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Running head: CURVILINEAR EFFECTS OF REFLEXIVITY IN TEAM DECISION
MAKING
TEAM SUPPLY CHAIN MANAGEMENT DECISIONS
CURVILINEAR EFFECTS OF REFLEXIVITY AND REGULATORY FOCUS
MICHAÉLA SCHIPPERS
Rotterdam School of Management, Erasmus University
PO Box 1738, 3000 DR Rotterdam, The Netherlands
Email address: [email protected]
LAURENS ROOK
Faculty Technology, Policy and Management
Delft University of Technology
Email address: [email protected]
STEEF VAN DE VELDE
Rotterdam School of Management, Erasmus University
PO Box 1738, 3000 DR Rotterdam, The Netherlands
Email address: [email protected]
Author Note
Michaéla C. Schippers, Steef van de Velde, Rotterdam School of Management, Erasmus
University Rotterdam. Laurens Rook, Delft University of Technology. The authors wish to thank
Giles Hirst and Stefanie Protzner for their constructive comments on an earlier version of the
paper, and Jeremy Dawson for his statistical advice.
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TEAM SUPPLY CHAIN MANAGEMENT DECISIONS
CURVILINEAR EFFECTS OF REFLEXIVITY AND REGULATORY FOCUS
ABSTRACT
In the present study we explored how the team reflexivity and regulatory focus interact to
influence team performance in supply chain management decision making, using a sample of 258
people distributed over 81 teams playing a complex S&OP (Sales and Operations Planning)
business simulation. Our main finding is that high levels of reflexivity positively influence team
performance when teams are low on promotion and high on prevention. We further found that
low levels of reflexivity seem especially counterproductive for teams with a combination of low
promotion/high prevention focus, whereas moderate levels of reflexivity yielded moderate results
for all teams.
Keywords: team performance, team reflexivity, regulatory focus, sales & operations planning,
supply chain management.
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INTRODUCTION
Team decision making is essential for team performance and competitive advantage (De
Dreu, Nijstad, & van Knippenberg, 2008; Hollenbeck et al., 1995; Orasanu & Salas, 1993). A
growing body of research seeks to identify factors that are related to superior team decision
making and offset the process losses and biases inherent in group decision making (Kerr &
Tindale, 2004; Tindale, 1993; Tindale & Kameda, 2000). Unfortunately, group decisions are
often suboptimal (Kerr & Tindale, 2004), in many cases due to biased information processing
within teams (Schulz-Hardt, Frey, Lüthgens, & Moscovici, 2000). Organizations and researchers
therefore increasingly seek to understand the factors that enhance rather than impair the quality of
team information processing and subsequent decision making in various managerial settings. In
the present study, we focus on one of those managerial domains - supply chain management - and
attempt to improve our knowledge on how cognitive and motivational biases in group decision
making may influence supply chain management performance.
Supply chain management is concerned with the transformation of raw material into
distributive goods, and the delivery of those goods to consumers as quickly and cost-effectively
as possible (cf. Bowersox, Closs, & Stank, 1999). The critical supply chain decisions are
typically made in the so-called Sales and Operations Planning (S&OP) meeting (Oliva & Watson,
2009). This is a cross-functional team process, involving periodical meetings on a large number
of planning processes ranging from sales, marketing, new product launch, to manufacturing and
distribution. Based on detailed analysis of demand, demand forecasts, and supply and capacity
constraints, the outcome usually is a single executable plan in which demand and supply are
matched (Simchi-Levi, Kaminsky, & Simchi-Levi, 2003). Because of the sheer complexity of
supply chain management decisions in general and of the S&OP process in particular, there often
is a gap between the (mostly) mathematical models that could serve as guidance in the decision
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making process, and the rules of thumb that people tend to follow in practice (Bendoly, Donohue,
& Schultz, 2006). Prior research has in that respect highlighted the importance of information
processing skills of the various members within the supply chain for decision making outcomes
(Hult, Ketchen, & Slater, 2004). Others have called for the need to incorporate behavioral factors
in supply chain management decision making, but have so far limited their scope to individual
rather than team decision makers (Bendoly et al., 2006; Gino & Pisano, 2008). Given the
practical relevance of S&OP team decisions, it is therefore of key importance to combine these
two perspectives, and to gain more insight into the ways in which information processing skills of
the various members of decision making groups influences team supply chain management
decisions.
To foreshadow the theorizing developed in the present study, we maintain that the
behavioral factors 'team reflexivity' and 'regulatory focus' interact to influence S&OP decisions,
and hence team performance. Drawing from a motivated information processing perspective on
team decision making (De Dreu, 2007; De Dreu et al., 2008; Hinsz, Tindale, & Vollrath, 1997),
recent studies show that team reflexivity - i.e., the extent to which teams collectively reflect upon
their working methods and functioning - can trigger an information processing strategy, in which
the team consciously attempts to identify, discuss, and eventually diminish erroneous decisionmaking (Schippers, Edmondson, & West, 2011; Schippers & Homan, 2009; Schippers, West, &
Dawson, 2010).
However, this team process should also depend on the extent to which its individual
members are naturally inclined to engage in risky or conservative decision making. Along such
lines, a growing body of behavioral research points in the direction of regulatory focus - that is,
the extent to which people are predisposed towards a promotion focus (on risky decision making
aimed at achieving gains) or prevention focus (on vigilant decision making aimed at avoiding
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losses) (Bryant & Dunford, 2008; Förster, Higgins, & Bianco, 2003; Higgins, 1997). For the
present study, we therefore put forward that the extent to which teams set raw-material inventory
levels, develop capacity and production plans, and set end-product inventory levels is influenced
by the extent to which the team collectively engages in reflexivity, and the extent to which the
team members as a whole are focused on promotion or prevention. Reflexivity and regulatory
focus not only steer the extent to which a team sets inventory levels that are either too high or too
low -- or capacity and production plans that are either too tight or too slack, but also influence a
team's operating performance.
The current study makes the following contributions. First, it is one of the first to address
behavioral supply chain decision making at the team level, thereby covering new grounds in the
emerging field of behavioral operations management. Second, and related to this, it presents team
reflexivity as a novel key factor influencing the decision making process as well as the outcome
of team supply chain management decisions. Third, it expands existing research on team decision
making (De Dreu et al., 2008), team-situation interaction (Schippers et al., 2010) and regulatory
focus (Higgins, 1997; Higgins, 1998) by exploring (a) the relatively understudied topic how
motivational team composition can influence information processing and decision making at the
team level; and (b) the relationship between team reflexivity, team decision making and team
performance, and the way in which this relationship is moderated by a team's regulatory focus.
We start by giving insight in the context of the study, namely supply chain management.
HYPOTHESES DEVELOPMENT
Supply Chain Management
A supply chain is a network that transforms raw materials into distributed products.
Managing a supply chain involves complex activities to continuously balance supply and demand
between and within partnerships (Hult et al., 2004). Supply chain performance -- or the ability to
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balance supply and demand -- is strongly connected to operating and firm performance
(Hendricks & Singhal, 2003), and mismatches between supply and demand are known to destroy
shareholder wealth. For instance, failure to meet demand in a timely manner -- because of a lack
of end-product inventory -- may lead to higher costs due to express deliveries or overtime
production, or cause loss of revenues, reputation and credibility (Hendricks & Singhal, 2005a,
2005b). Excessive stocks, on the other hand, may among others lead to write-offs or extreme
inventory holding costs (Hendricks & Singhal, 2009). Supply chain management thus involves a
balancing act between the risk of understocking (carrying too little inventory) and the risk of
overstocking (carrying too much inventory). Importantly, when it comes to the management of a
supply chain, the key supply chain decisions are usually made in decision making groups rather
than by individuals (Hult et al., 2004). Given the complexity inherent to supply chain
management, those teams that manage the supply chain business process constantly face a huge
series of highly uncertain and variable decisions.
Typically, such decisions are made in a Sales and Operations Planning (S&OP) business
process, in which the team as a whole needs to come up with an executable sales and operations
plan to match supply and demand. This is a complex procedure, in which the decision making
team considers an array of supply chain management issues such as demand forecasting, product
development, promotions, supplier selection, raw material inventory planning, quality control,
and finished goods inventory planning (how much to stock). Arguably some of the more vital
decisions in this process concern raw material inventory planning, capacity and production
planning, and finished goods inventory planning. Inventory decisions involve the earlier
introduced balancing act between under- and overstocking that seems to be a defining feature of
supply chain management. That is, in setting raw material inventory levels, the trade-off is
between the risk not to be capable of producing due to stock-outs versus the risk of obsolescence
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and high inventory holding costs due to overstock. Capacity planning in that process refers to
such decisions as the number of machines and the number of shifts, whereas production planning
concerns what to produce when and by which quantities. Jointly, capacity and production
planning cover the production reliability within an S&OP business process - i.e., the extent to
which planned capacity and production are effective to meet demand from finished goods
inventory for a whole range of products in a certain period. Finally, the ultimate measure for
successful performance in this S&OP business process is simply financial - how many revenues
does the team generate in the end? Summarizing, the S&OP business process can be regarded as
a very complicated form of team decision making on a huge series of highly uncertain and
variable decisions. Next, we will discuss the role of team reflexivity in the S&OP decision
making process.
Reflexivity, Inventory Decisions, Production Reliability and Team Performance
Team reflexivity is defined as the extent to which group members overtly reflect upon,
and communicate about the group's objectives, strategies (e.g., decision-making) and processes
and make changes accordingly (e.g., communication; West, 2000). Recently, research has shown
that motivated information processing in the form of team reflexivity is of vital importance in
decision-making, largely because it can yield the motivation within a team to identify, discuss,
and eventually diminish errors and biases in team decision making (Schippers, Edmondson, &
West, 2011; Schippers & Homan, 2009; Schippers et al., 2010). The Motivated Information
Processing in Groups (MPIG) model (De Dreu et al., 2008) argues that decision quality and team
performance in cooperative groups benefit from epistemic motivation -- the willingness to
expend effort to gain an accurate and rich understanding of the world, including the team's task
and context. This may be especially true for certain teams, such as teams involved in highly
ambiguous tasks (De Dreu & Beersma, forthcoming). Building on the MIPG framework (De
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Dreu, 2007; De Dreu et al., 2008; Hinsz et al., 1997), we suggest that high quality team decisions
and subsequent improved (financial) performance is more likely to occur in teams that
consciously reflect on the decision making process and demands they face. The reason for this is
that such teams will process information regarding supply chain management decisions more
fully and accurately, increasing the chance that they will improve the quality of the decisions.
Consequently, these teams will improve their (financial) outcomes (West, 1996). Prior research
has indeed consistently found that reflexivity is positively related to subjective as well as
objective measures of team performance (Carter & West, 1998; Giles Hirst, Mann, Bain, PirolaMerlo, & Richter, 2004; Schippers, Den Hartog, Koopman, & Wienk, 2003; Somech, 2006;
Tjosvold, Tang, & West, 2004). For example, Carter and West (1998) found in a study among
nineteen BBC production teams that reflexivity predicted team effectiveness. Also, a study
among three-person experimental groups showed that teams in the reflexivity condition
performed better than teams in the control condition (Gurtner, Tschan, Semmer, & Nägele,
2007), whereas a field study among 59 work teams showed that team reflexivity mediated the
(moderated) relationship between diversity and team performance, commitment, and satisfaction
(Schippers et al., 2003). However, the mediating effects through which this effect on performance
occurs, has only recently received research attention, showing that a shared vision (Schippers,
Den Hartog, Koopman, & van Knippenberg, 2008), and shared task representations mediate (van
Ginkel, Tindale, & van Knippenberg, 2009) between team reflexivity and team performance.
Furthermore, team reflexivity has been shown to improve information elaboration and team
decision making (van Ginkel et al., 2009). However, the relationship between decision making
and team performance in a supply chain management context has received far less research
attention up to now. In the current research we propose that team reflexivity can have a positive
influence on the S&OP decision making process. To be precise, we hypothesize that team
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reflexivity is positively related to the quality of raw material inventory decisions, production
reliability (i.e. the operations process) and in turn to team performance. Furthermore, we propose
that both team decision making with respect to inventory level, as well as production reliability
mediate between team reflexivity and team performance.
Hypothesis 1. Team reflexivity is positively related to the quality of team raw material
inventory decisions, production reliability, and ultimately team performance.
Hypothesis 2. Raw material inventory decisions and production reliability both partially
and sequentially mediate team reflexivity and team performance.
Regulatory Focus as Moderator
Research into self-regulation is currently gaining momentum as a framework to
understand how intuition and cognitive heuristics influence decision-making processes
(Boekaerts, Maes, & Karoly, 2005) and organizational team behavior (Brockner & Higgins,
2001; Kark & Van Dijk, 2007; Neubert, Kacmar, Carlson, Chonko, & Roberts, 2008). According
to regulatory focus theory, people differ in their motivational orientation on self-regulation, and
in the realization of desired end-states (Higgins, 1997). Specifically, people can have a promotion
focus on advancement, growth and accomplishment, or a prevention focus on security, safety,
and responsibility (Crowe & Higgins, 1997; Higgins, 1998). Promotion-focused people over the
whole display risky processing styles in which gains, hits and successes are actively approached,
whereas prevention-focused people generally display a vigilant processing style in which losses,
errors and failures are actively avoided (Crowe & Higgins, 1997; Higgins, 1997; Higgins, 1998;
Liberman, Molden, Idson, & Higgins, 2001). Research has for instance shown that promotionfocused individuals generally make more speedy and less accurate decisions than preventionfocused individuals (Förster et al., 2003), and also more readily engage in more risky and
exploratory processing styles than prevention-focused individuals (Friedman & Förster, 2001).
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Furthermore, even though regulatory focus can be situationally induced, people can also can be
more promotion or prevention focused by inclination, and as a result of prior experiences in life
(Higgins & Silberman, 1998; Lockwood, Jordan, & Kunda, 2002).
Regulatory focus can also serve as an important moderator for the accuracy of team
performance in team supply chain management decisions. As stated in the introduction, the
typical S&OP supply chain business process confronts a decision making team with a large
number of uncertainties and variabilities. That is, the decision making team needs to develop a
sales and operations plan that specifies the purchasing of supplies, capacity planning (a
complicated series of decisions among others involving the number of shifts, overtime, scheduled
maintenance), production planning (what to produce when and by how much), and end-product
inventory planning (how much to stock). Building on the vast body of regulatory focus literature,
we expect that teams characterized by a high overall promotion focus will more strongly and
radically seek gains in novel opportunities in an S&OP supply chain business process - especially
when collective efforts are perceived as possibly yielding gains, whereas teams with a high
overall prevention focus will more likely act in vigilant and conservative fashion in an S&OP
supply chain business process - especially when collective efforts could possibly yield losses.
However, the precise way in which regulatory focus thus influences actual team performance in
this complex S&OP supply chain business process should also depend on the level of reflexivity
within the team. This observation is fueled by prior research that identifies reflexivity as a vital
factor for predicting performance for teams with complex jobs - that is, evaluating and reflecting
on non-routine tasks that involve high levels of uncertainty and variability seems to nurture team
performance under such circumstances (West, 1996).
Because reflexivity refers to the extent to which group members overtly reflect upon, and
communicate about the group's objectives, strategies and processes (West, Garrod, & Carletta,
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1997), it may render accessible especially those regulatory foci that are most salient within the
team before the team makes adaptations to their S&OP supply chain process. That is, a high level
of reflexivity within the team may cause the team as a whole to become aware of those
aspirations and collective goals that are dominant within the team. To be precise, it has been
widely documented that promotion and prevention focused people differ in the hopes and
aspirations that they wish to obtain: promotion-focused people typically strive for reaching a
positive (success) rather than a negative end-state (non-fulfillment), just as prevention-focused
people strive for reaching a positive (non-losses) rather than a negative end-state (losses)
(Molden, Lee, & Higgins, 2008). In a complicated S&OP team process, a high (vs. moderate or
low) level of reflexivity could specifically serve to facilitate the realization of these positive
rather than negative regulatory end-states, with the net result that the group remains focused on
those inventory decisions that contribute to the realization of the desired end-state of the team as
a whole - leading to good team performance. Moreover, because prior research has shown that
moderators on the reflexivity-performance relation can have non-linear effects and differ on low,
medium and high levels of reflexivity (Schippers, West, & Dawson, 2011), we specifically
predict a curvilinear interaction between reflexivity and regulatory focus on team performance.
The regulatory fit perspective would predict that team processes and regulatory focus will
combine to predict team outcomes. Given the nature of the S&OP business simulation that we
use in the current research - that is, the game requires participants to decrease the excessively
high stock levels (a default starting point of the game) -we propose that for teams with a low
promotion focus, a U-shaped relation is expected with high reflexivity, while for teams with a
high promotion focus an inverted U-shape will occur, that will likely be negative especially when
combined with high reflexivity. That is, such teams will use reflexivity to strengthen their initial
idea that they should "go for it" instead of lowering their raw material inventory level. For
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prevention focus, the exact opposite holds: when prevention is high, we predict that a U-shape
relationship will exist between reflexivity and performance, whereas we expect an inverted Ushape relationship for low prevention focus. Although empirical tests are lacking, several authors
have indeed suggested that that team reflexivity may strengthen initially held beliefs, even if
those are wrong, as long as they are shared between team members (Tindale & Kameda, 2000;
van Ginkel et al., 2009). We thus hypothesize:
Hypothesis 3: The performance of teams with a high promotion focus will increase when
reflexivity is moderate, but will decrease when reflexivity is high, whereas the
performance of teams with a low promotion focus will decrease when reflexivity is
moderate, but increase when reflexivity is high.
Hypothesis 4: The performance of teams with a high prevention focus will decrease when
reflexivity is moderate, but will increase when reflexivity is high, whereas the
performance of teams with a low prevention focus will increase when reflexivity is
moderate, but decrease when reflexivity is high.
A core principle of chronic regulatory focus is that essentially four combinations of
regulatory foci are possible: (1) high promotion/ high prevention focus, (2) high promotion/low
prevention focus, (3) low promotion/high prevention focus, and (4) low promotion/high
prevention focus (Lockwood et al., 2002). To the best of our knowledge, the combination of the
two regulatory foci in teams has never been investigated before, but in line with the argument
developed above, it seems likely that these four combinations of regulatory focus within the team
will have different effects on the way in which teams reflect upon information and make
subsequent decisions in their collective S&OP process. That is, reflexivity will strengthen the
benefits inherent to regulatory foci only if the desired end-states for those two foci are in line
with the task demands within the S&OP game. To be precise, when both the promotion and
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prevention focus are high within the team, the level of reflexivity will be unrelated to
performance, because the desired end states (reaching success vs. avoiding losses) associated
with the two foci have similar consequences. Likewise, when both the promotion and prevention
focus are within the team, high and low levels of reflexivity will be ineffective, while at moderate
levels of reflexivity performance will be moderate. Also, when promotion is high within the
team, but prevention focus is low, the effect of reflexivity will again be unrelated to performance,
largely because the dominant desired end-state itself (reaching success) will drive the decision
making process within the team. But, when promotion is low within the team and prevention
high, reflexivity can reinforce team performance, because then the team will engage in thoughtful
and careful decision regarding inventory level and (financial) performance -especially at high
levels of reflexivity.
We propose that high reflexivity will show a U-shaped relationship with performance for
teams with a combination of high prevention focus and low promotion focus. Such teams will be
inclined to decrease their raw material inventory levels and thus improve performance, especially
at high levels of team reflexivity, while at medium reflexivity a slight decrease in performance
will occur. For teams low on both foci, an inverted U-shape relationship is expected, such that
we would expect that both low and high levels of reflexivity are negatively related to team
performance, with a slight increase at medium levels of reflexivity. For promotion focus, we
expect to find the opposite patterns. The above described relations will be opposite when raw
material inventory level is taken as the dependent variable. This leads to the following
hypotheses:
Hypothesis 5: Regulatory focus moderates the relationship between team reflexivity and
team performance in such a way that for teams low on promotion/high on prevention, this
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relationship follows a U-shape, whereas the reversed pattern exists for teams low on
promotion/low on prevention.
Hypothesis 6: Regulatory focus moderates the relationship between raw material
inventory level and team performance in such a way that for teams low on promotion/high
on prevention, this relationship follows an inverted U-shape, whereas the reversed
pattern exists for teams low on promotion/low on prevention.
Hypothesis 7: Regulatory focus moderates the relationship between team reflexivity and
raw material inventory decisions, in such a way that for teams low on promotion/high on
prevention, this relationship follows an inverted U-shape, whereas the reversed pattern
exists for teams low on promotion/low on prevention.
METHOD
Participants and procedure
The initial sample consisted of a total of 376 people distributed over 94 four-person teams
who participated in an S&OP (Sales and Operations Planning) supply chain business simulation
(see below). Participants were professionals with direct or indirect experience in supply chain
management, including general managers, operational managers, commercial managers, financial
managers, logistics managers, supply chain managers, planners, purchasing managers, transport
managers, warehouse managers, production managers, and marketing/sales managers. Their main
motivation to participate in the game was to learn. Participation was completely voluntary. Those
teams that participated received feedback on their team level scores and on the meaning of their
measures. The participants had to pay a participation fee to the company that developed, ran and
supported the simulation game. The response rate for the online survey was 83% (258 persons
from 82 teams). One team was excluded from further analysis, because they never finished the
game and thus did not receive end-scores on the dependent variables. This resulted in a final
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sample that consisted of 254 persons from 81 teams. Of these respondents, 76.4% was male and
the average age was 33.7 years (SD = 9.42). 81.5% of the respondents had the Dutch nationality,
the remaining respondents had American (18.5%) nationality; 39.8% held, at least, a bachelor's
degree and 2.7% had earned an additional advanced degree or professional qualification.
Task
Work simulations in the form of management games are frequently used in organizations
for development purposes of managerial talent as they offer participants meaningful feedback to
improve their work-related behavior and skills (Anseel, Lievens, & Schollaert, 2009; Seijts,
Latham, Tasa, & Latham, 2004; Thornton & Cleveland, 1990). The game used here was called
the Fresh Connection Game and included an interactive, computer-based simulation based on
events in the production and supply of fresh juices to customers. In this realistic S&OP supply
chain business simulation, a decision making team considers issues such as its sales and
operations plan regarding the purchasing of supplies, capacity planning (a complicated series of
decisions among others involving the number of shifts, overtime, scheduled maintenance),
production planning (what to produce when and by how much), and inventory planning (how
much to stock). In this particular case, the team was divided into four roles: a supply chain vicepresident (responsible for supply chain strategy and control decisions), a purchasing vicepresident (responsible for the choice of suppliers, supplier agreements etc.), an operations vicepresident (concentrating on the organization of operations and the warehouse), and a sales vicepresident (responsible for decisions on customer service, the priorities of orders, and promotional
activities).
Care was taken to ensure the realism of the simulation, including role descriptions,
background information, graphics, pictures, e-mail simulation, organizational charts, and
interactive activities. The game itself took place in seven decision periods of one week each,
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where one week supposedly represented half a year in real life. During a first trial round, teams
were able to familiarize themselves with the game (and the performance in this round was not
included in the final results), and then the real competition started. The competition itself lasted
six weeks. The team that scored the highest return on investment (ROI) after those six weeks won
the game.
As to the design of The Fresh Connection, the simulation started with a video message
from the CEO, who gave general information about the company - a fruit-juice maker active in
the production and supply of fresh juices to customers - and its challenges and who stressed the
urgency to improve supply chain operations. The evolution of this company in the simulation was
predetermined. That is, in the first period, teams were informed that things were not going well at
all for the fruit-juice maker, evidenced by excessive stocks, substantial losses, dissatisfied
customers, and disgruntled suppliers. The teams had to evaluate a considerable number of
strategies for addressing the several supply chain problems in order to steer the company through
this phase. In the course of the game, the teams received e-mail messages about new
opportunities and upcoming events, such as new customers, or the introduction of a new product.
For instance, in the second period, a new product was introduced in the form of PET bottles. This
element was introduced to create another potential supply chain dilemma: the inventory of these
bottles was very costly (because these bottles were more spacious than the carton containers), and
would cause problems in later stages of the game. Not all emails were sent to all team members;
Like in reality, the team members had proprietary information. In the fifth and sixth period,
participants were increasingly confronted with the growing complexities of the supply chain, and
proper management of the various uncertainties and variabilities became a principal challenge.
Following each decision period, the teams received feedback about their results, and how their
team performance was related to the other teams participating in the game. Those eight teams that
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received the highest scores after the seventh period were invited to play the final period in a
separate event on one location.
This task was used for three reasons. First, management games are frequently used for
learning and development purposes, because they offer participants a high degree of component,
dynamic and coordinative complexity (Anseel et al., 2009; Thornton & Cleveland, 1990; see also
Seijts et al., 2004, for a similar argument). Second, the task complexity and the interplay between
and cooperation of the team members in the simulation game would most likely yield behavioral
differences between teams as a function of team reflexivity and regulatory focus. Third, the
simulation was highly realistic, related to actual work settings. The game was challenging even
for people working in this area1.
Measures
Team performance. Performance was assessed by the team score of return on investment
(ROI) of the company, a weighted average of the score, where the last two rounds were most
important in determining the final score for the team by the game provider. The scores on ROI
varied from -.46 to .17, M = .034, SD = .11.
Inventory decisions. Team decision making regarding inventory level was measured as
the amount of raw product the teams had in stock. In general, a high stock level was bad for
performance. Overstocking was more of an issue than understocking, since at default the
inventory level was too high before the game started. The score used here is also the weighted
average used by the game provider in determining the highest scoring teams. The scores on
inventory level varied from 1.92 to 8.10, M = 3.75, SD = 1.10.
Production reliability. The extent to which teams maintained a good production reliability
(i.e. operations) was also measured by the weighted score used by the game provider. This
weighted scores varied from .10 to 1.0, M = .62, SD = .25.
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Reflexivity. Reflexivity was measured using a five-item scale from the reflexivity measure
of Schippers et al., 2007, adapted to fit the game context. Example items are: "During the game,
we stopped to assess whether the team was on the right track," and "We reflected on what we
could learn from prior decisions we made" (1 = strongly disagree, 5 = strongly agree).
Regulatory focus. Regulatory focus was measured using a 6-item version of the scale of
Lockwood et al. (2002). Promotion focus was measured using three items: "Overall, I am more
oriented toward achieving success than preventing failure", "In general, I am focused on
achieving positive outcomes in my life", and "I see myself as someone who is primarily striving
to reach my "ideal self" - to fulfill my hopes, wishes, and aspirations." (1 = strongly disagree, 5 =
strongly agree). Prevention focus was measured using three items: "I am more oriented toward
preventing losses than I am toward achieving gains", "I frequently think about how I can prevent
failures in my life", "I see myself as someone who is primarily striving to become the self I
"ought" to be - to fulfill my duties, responsibilities, and obligations"(1 = strongly disagree, 5 =
strongly agree).
Control variables. Since all groups consisted of four team members, there was no need to
control for group size. We entered several control variables in different sets, in order not to lose
too much power. We controlled for age, gender, supply chain management knowledge,
experience in playing management simulations, hours per week spent on the game, and
familiarity -- i.e., how well the team members knew each other before the start of the game. We
also controlled for the standard deviation of promotion and prevention focus. None of these
variables changed our pattern of results. We therefore proceeded to test our hypotheses without
these variables in order to preserve degrees of freedom and to minimize the chances for a Type I
error.
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Response bias. To check for a possible response bias, we performed t-tests on the two
dependent variables, raw material inventory level and ROI. These tests revealed no differences in
inventory level (t = -1.12, ns) and production reliability (t = -0.02, ns). However, a significant
difference was found between the participating teams and the teams that did not fill out the
questionnaire. The non-participating teams scored significantly lower than the participating teams
on team performance, ROI (t = 5.46, p < .001). According to the game provider, this was due to
motivation: All teams received weekly feedback on their scores and relative standing, and teams
with a low score were probably less motivated to fill out a questionnaire. Although this
significant difference may point to a response bias, we firmly believe that it does not speak
against our findings: with lower scoring teams excluded from the analysis, the variance in ROI in
our sample is limited to medium and higher scoring teams only. This effect may have reduced
rather than enhanced our power for detecting significant relationships. It stands therefore to
reason that this difference has led to a more conservative test of our hypotheses.
RESULTS
Confirmatory factor analysis and level of analysis
In order to test whether a three-factor model gives a parsimonious fit of our model, we
conducted confirmatory factor analyses. We ran CFA analyses including the independent
variables we measured with our questionnaire (promotion focus, prevention focus, and
reflexivity) as separate factors. This procedure produced the following fit indices: Chi-square =
85.42, df = 41, CFI=.95, AGFI=.91, RMSEA =.061, CI lower 90%=.43, CI upper 90% =.63. In
the next step we loaded the three variables onto one construct. This procedure produced the
following fit indices: Chi-square = 176.36, df = 44, CFI=.86, RMSEA =.11, CI lower 90%=.093,
CI upper 90% =.13. Thus our three-factor model was a superior fit to the data.
20
With respect to our level of analysis, for reflexivity, the ICC and rwg(j) values (see Table 1)
indicate that this is a team level construct, and was therefore aggregated to the team level. The
ICC values of promotion and prevention focus indicate that these are individual level (below .12),
while the rwg(j) values point in the team level direction. Prior research indicates that the
theoretically appropriate operationalization of personality variables depends on the team task
(e.g.,Barrick, Stewart, Neubert, & Mount, 1998; Homan et al., 2008; LePine, 2003), and
following these authors’ recommendations, we examined the nature of the task to determine how
regulatory focus should be aggregated to the group level. This aggregation procedure is rooted in
the theoretical work of Steiner, 1966; Steiner, 1972, distinguishing between disjunctive,
conjunctive, and additive tasks. Of these three task categories, the additive model best represents
the team task used in our study (for a full description of the task, see method section). Each
member could access a certain set of information common to all team members; however, he or
she also had knowledge of certain aspects of the task that were specific to his or her role; that is,
team member could choose to share specific information with other team members (which almost
all teams did), team members had an equal level of responsibility and an equal share of input into
the team’s output. This additive task is fundamentally different from a disjunctive task, such as
problem solving, where the team’s best member determines the output of the team. It is also
different from a conjunctive task (e.g., mountain climbing), where the team’s weakest member
determines the team’s output. Summarizing, if a team was to perform at a high level, all team
members had to interact with each other, exchange information, and make decisions accordingly.
Thus, in light of the additive nature of the task, we used the average (i.e. the mean; see also
Barrick et al., 1998) of the team member’s scores to represent regulatory focus at the team level.
As mentioned earlier, controlling for the aggregated standard deviation of regulatory focus did
not change our pattern of results.
21
Descriptive Statistics
As can be seen in Table 1, reflexivity was negatively related to inventory decisions (r =
-.30; p < .01); positively to production reliability (r = .33, p< .01), promotion focus (r = .36, p <
.01) and team performance (ROI, r = .40, p < .001), and unrelated to prevention focus ((r = .10,
ns). Inventory decisions were negatively related to production reliability (r = -.41, p < .001) and
team performance (r = -.47, p < .001), confirming the idea that for this simulation high inventory
levels were detrimental for team performance, and that reflexive teams would have lower stock
levels. Promotion focus was positively related to team performance (r = .25, p < .05), while there
was a slight but insignificant positive relationship between team level prevention focus and team
performance.
Hypotheses Testing
Hypotheses 1 and 2 predicted direct and mediating relationships. We tested these
relationships through a series of regression analyses (see below). We expected to find a main
effect of team reflexivity on team performance (Hypothesis 1). In addition, we predicted a
number of mediational effects between team reflexivity and team performance of inventory
decisions and production reliability (Hypothesis 2). To examine the sequential mediating roles of
decision making and production reliability in the relationship between team reflexivity and team
performance, three steps were followed, in line with the suggestions of Baron and Kenny (1986).
First, we should demonstrate that there is a relationship between the antecedent and the
consequence. A series of regression analyses showed significant relationships (see Figure 1). As
predicted by Hypothesis 1, a relationship between team reflexivity and production reliability was
found (β = .33, p < .01), as well as a relationship between team reflexivity and team performance
(β = .40, p = .001). Second, the relationship between the antecedent and the mediator should be
significant, as well as the relationship between the mediator and the consequence. A relationship
22
between team reflexivity and inventory decisions was indeed found (β = -.30, p < .01), as well as
a relationship between inventory decisions and production reliability (β = -.41, p < .001).
Furthermore, the mediator inventory level was positively related to team performance reflexivity,
and the mediator production reliability was positively related to team performance (see Figure 1).
Finally, the unique impact of the mediators (inventory decisions and production
reliability) should be demonstrated. In line with this, our hierarchical regression analysis revealed
that the betas of the simple main effects declined when inventory decisions was added to the
equation (change in β from .40 to .23), supporting Hypothesis 2. Moreover, the beta values also
declined and became non-significant when production reliability was added in the last step
(change in β from .40 to .20; see Figure 2), corroborating Hypothesis 3. When production
reliability was added to the equation, the relation between inventory decisions and team
performance also declined (change in β from -47 to -.39. With respect to performance, we
expected a partial mediational effect, as other variables besides these were also expected to
influence team performance (see below for the test of the full model).
We then performed Sobel tests in order to assess whether the decreases in the β 's of the
hypothesized mediation models are significant (Goodman, 1960). For the relationship reflexivity
- decision making - production reliability, the z-value was 2.11, p < .05. For the relationship
decision making - production reliability - team performance the z-value was 2.49, p < .05. For the
complete meditational chain reflexivity - decision making - production reliability - team
performance the z-value was 1.92, p = .06.
Our results thus suggest that team reflexivity is related to better decision making (lower
inventory level) in teams, which is in turn related to increased production reliability. This is
ultimately related to enhanced team performance (ROI) as proposed in Hypothesis 2, although
the z-value for the complete chain was marginally significant.
23
Interactive Effects
Before testing our predicted interactions, all continuous independent variables where
mean-centered (Aiken & West, 1991). Hypothesis 3 predicted quadratic interactions between
reflexivity, regulatory focus and team performance. Hierarchical regressions showed that besides
the above tested main and mediating effects, the predicted curvilinear two-way interactions
explained additional variance; β = .48, p < .01 for the reflexivity squared x prevention focus
interaction and β = -.42, p < .01 for the reflexivity squared x promotion focus interaction. These
findings showed a U-curve for high prevention focus and an inverted U-curve for low prevention
focus. For promotion focus the relation was reversed; a slight inverted U-curve for high
promotion focus and a slight U-curve for low promotion focus, while the two curves cross
towards high reflexivity (see Figure 3 and 4). In general, these findings indicate that high
reflexivity, high prevention focus and high promotion focus are most beneficial for performance.
Hypothesis 4 predicted quadratic interactions between reflexivity, regulatory focus and
team performance, as well as between inventory level decision making, regulatory focus and
team performance. Hierarchical regressions showed that besides the abovementioned main,
mediating effects and two-way interactions, the predicted curvilinear three-way interactions
explained additional variance (β = -.44, p < .01) for the reflexivity squared*promotion*
prevention focus interaction; (β = -.53, p < .01) for the inventory level squared*promotion*
prevention focus interaction.
The findings indicate that there are three kinds of combinations lead to better or worse
team performance. First, the findings suggest that all teams benefit equally from a moderate level
of reflexivity, all lines converge at moderate level (see Figure 4, 5 and 6). The teams that have the
highest score on team performance are the teams that have a combination of low promotion/ high
prevention/ high reflexivity. This suggests that reflexivity is better than just "go for it" as implied
24
by a high promotion focus. The combination of trying to prevent losses, while at the same time
being highly reflexive, helps teams to gain a high ROI as indicator of team performance. The
complimentary quadratic three-way interactions with dependent variable inventory level, showed
that such teams indeed have a lower inventory level, which may have contributed to this high
score, since lower inventory levels were in general related to higher performance (β = .57, p <
.05); see Table 3 and Figure 7. As predicted, the lowest scores were achieved by teams with a
combination of low prevention, low promotion, and low reflexivity. As can be seen in the
complimentary 3-way interaction with inventory level as dependent variable, those teams had a
relatively high inventory level. Interestingly, they also had a high inventory level at a high level
of reflexivity, as opposed to a medium level of reflexivity. Middle of the road seemed to be teams
with a combination of high promotion/high prevention, or a combination of high promotion/low
prevention. Those teams had an average result regardless of level of reflexivity. The three-way
interaction with inventory level as independent variable and team performance as dependent
variable showed that those teams do get a relatively good performance at high level of inventory.
DISCUSSION
Theoretical Implications
We proposed that team reflexivity and regulatory focus influence performance in Sales
and Operations Planning (S&OP) decision making, and that inventory, capacity and production
planning decisions would mediate this relationship. In the present study, we tested and found
these mediating effects, and also showed that team reflexivity and regulatory focus in interaction
influence inventory decisions and return on investment (ROI) to the extent that the right fit
between reflexivity and regulatory focus can positively boost a team’s decision making and
performance.
25
The main contribution of our research lies in the fact that we show the viability of a
behavioral approach to supply chain management at the team level. Our main findings clearly
indicate that people in S&OP processes are influenced by cognitive-motivational factors that can
make or break their performance in terms of ROI. This is consistent with a growing awareness in
the field that behavioral biases are critical to people’s decision making and performance in
operations management (e.g., Gino & Pisano, 2008). Moreover, our study offers confirmation for
an earlier observation by Bendoly and colleagues (2006) that behavioral issues in the field of
operations management are especially likely to arise in supply chain management practices, in
which task requirements “involve reliance on multiple parties across different organizations, with
different perspectives, capabilities, objectives, and information availability” (p. 749). In our study
we directly tackled this issue by showing for decision making teams in a stylized S&OP
constellation that the information processing skills of team members, together with their joint foci
on promotion or prevention, influence team supply chain management decisions.
Second, and related to the above, the present study points to the importance of team
reflexivity as a factor influencing the outcome of team supply chain management decisions. We
found that reflexivity -- together with regulatory focus – exerts an influence on team performance
in an S&OP setting, in which the team as a whole needs to produce a feasible sales and
operations plan to match supply and demand. That is, high levels of reflexivity positively
influence team performance when teams are low on promotion and high on prevention, and low
levels of reflexivity negatively influence team performance when teams are low on promotion
and prevention focus. Of particular relevance to operations management research is our finding
that team reflexivity is not always linearly related to team performance, but may be stronger for
teams with a regulatory focus that fits the team context. This extends earlier work of Schippers et
al., 2010, in showing that team reflexivity is not always linearly and positively related to team
26
performance, but also adds further evidence for the role of team reflexivity in team decision and
performance (West, 1996; see also Schippers, Den Hartog, & Koopman, 2007), thus highlighting
reflexivity as a useful framework to guide theoretical development in the area of behavioral
operations management.
In related fashion, the present research expands prior research on team decision making
(De Dreu et al., 2008) and regulatory focus (Higgins, 1997, 1998) by exploring how the
composition of a team in terms of underlying motivational focus can influence the willingness of
individual team members to processing information and make decisions. Up till now, the role of
individual differences in regulatory focus for team decision making and performance in general
had often been theoretically assumed (cf., Higgins, 2000), but hardly been put to the test.
Importantly, in the present study we did so, and found that the effects of team reflexivity are
moderated by regulatory focus within the team context. Our results suggest that both the team
context and regulatory focus are boundary conditions for the relationship between team
reflexivity and team performance in general and in the specific S&OP setting. In doing so, we
extend the literatures on team reflexivity, regulatory focus and behavioral operations
management.
Managerial Implications
Practitioners and the popular press have focused on team learning and reflection as a
panacea for team decision making and performance (Boud, Keogh, & Walker, 1985; Gray, 2007;
Senge, 1990), and up to a point our analysis corroborates this conclusion. The relationships
observed in our study are complex, but in short they do place a premium on team reflexivity in
promoting team decision making and performance. Our analysis also provided two important
qualifications to this conclusion however.
27
First we show that this relationship is highly dependent on the combination of regulatory
foci in teams. It is the combination of team reflexivity, regulatory focus as well as the decision
making context that determine the quality of the decision making process and performance
(Stam, van Knippenberg, & Wisse, 2010). An emphasis on reflexivity to enhance team
performance should therefore be combined with the regulatory focus that fits the team context.
On the individual level, this could include the consideration of regulatory focus in personnel
selection and in investing in employee development programs that build employees' tendency to
reflect on work-related issues, for instance through team leadership promoting team reflexivity
(Schippers et al., 2008)
Second, as return on investment and inventory levels are crucial in supply chain
management, and in general to the organizations' quest for competitive advantage, factors
contributing to the optimizing of factors that hinder or foster team work in this respect are
important. The current study highlights the crucial interacting role of regulatory focus on the
team reflexivity - decision making/performance relationship, thereby emphasizing the role of
team level disposition and team process in interaction with the team context. It is the combination
of team level regulatory focus, team processes and the decision making context that yields the
stronger association with team level (financial) performance. However, reflexivity may also be
time-consuming, and especially for high performing teams, it can be questioned whether the
investment is always worth the pay-off (Bunderson & Sutcliffe, 2003; Schippers et al. , 2009).
The present findings suggest that a targeted use of reflexivity may be effective - particularly
when teams face an environment that calls for a prevention focus (i.e. too high stock levels) in
combination with a high prevention focus and a low promotion focus. An important management
implication could thus be that teams facing conditions that call for a prevention focus, should be
trained to be reflexive while at the same time a prevention focus could be induced in such teams.
28
Whether at the same time a low promotion focus can be induced is an important avenue for future
research.
LIMITATIONS AND FUTURE RESEARCH
An important strength of the current research lies in the fact that we used objective
measures for decision-making and performance (ROI) that were the same across all teams.
However, we did not directly measure those mechanisms that could be held accountable for
linking reflexivity to team decision making and performance – in other words, we do not know
what was actually discussed in those teams. Future research could more directly tap into those
team dynamics with the help of video recordings of team interaction processes, and the coding of
these recordings (Weingart, 1997). Furthermore, in our research we examined chronic
differences in people’s regulatory focus, while research in laboratory settings has shown that
regulatory focus can also be situationally induced by framing situations in terms of gains (for
promotion) or losses (for prevention) (e.g., Cropanzano, Paddock, Rupp, Bagger, & Baldwin,
2008; Crowe & Higgins, 1997; Friedman & Förster, 2001). However, little is known about how
to influence regulatory focus at the team level, and for a prolonged period of time in a field
setting, rather than a short-lived manipulation in a lab context. Therefore an important avenue for
future research would be to more thoroughly explore those contextual factors or managerial
practices that may trigger a team focus on promotion or prevention depending on the decision
making context (Avnet & Higgins, 2007; Zhou, Hirst, & Shipton, 2010). Also, we need not limit
the scope of our attention to differences in regulatory focus alone: we may further advance our
understanding of the S&OP team process by also considering other promising personality
differences that have shown to relate to team performance, such as learning versus performance
orientation (Hirst, van Knippenberg, & Zhou, 2009; LePine, 2005; Porter, 2005). Finally, because
our teams did not have a formal leader, we could not delve into the issue what sort of leadership
29
can possibly boost or hamper team reflexivity in S&OP setting. For instance, the precise role of a
leader in triggering a promotion focus or a prevention focus among their team members could not
be assessed (Kark & Van Dijk, 2007; Stam, Knippenberg, & Wisse, 2010). Future research could
address this leadership issue in greater detail.
CONCLUSION
Managers often face the dual challenge of selecting team members that make optimal
decisions and managing the team context to render it more conducive to optimal decision making
and (financial) performance. Our study directly addresses this challenge, identifying the
combination of reflexivity and regulatory focus as a possible route to more optimal decision
making and performance, in showing that (a) these relationships are complex and curvilinear, and
(b) the level of reflexivity level should match the level of promotion/prevention focus as well as
the team context.
30
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FOOTNOTES
1
For instance, a supply chain director of a large plastic tubes manufacturer commented:
“This game shows, in an extraordinary realistic way, how functional decisions affect the chain as
a whole. While we used to play the 'beer game' with our colleagues in the chain, we now have the
new standard for it: The Fresh Connection.”
39
TABLE 1.
Means, Standard Deviations, Aggregate Level Intercorrelations, and Alpha’s
(N = 81 teams)
Variable
M
SD
ICC(1) ICC(2) Rwg(j) 1
2
3
4
1 Reflexivity
4.21
.50
.34
.82
.87
-
2 Inventory level
3.75
1.10
-
-
-
-.30**
-
3 Production reliability
.62
.25
-
-
-
.33**
-.41*** -
4 Promotion focus
3.91
.37
.05
.29
.84
.36**
-.15
.16
-
5 Prevention focus
3.08
.48
.03
.22
.67
.10
.02
.02
.22*
-
6 Team performance a
.03
.11
-
-
-
.40***
-.47*** .54***
.25*
.18
Note: † p < .10; * p < .05; ** p < .01; two-tailed; Dashes indicate that data were not applicable.
Cronbach’s alphas are on the diagonal; a ROI (return on investment)
5
6
-
40
TABLE 2
Results of Regression Analyses with Dependent Variable: Team Performance (ROI)
Model
1
2
3
4
5
β
β
β
β
β
.11
.18
.24
.21*
-.24*
-.20
-.06
. -.01
Step 1: Main and mediating
effects
Reflexivity
.17
Inventory level
-.26**
Production reliability
.36**
.37**
.42***
.37***
.35***
Promotion focus
.06
.14
.31**
.40***
.36***
Prevention focus
.15
.04
-.10
.01
.03
Promo x Prev
-.22
-.28*
.14
.17
Refl x Promo
-.11
-.23
-.35**
-.39***
Refl x Prev
-.20
-.08
.14
.11
Refl x Promo x Prev
.39**
.31*
.14
.05
Reflexivity squared
-.16
.01
.01
Refl squared x Promo
-.41**
-.36*
-.42**
Refl squared x Prev
.35*
.49***
.48***
-.71***
-.44**
.13
.25*
Step 2: Linear interactions
reflexivity
Step 3: Non-linear effects
reflexivity
Refl squared x Promo x Prev
Step 4: Linear moderations
inventory
Inventory x Promo
41
Inventory x Prev
.10
.08
Inventory x Promo x Prev
-.25
-.14
Step 5: Non-linear effects
inventory
Inventory squared
-.12
Invent squared x Promo
.17
Invent squared x Prev
.03
Invent squared x Promo x Prev
∆R2 due to step
-.53*
.42***
.10**
.15***
.04†
.05*
Note: †p < .10; *p < .05; **p < .01; ***p < .001; two-tailed; total R = .87 for model 5;
42
TABLE 3
Results of Regression Analysis for Hypothesis Tests with Dependent Variable:
Inventory Level
1
2
3
β
β
β
Model
Main and mediating effects
Reflexivity
-.28*
-.25*
-.22 †
Promotion focus
-.07
-.11
-.22
Prevention focus
.07
.08
.03
Promo x Prev
.19
-.12
Refl x Promo
-.02
.07
Refl x Prev
-.13
-.31†
Refl x Promo x Prev
-.06
.10
Linear moderations reflexivity
Non-linear effects reflexivity
Reflexivity squared
.12
Refl squared x Promo
.09
Refl squared x Prev
-.29
Refl squared x Promo x Prev
.57*
∆R2 due to step
.09*
Note: †p < .10; *p < .05; two-tailed; total R = .48 for model 3;
.03
.10 †
43
FIGURE 1
Research model with the hypothesized direct, indirect and moderating effects in
the current study
Regulatory focus
Promotion X
Prevention
Team
reflexivity
(squared)
Inventory
level decisions
(squared)
Team
performance
Production
reliability
44
FIGURE 2
Main and mediating relationships of reflexivity with team performance (N = 81 teams)a
.40***/.20*
.33**/.23*
Team
reflexivity
-.41***
Inventory
level
decisions b
-.35**
Production
reliability
.36**
Team
performance
-.47***/-.29**
a
Numbers above the arrows represent standardized coefficients (betas). Betas in bold are
based on regression equations including the connecting mediator; b Inventory level: a low
score is related to better team performance
Note: * p < .05, ** p < .01, *** p < .001; two-tailed tests
45
FIGURE 3
Curvilinear two-way interaction of team level prevention focus on the team reflexivity
squared — team performance relationship
7
ROI
6
5
4
Low Prevention
focus
3
High Prevention
focus
2
1
Low Reflexivity
High Reflexivity
46
FIGURE 4
Curvilinear two-way interaction of team level promotion focus on the team reflexivity
squared — team performance relationship
7
ROI
6
5
4
Low Promotion
Focus
3
High Promotion
Focus
2
1
Low Reflexivity
High Reflexivity
47
FIGURE 5
Curvilinear three-way interaction of team level regulatory focus on the team reflexivity
squared — team performance relationship
0.5
0.4
High promotion
focus, High
prevention
focus
High promotion
focus, Low
prevention
focus
Low promotion
focus, High
prevention
focus
Low promotion
focus, Low
prevention
focus
0.3
Return on Investment
0.2
0.1
0
-0.1
-0.2
-0.3
-0.4
-0.5
Low
Reflexivity
High
48
FIGURE 6
Curvilinear three-way interaction of team level regulatory focus on the inventory level
squared — team performance relationship
0.5
0.4
High promotion
focus, High
prevention
focus
0.3
Return on Investment
0.2
High promotion
focus, Low
prevention
focus
0.1
0
Low promotion
focus, High
prevention
focus
-0.1
-0.2
Low promotion
focus, Low
prevention
focus
-0.3
-0.4
-0.5
Low
Inventory level
High
49
FIGURE 7
Curvilinear three-way interaction of team level regulatory focus on the team reflexivity
squared— inventory level relationship
7
High promotion
focus, High
prevention
focus
High promotion
focus, Low
prevention
focus
Low promotion
focus, High
prevention
focus
Low promotion
focus, Low
prevention
focus
Inventory level
6
5
4
3
2
1
Low
Reflexivity
High