both synergy (high
hunting, high farming) and tradeoffs (e.g., low hunting, high
farming and vice versa). Our focus on the profit impact of
J. of the Acad. Mark. Sci.
salesperson ambidexterity extends Carter et al.s(2014)focus
on factors that improve the top line effect (i.e., sales revenue)
of salesperson hunting time allocation. We also extend their
findings by demonstrating that customer-acquisition based
compensation plans and expected hunting success can tempo-
rarily change a salespersons hunting and farming orientation.
Our results also build on Jasmand et al.s(2012) findings that
show boundary spannersambidexterity in the form of selling
both products and services can reduce salesperson efficiency
for a specific customer. Our results indicate that efficiency
across a customer base can be achieved when salespeople
have the ability, that is, high on customer orientation, to deal
with varied demands from both new and existing customers.
Furthermore, our findings are the first to answer Lanaj
et al.s(2012) calls for research on the joint effects of these
two situated regulatory foci on work outcomes. Our findings
reveal that the interaction effect of regulatory foci is not nec-
essarily a cancelling effect wherein the existence of one regu-
latory focus weakens the effect of the other. Quite the contrary,
we show that a synergistic effect can be achieved if people
have the ability, or a slack of resource, to pursue both goals.
This finding is in line with prior research at the firm level on
how firms can pursue both exploration of building new capa-
bilities and knowledge, such as hunting for new customers in
our context, and exploitation of existing capabilities and
knowledge, such as farming existing customers in our context
(e.g., Kyriakopoulos and Moorman 2004;Vossetal.2008).
Identifying hunters and farmers in the salesforce We show
that all else equal, salespeople possessing a regulatory focus
involving promotion (prevention) hold relatively strong hunting
(farming) orientations toward new (existing) customers, which
in turn, affected profit margins. In providing such evidence, our
results document the usefulness of employing regulatory focus
to identify salespeople who are prone to adopt hunting or farm-
ing orientations, even after controlling for variables such as su-
pervisor selection, time left in the quota cycle, and the firms
market share. Given the widespread availability of valid mea-
sures of regulatory focus, this variable can easily be incorporated
into existing personality batteries used by companies in evalu-
ating the potential fit of an individual with firm sales objectives.
Firm-level antecedents of hunting and farming
orientation Results from Study 3 also suggest a high expec-
tation of hunting success does not reduce salesperson farming
orientation. In contrast, a customer acquisitionbased com-
pensation plan will gravitate salespeople to more hunting
and less farming. However, we also found that these factors
will also significantly disrupt the impact of regulatory focus
on salesperson customer engagement orientations.
In particular, compensation plans that emphasize customer
acquisition have a strong positive effect on high prevention-
focused salespeoples hunting orientation. This supports the
notion that high prevention-focused people are particularly
sensitive to fulfilling the requirements of their position and
avoiding the negative consequences for failing (Lanaj et al.
2012). As such, compensation can provide an important
boundary effect of regulatory focus in that, despite the a priori
preferences of prevention-focused salespeople for safer, less
risky activities (e.g., a farming orientation) may be over-
ridden by their motivations to engage in behaviors (e.g., hunt-
ing) that increase their probability of making quota. Our re-
sults also indicate that customer acquisition pay plans that fit
with a salespersons innate regulatory focus can have an alter-
ing effect on salesperson hunting orientation and farming ori-
entation. Theoretically, this result contributes to research that
suggests regulatory fit is associated with higher levels of mo-
tivation toward goal pursuit (Lanaj et al. 2012)bydemonstrat-
ing the influence of firm-level factors. Our study is the first, to
our knowledge, to examine how such expectations and com-
pensation plans can alter, yet under other situations fail to
disrupt, salesperson customer engagement orientations.
Managerial implications
In response to recent economic downturns and the ensuing
need for lean management, sales managers are likely to ask
their salesforces to be ambidextrous, that is, to engage in both
hunting and farming activities. In that regard, our research
offers useful insights for managers seeking to identify, allo-
cate, and balance hunting and farming efforts within the
salesforce.
Salesperson ambidexterity Findings from Study 2 extend pri-
or firm-level research suggesting inherent trade-offs in the
simultaneous pursuit of oppositional firm goals such as explo-
ration and exploitation (Voss et al. 2008). Our results suggest
that salespeople who pursue both hunting and farming are
actually more efficient: they able to generate higher profit
margins. Specifically, our findings showed at least a 3% in-
crease in profit margins associated with salespeople
possessing high farming and hunting orientations. This syner-
gy is even higher when salespeople are customer oriented. The
profit impact of ambidexterity is also surprisingly robust to the
specification of time. As mentioned earlier, when we
reestimated the empirical model with profit margins for each
of the 3 months after the survey instead of using an average of
3 months, the results are almost identical and supportive of our
hypothesis. This robustness further demonstrates that the ben-
efit of being ambidextrous can be sustainable.
Using situational factors to alter salespeoples customer en-
gagement orientation Our results also demonstrate the impor-
tance of understanding the influence of two situational factors,
expected hunting success and customer acquisitionbased com-
pensation plans. While high expected hunting success will
J. of the Acad. Mark. Sci.
enhance hunting orientation regardless of a salespersons regula-
tory focus, lowered expectations appear to significantly reduce
the relationship between prevention focus and hunting orienta-
tion (Fig. 3, Panels A and B). Thus, a manager who pursues a
customer acquisition strategy is cautioned to understand the po-
tential lack of fit, discouragement, and/or poor performance
prevention-focused salespeople may experience when they hold
pessimistic outlooks regarding the outcome of their hunting ac-
tivities. In contrast, sales managers can shift the selling orienta-
tions of prevention-focused salespeople who are inherent farmers
by shaping their perceptions of expected hunting success, thereby
promote the adoption of hunting orientations by such individuals.
Furthermore, management can affect salesperson customer en-
gagement orientations through the use of customer acquisition-
based compensation plans. In particular, salespeople who are
high in prevention focus can be Bmanaged^into becoming more
hunting-oriented through compensation plans that emphasize
customer acquisition given our results indicating that
prevention-focused salespeople who are farmers by design be-
come more hunting oriented in response to such plans. In con-
trast, highly promotion-focused salespeople tend to remain hunt-
ingorientedevenundercompensationschemesthatdonotpri-
marily reward customer acquisition (Fig. 3, Panels C and D).
These findings enable managers to better understand how com-
pensation affects the balance between customer acquisition and
retention at the individual salesperson during a quota cycle.
Implications for salesforce selection process The risks and
opportunity costs of hiring an unproductive salesperson can
be substantial. Accordingly, having assessment tools to place
employees into the proper sales positions is a critical impera-
tive in sales management. Given that general personality fac-
tors have been Bpoor to modest predictors of salesperson
performance^(Krishnan et al. 2002, p. 286), our findings
suggest an important role for employing measures assessing
regulatory focus as a basic personality trait of self-motivation
and hunting/farming orientation as a surface trait in salesper-
son customer strategies. Our findings inform managers to
match a salespersons regulatory focus and customer engage-
ment orientation with the appropriate sales position in order to
maximize salesperson and firm performance. Selecting sales-
people without relying on these important variables has the
potential to increase Bmisses^in salesforce deployment strat-
egies (as suggested by the nonsignificant effect of supervisor
selection on hunting orientation in Study 3).
Limitations and further research
Our work has some limitations. First, it can be argued that
there might be reverse causality between regulatory focus
and salesperson hunting and farming orientation. With cross-
sectional survey data, showing causality is difficult. Theoret-
ically, however, the causality should flow from more generic
measure of a trait (workplace regulatory focus as more basic
traits) to a more task-specific trait (hunting and farming orien-
tation as surface traits), and not the other way around. Never-
theless, further research with longitudinal data is needed to
empirically prove causality. Second, given that our analyses
were focused primarily at the salesperson level, future re-
search efforts emphasizing organizational-level factors using
a multilevel approach would seem warranted. For example, it
would be of interest to examine whether sales team effective-
ness and organizational strategic orientations is positively re-
lated to the extent to which various team members share a
common customer engagement orientation.
Third, on the antecedents side, we recognize that the mod-
erating role of other situational variables deserves further in-
vestigation. For example, it will be worthwhile to explore the
role of the qualifying processes, frequency of repeat purchase,
customer characteristics, cross-functional collaboration, CRM
technology, and firm-level market orientation on the relation-
ships between regulatory focus and the various sales outcomes
examined in the present investigation (e.g., Kyriakopoulos
and Moorman 2004; Sabnis et al. 2013).
Fourth, on the consequences side, we focus on the joint
effect of customer engagement orientations on profit margins.
While important, we have not examined the underlying pro-
cess, other outcomes, and other contextual factors. The fairly
moderate relationship between salesperson hunting and farm-
ing orientation and salespeoples actual time allocation sug-
gests it will be useful to examine the moderators thereof. Ad-
ditional work is needed to explore other outcome variables,
such as salesperson total profits, salesperson job attitude (e.g.,
when assigned to tasks that do not fit with their hunting/
farming orientation), and customer outcomes (e.g., breadth
of products purchased). Future research is also needed to ex-
amine if this joint effect on profit margins is more sensitive to
characteristics of the existing customer base, such as customer
power, transaction costs (see Carter et al. 2014)andtherela-
tive dependence of firms on hunting and farming activities.
For example, if a firm competes in an industry characterized
by a Bmarket exchange^customer base, then most accounts
would be considered new customers as compared with a com-
pany focusing on longer-term contractual arrangements. Thus,
we may see stronger emphasis on hunting and farming activ-
ities under these varying customer markets.
Finally, we encourage future research to extend our find-
ings using longitudinal designs or field experiments. These
research designs allow for a more dynamic examination of
salespeoples customer engagement orientation, such as se-
quential alternations between hunting and farming over time
(e.g., temporal sequencing of ambidexterity, Gupta et al.
2006) instead of a concurrent pursuit of hunting and farming.
It will also be interesting to examine the consequences of
salesperson ambidexterity in industries that require a longer
selling cycle.
J. of the Acad. Mark. Sci.
Appendix 1
Tabl e 6 Key measurement scales
Construct and measures Standardized
factor loadings
Study 2 Study 3
Hunting orientation (New scale, 7-point Likert, Strongly disagree = 1, strongly agree = 7)
To Bhunt^for a new sales opportunity is the most enjoyable part of the job. 0.86 0.81
I am at my best when I engage a new prospect that I have never met before. 0.87 0.80
I prefer to spend the majority of my day prospecting and closing new accounts. 0.84 0.76
The most enjoyable part of the job is selling to new accounts. 0.88 0.85
Farming orientation (New scale, 7-point Likert, Strongly disagree = 1, strongly agree = 7)
Spending time working with current customers is the most enjoyable part of the job. 0.77 0.75
My best attributes are my customer relations skills where I work for the best interests of my current customers. 0.75 0.82
The most gratifying is working with an established customer. 0.51 0.68
Of all my responsibilities, I most enjoy using my skills to maintain and grow existing accounts. 0.62 0.71
Customer orientation (adapted from Thomas et al. 2001, 7-point Likert, Strongly disagree = 1, strongly agree = 7)
I try to figure out what a customers needs are. 0.94 _
I have the customers best interests in mind. 0.91 _
I take a problem solving approach in selling products or services to customers. 0.93 _
I recommend products or services that are best suited to solving problems. 0.93 _
I try to find out which kinds of products or services would be most helpful to customers. 0.95 _
Promotion focus (adapted from Neubert et al. 2008; 7-point Likert, Strongly disagree = 1, strongly agree = 7)
I take chances at work to maximize my goals for advancement. 0.95 0.95
I tend to take risks at work in order to achieve success. 0.82 0.80
I focus on accomplishing job tasks that will further my advancement. 0.63 0.48
Prevention focus (adapted from Neubert et al. 2006; 7-point Likert, Strongly disagree = 1, strongly agree = 7)
At work I focus my attention on completing my assigned responsibilities. 0.74 0.92
I concentrate on completing my work tasks correctly to increase my job security. 0.94 0.87
Fulfilling my work duties is very important to me. 0.79 0.92
At work, I am often focused on accomplishing tasks that will support my need for security. 0.73 0.72
Supervisor selection Please rate your level of agreement with the following statements about your direct supervisor
(7-point Likert, Strongly disagree = 1, strongly agree = 7)
My supervisor assigned me to my current position because Im good at hunting for new customers. 0.73
My supervisor assigned me to my current position because Im good at farming existing customers. 0.69
My supervisor assigned me to my current position because Im good at both hunting and farming. 0.78
Expected hunting success: What is your expectation about your chance of being successful in hunting for more new
customers in the current quarter? 1 = No chance at all, 7 = Very high.
_a
Quota achieved in the current cycle: What is the percentage of quota that you have already obtained for the current annual
quota cycle?
_a
Months left in the current quota cycle: How many months are remaining in your current quota cycle? _a
Acquisition-based compensation plans: What is the percentage that your compensation plan that is based on the following
activities. Respondents then allocate 100% to hunting and farming activities.
_a
Company market share: What is the approximate market share of your company in the industry segment you work in? _a
a
single item. All factor loadings are significant at p<0.01
J. of the Acad. Mark. Sci.
Appendix 2
Appendix 3
Tabl e 8 Study 3: Sample composition
Industry % Number of employees at the firm % Annual revenue of the firm %
Advertising, Branding, and Marketing 6.5 <50 20.0 < $10 million 18.0
Apparel, Textiles, and Fashions 1.5 50100 15.5 $10 million$25 million 21.0
Automobiles and Trucks 1.0 100500 19.5 $25 million$50 million 12.5
Cellular Telephone and Telecommunications 2.0 5001,000 17.5 $50 million$100 million 14.0
Chemicals, Coatings, and Plastics 4.0 1,0005,000 12.5 $100 million$500 million 14.5
Computers, Internet, ECommerce, and InfoTech 8.5 >5,000 15.0 $500 million$1,000 million 7.0
Consulting, Outsourcing, and Offshoring 4.0 > $1,000 million 13.0
Construction 4.0
Education 2.0
Energy 4.5
Engineering 1.5
Entertainment and Media 2.5
Financial Services and Real Estate 12.0
Food, Beverages, and Tobacco 4.5
Government and Military 0
Health Care, Biotechnology, and Drugs 6.0
Job Seekers, Careers, and Employment 0.5
Retailing 8.0
Sports Industry 0.5
Transportation 3.5
Travel, Airlines, Hotels, and Tourism 2.0
Other 21.0
Tabl e 7 Moderated mediation test results with hunting orientation as mediator
Moderators Conditional indirect effect Bootstrap standard error Bootstrap 95% confidence interval
Farming orientation Customer orientation
0.77 1.08 0.03 0.12 [0.18, 0.33]
0.77 0.00 0.08 0.08 [0.25, 0.05]
0.77 0.64 0.15 0.09 [0.38, 0.01]
0.00 1.08 0.03 0.12 [0.19, 0.18]
0.00 0.00 0.04 0.05 [0.06, 0.16]
0.00 0.64 0.05 0.06 [0.09, 0.17]
0.77 1.08 0.03 0.18 [0.44, 0.19]
0.77 0.00 0.16 0.08 [0.03, 0.36]
0.77 0.64 0.24 0.12 [0.06, 0.48]
Variables are mean-centered. We used +1/1 SD about the mean as the high/low values for calculating the conditional indirect effect of hunting
orientation on profit margins. For each variable, zero represents the mean, a negative number represents a low value, and a positive number represents
a high value. Bootstrap = 1,000 runs
J. of the Acad. Mark. Sci.
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... This question is especially relevant for salespeople in B2B markets. A key stressor for B2B salespeople is potential rejection by customers (e.g., DeCarlo & Lam, 2016;Ingram, LaForge, Avila, Schwepker, & Williams, 2017;Verbeke, Bagozzi, van den Berg, Worm, & Belschak, 2016;Whiting, Donthu, & Baker, 2011). Such rejection is particularly likely during prospecting, that is, approaching and engaging with unknown potential customers (DeCarlo & Lam, 2016;Ingram et al., 2017;Verbeke & Bagozzi, 2000). ...
... A key stressor for B2B salespeople is potential rejection by customers (e.g., DeCarlo & Lam, 2016;Ingram, LaForge, Avila, Schwepker, & Williams, 2017;Verbeke, Bagozzi, van den Berg, Worm, & Belschak, 2016;Whiting, Donthu, & Baker, 2011). Such rejection is particularly likely during prospecting, that is, approaching and engaging with unknown potential customers (DeCarlo & Lam, 2016;Ingram et al., 2017;Verbeke & Bagozzi, 2000). Salespeople significantly differ in their reactions to potential rejection. ...
... Salespeople significantly differ in their reactions to potential rejection. For example, some salespeople actively seek new prospects while others avoid prospecting and instead focus on existing customers (DeCarlo & Lam, 2016). Further, while some salespeople thrive under pressure, others develop mental health issues like burnout (e.g., Habel, Alavi, & Linsenmayer, 2021;McFarland & Dixon, 2021). ...
... Importantly, although a number of studies are based on managers' views and perceptions (see, for example, Agyei, Manu, and Coffie 2022;Casidy and Lie 2023;Casidy and Yan 2022;Guo et al. 2018;Iyer et al. 2019;Jalkala and Keränen 2014), the related literature is silent on the question of what motivates managers to recommend specific positioning strategies and the motivational drivers of subsequent related decisions following contextual and market conditions. Understanding positioning decisions at the micro/individual manager level is important given that goal orientation is a central driver of managerial behaviors for both service firms (Yadav, Prabhu, and Chandy 2007) and those in the B2B domain (Brown, Locander, and Locander 2022;DeCarlo and Lam 2016;Robertson et al. 2019). Further, support for our view regarding the need to examine the effects of micro-level factor is provided by Kalafatis et al. (2020) whose study provides evidence of the relevance of managers' self-regulation in positioning-related deliberation. ...
... Consequently, situational factors, such as the organizational environment and job characteristics (e.g. Cron, Dubinsky, and Michaels 1988;DeCarlo and Lam 2016), interact and play a critical role in the formation of a salesperson's motivations. Applied to our setting, we derive key contingencies of a salesperson's motivation to put effort into maximizing profit through defending a firm's position in price negotiations by drawing on expectancy and instrumentality. ...