Content uploaded by Marco Marabelli
Author content
All content in this area was uploaded by Marco Marabelli on Oct 09, 2017
Content may be subject to copyright.
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 1
Ups and Downs in Information Systems
Projects – The Dynamic Interplay Between
Control Activities and Emotions
Short Paper
David Murungi
Bentley University
Information and Process Management
175 Forest Street
Waltham, MA 02452, USA
dmurungi@bentley.edu
Martin Wiener
Bentley University
Information and Process Management
175 Forest Street
Waltham, MA 02452, USA
mwiener@bentley.edu
Marco Marabelli
Bentley University
Information and Process Management
175 Forest Street
Waltham, MA 02452, USA
mmarabelli@bentley.edu
Abstract
The control of information systems (IS) projects is an important pursuit for
organizations that are seeking to realize the value-creating capabilities of IT. Realizing
this goal, however, has proven to be a complex undertaking that has engendered
research illustrating unique challenges of IS project control. Extant research in this
domain has focused primarily on the configuration of controls in terms of control modes
and control amounts, but has largely overlooked ongoing dynamics of control (i.e., a
process view) and is reticent on the socio-emotional aspects of control processes. In this
study, we report preliminary findings of a longitudinal case study that evaluates the
dynamic interplay between control activities and emotions within the context of a large-
scale healthcare information systems (HIS) project. Early findings show that emotions
can impact, or be impacted by, control activities, but also provide some seemingly
paradoxical evidence regarding the mechanisms underpinning this dynamic.
Keywords: Healthcare information systems (HIS), IS project control, Control dynamics,
Emotions, Process perspective.
Introduction
An enduring and prevalent theme in the information systems (IS) literature is the problem of IS project
control, or the attempt to motivate project stakeholders to act in accordance with organizational
objectives (Kirsch 1996). Academic interest in this concern has been attributed to the complexity
associated with getting diverse stakeholders, who often do not have prior working relationships, to work
together to achieve organizational goals (Chua et al. 2012). This complexity is compounded by distinctive
features of IS projects such as: (1) their highly abstract and difficult ways to measure work processes and
Page 11 of 21
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 2
outcomes; (2) their frequently changing goals and requirements, task characteristics, team composition,
stakeholder involvement, and organizational context factors; and (3) the uncertainty and difficulty
associated with their temporal nature and typically non-routine and non-recurring performance of tasks
(Remus et al. 2015). Indeed, IS project failures are often not failures of the technology itself, but rather
can be attributed to the complexities associated with stakeholder interactions and relationships (Kirsch
2004).
One such complexity is the role that emotions play in the enactment of IS project control. Since emotions
are attributed to creating and sustaining work motivation (Barsade and Gibson 2007) and project control
is essentially an attempt to motivate individuals to behave in manners consistent with organizational
objectives (Kirsch 1996), it is expected that emotions will influence project control activities, and vice
versa. The nature of this interplay, however, is unclear. In one perspective, for example, the notion of
control is associated with negative emotions that reduce creativity, satisfaction and motivation
(Orlikowski 1991; Gregory and Keil 2014b). The contrasting view suggests that control accomplishes the
opposite by clearly articulating expectations and thus providing stress-reducing structure with respect to
the control situation (Roberts et al. 2006; Boss et al. 2009).
In order to shed light on the interplay between IS project control activities and emotions, this research in
progress adopts a dynamic view of control that sees it as an ongoing organizational process that can be
promoted or constrained by individual emotions (Cram et al. 2016). The paper is thus positioned to help
address a gap in the literature related to a dearth of papers that examine control as a dynamic process.
The large majority of existing studies have focused on the configuration of control portfolios in terms of
control modes and control amounts, thus addressing the question of “what’ controls should be in place”
(Wiener et al. 2016). This was at the expense of addressing ‘how’ questions, which involve viewing
controls as ongoing and dynamic organizational processes. Further, this paper is also positioned to
contribute to a gap in the IS literature related to the topic of emotions. Similar to the dynamic view of
controls, the IS literature on emotions in general (e.g., De Guinea and Markus 2009; Thompson 2012;
Stein et al. 2014; 2015) and in particular on how emotions might affect control processes over time (e.g.,
Cram et al. 2016) is extremely scant.
More specifically, in this research in progress, we examine the impact that different modes and types of
controls (e.g., formal vs. informal) as well as the style in which such controls are enacted (authoritative vs.
enabling) have on both controllee and controller emotions. In turn, we also aim to learn more on how
controller and controllee emotions influence and shape control processes. We therefore wonder: How do
project control activities affect the emotions of project stakeholders, and vice versa, over the course of an
IS project? By exploring the dynamic interplay between control activities and emotions, our study aims to
explore the socio-emotional antecedents and consequences of control activities, thereby contributing to
the growing control literature in the specific context of IS projects.
The paper is structured as follows: We first introduce two complementary conceptualizations of IS project
control activities and review extant literature on IS project control dynamics and emotions. Next, we
describe the research methodology and context of our case study. Finally, we present the findings of our
preliminary case analysis and outline next steps.
Theoretical Background
IS Project Control
Consistent with prior IS project control studies (Kirsch 1996; Choudhury and Sabherwal 2003) and
related studies in contributing disciplines (Ouchi 1979; Das and Teng 1998), we define control as any
attempt to motivate participants to behave in a manner that is consistent with organizational goals. In this
behavioral view of control, a control situation involves a controller who carries out control activities to
influence the behavior of a controllee, or group of controllees (e.g., Choudhury and Sabherwal 2003).
Here, extant literature offers two complementary views to conceptualize IS project control activities.
The majority of IS project control studies conceptualize control activities in terms of control modes (e.g.,
Henderson and Lee 1992; Kirsch 1996), which can be further divided into two types: formal and informal.
Formal control modes (input, behavior, and outcome control) rely on explicit controller prescriptions,
whereas informal control modes (clan and self-control) rely on rather implicit determinants of controllee
Page 12 of 21
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 3
behavior (Jaworski 1988). More precisely, input control concerns the allocation and manipulation of IS
project resources (Jaworski 1988; Mähring 2002). Behavior control aims at specifying work processes and
monitoring controllee adherence to these processes (Kirsch 1996). Outcome control focuses on measuring
actual outcomes and comparing them with prespecified outcomes (Ouchi and Maguire 1975), regardless of
how the results were produced (Kirsch et al. 2002). With regard to informal control modes, clan control
emphasizes the reinforcement of acceptable behaviors through the development of norms and values
shared by IS project participants (Ouchi 1979). In self-control, the controllee herself sets the specific goals
and behaviors to achieve these goals (Henderson and Lee 1992; Kirsch 1997).
A complementary view to conceptualize IS project control activities considers how the controller enacts
control through her interactions with the controllee(s), emphasizing the multidimensionality of control
activities (Gregory et al. 2013). In this regard, Wiener et al. (2016) draw on earlier IS project control
research to introduce the distinction between two ‘extreme’ control styles: authoritative and enabling. An
authoritative control style relies on bureaucratic values and represents a top-down control approach
(Adler and Borys 1996; Gregory et al. 2013; Gregory and Keil 2014a), which is designed to ensure and, if
needed, enforce controllee compliance. In contrast, an enabling control style involves frequent interaction
between controller and controllee (Gregory and Keil 2014a), promotes bilateral feedback (Adler 1999;
Gregory et al. 2013), and grants the controllee some flexibility in dealing with real-work contingencies
(Adler and Borys 1996). There are two central features that distinguish an enabling control style from an
authoritative control style; repair and transparency (Adler and Borys 1996; Wiener et al. 2016). The repair
feature of an enabling control style anticipates breakdowns in control activities and provides capabilities
for fixing them by appreciating controllee feedback about, and facilitating controllee responses to, real-
work contingencies (Adler and Borys 1996; Wiener et al. 2016). The transparency feature of an enabling
control style concerns the visibility of control and other project activities (internal transparency) as well as
the visibility of the broader project organization and context (global transparency).
Although prior IS project control research points to the importance of considering the applied control
style in combination with the employed control modes (Wiener et al. 2016), empirical studies on this topic
remain scarce (Remus et al. 2015). Considering the controller’s control style along with control modes can
be expected to further our understanding of control dynamics, which is an under-researched topic in the
IS project control literature (Wiener et al. 2016).
IS Project Control Dynamics and Emotions
As noted above, project control is essentially an “attempt to motivate individuals to behave in a manner
consistent with organizational objectives” (Kirsch 1996, p. 374). Emotions have been credited with
creating and sustaining work motivation (Barsade and Gibson 2007). We thus propose that emotions are
relevant to understand dynamics in control processes.
The significance of emotions to IS project control is also supported by prior literature. Cram et al. (2016),
for example, found that structural characteristics of the IS control mechanisms and control environment
encourage intrinsic and extrinsic motivations, and thus have the ability to influence individual
participation. Moreover, structural control characteristics cultivate feelings of satisfaction that can in turn
reinforce the related controls and produce improved outcomes. Indeed, as Adler and Borys (1996)
observed, there are two antithetic perspectives on the relationship between control activities and
emotional experience. In one perspective, control is associated with reductions in creativity, satisfaction
and motivation (Orlikowski 1991; Gregory and Keil 2014b). The contrasting view suggests that control
accomplishes the opposite by clearly articulating expectations and thus providing stress-reducing
structure with respect to the control situation (Roberts et al. 2006; Boss et al. 2009).
While, therefore, emotions are important to the practice of IS project control, there is still a gap related to
our understanding of how control activities trigger emotional responses as well as how these responses in
turn lead to subsequent changes (i.e., dynamics) in control activities (Cram et al. 2016; Wiener et al.
2016). The task of developing such an understanding is nevertheless fraught with difficulty not the least of
which is the abundance and confusion surrounding different emotion-related concepts (Stein et al. 2015).
This task is also complicated by an implicit tension between the rational, goal-oriented attributes of the
notion of control and the visceral, spontaneous traits of individual emotions. To address these challenges,
our study builds on novel developments in the IS field that have helped advance our conceptualizations of
emotion in IS contexts.
Page 13 of 21
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 4
In this regard, Zhang's (2013) affective response model unifies a mélange of emotion-related concepts.
Zhang accomplishes this unification by establishing ‘affect’ as “an umbrella term for a set of more specific
concepts, which include emotions, moods and feelings” (Zhang 2013, p. 247). Zhang (2013) also offers
stimulus and core affect as two fundamental concepts that encapsulate this vast domain. Building on
Zhang’s (2013) work, Stein et al. (2015) show how different characteristics of an IT stimulus event, or
emotional cues, interact to produce various types of emotional appraisals and responses that in turn
impact IT use patterns. Stein and colleagues draw from Beaudry and Pinsonneault (2010) who categorize
emotional appraisals along two dimensions: (1) threat vs. opportunity and (2) low vs. high autonomy. On
this basis, they introduce four classes of emotional responses, namely loss (threat and low autonomy),
deterrence (threat and high autonomy), achievement (opportunity and low autonomy), and challenge
(opportunity and high autonomy). It is worth noting that, in the context of our study, emotional cues
relate to the specific features of a control-related activity that induce particular emotional appraisals.
On a related note, Stein et al. (2015) recommend the conduct of longitudinal analyses of emotional cues,
appraisals, responses, and behavioral patterns since such studies can be used to reveal more about the
conditions under which cues change over time, and might highlight the influence of these changes on
resultant emotions and behaviors. Stein et al. (2015) also offer a dynamic model of emotions that we have
revised and adapted to fit the specific context of IS project control processes (Figure 1). In particular, in
our emotion-centered model of IS project control dynamics, a control process starts with a controller
performing a control activity, referred to as controller activity in Figure 1. As noted above, such a control
activity can be classified along two main dimensions: control modes (what) and control style (how). From
the controllee perspective, the controller activity may contain an emotional cue, and eventually trigger an
emotional response by the controllee. For example, a controllee may perceive the controller’s request to
provide daily updates on the progress of the IS project to be inappropriate (emotional appraisal: threat
and low autonomy), and thus may feel disrespected (emotional response: loss). The controllee’s emotional
response is then expected to influence her or his behavior, referred to as controllee activity in the figure
below (e.g., the extent to which she or he adheres to the behaviors prescribed by the controller). From the
controller perspective, the controllee activity may be perceived in terms of an emotional cue, and
eventually trigger an emotional response by the controller. The emotional response may then result in an
adaptation of the enacted controls by the controller (“controller activity”).
Figure 1. An Emotion-Centered Model of IS Project Control Dynamics
Controller
activity
Emotional cue
(controllee)
Emotional
response
(controllee)
Controllee
activity
Emotional cue
(controller)
Emotional
response (controller)
Page 14 of 21
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 5
Research Methods and Setting
Data Collection and Preliminary Analysis
In this study, we chose a qualitative, in-depth approach to examine ‘how’ questions related to the dynamic
interplay between IS project control activities and emotions (Myers 1997; Baskerville and Myers 2002). In
particular, following Easterby-Smith et al. (2008), we chose a single case study to allow close observation
of the organizational actors’ everyday practices based on fieldwork and the collection of supplementary
data. The primary data used in this paper was collected through a series of 40 interviews that were
conducted between November 2010 and October 2011 aimed at understanding various dynamics
occurring during the implementation of a large-scale healthcare information system (HIS). Interview
length varied, but a typical interview lasted about one hour. Most study participants were interviewed
only once, but interviews with the project manager were recurrent to obtain updates on the project’s
progress. Informed by past research capturing work practices through interviews (Scott and Orlikowski
2014; Orlikowski and Scott 2015), we conducted informal, open-ended and semi-structured interviews
aimed at collecting as much detail as possible through carefully listening to the ‘stories’ of project
participants around their direct experience and personal perceptions and feelings during the various
phases of the implementation project (Walsham 1993, 2006). We were thus able to collect both
retrospective (2007-2010) and longitudinal (2010-2011) data. All the interviews were audio-recorded and
professionally transcribed. Note-taking during the interviews was deliberately sparse with a goal of
making the interview feel more conversational than interrogative. Reflection and memo writing were
conducted shortly after the interview to help solidify the insights derived from the interview. In addition
to the interviews, we collected documents on system demonstrations, attended conference calls, and
examined archival data in the form of reports, news clippings and other filed documents. We exchanged
follow-up emails with some of the study participants to further clarify details. We decided to stop
interviewing individuals once most of the details around the implementation process became recurrent
allowing theoretical data saturation (Bowen 2008).
The data collection was part of a dissertation project, therefore some of the interviews have previously
been analyzed for purposes not related to this study. However, given our interest in control processes and
associated emotions, and because this particular dataset is extremely rich on these two aspects (controls
and emotions), we decided to undertake a fresh data analysis involving two new researchers. In fact, all
details arising from our preliminary case analysis (briefly described next) were driven in no way by the
interviewers, and thus genuinely emerged from loosely structured conversations with focal actors involved
in the HIS project implementation.
Our preliminary data analysis was performed using NVivo. We undertook an open coding approach (Miles
and Huberman 1984), which is consistent with prior research aimed at interpreting and making sense of
how phenomena unfold in practice (Orlikowski 2002; Nicolini 2011). For purposes of this research
endeavor, we scanned the interview transcripts as well as the open coded data (approximately 5,500
initial codes) to develop preliminary observations related to significant emotional events in the HIS
project as well to identify any overt links between these emotional events and IS project control activities.
For example, to capture controllee emotions in the data, we employ Stein et al.’s (2015) approach that
identifies the presence of affective data by looking for emotional terms (e.g., pleased; worried; angered) in
interviewee depictions of the HIS project. We then grouped these responses into the four affect categories
used in Stein et al. (2015) (i.e. loss, deterrence, achievement, and challenge) and analyzed the reasons
given for these responses to understand how they are associated with specific control activities by the
controller(s). In particular, to understand what specific aspects of control activities trigger emotional
responses (i.e., contain emotional cues), we assessed whether or not respondents link these emotional
expressions to particular control modes (i.e., input, behavioral, output {formal}, clan, and self {informal})
or control styles (i.e., authoritative and enabling).
To illustrate this coding process, which is grounded in Stein et al.’s (2015) approach to capturing emotions
from semi-structured interviews, we demonstrated the main steps associated with analyzing the following
depiction of the HIS project by one of the controllees (user in marketing department) when discussing the
history of the initiative:
Page 15 of 21
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 6
“…I think IS is still paying a price for a very poorly executed centralization. I think they thought they
were doing it really well, but that particular model that they used, which was kind of just napalmed
across the organization, created a lot of hard, hard feelings, a lot of distrust. I think they struggle to
listen and really be that kind of service or client service model mentality, tell us what your goals are and
then we are going to be subject matter experts to help you accomplish your goals.”
In the initial coding this response was coded as follows: poorly executed centralization, conflicting
perceptions of centralization success, napalmed centralization, hard feelings and distrust, IS listening
struggles, client service model unachieved. Hard feelings and distrust were then deduced from these codes
as the core emotional terms in the discourse and these were placed in the loss category of emotional
response, which was prompted by the controllee’s perception of threat and low autonomy (emotional
appraisal). This emotional appraisal could also be linked to a particular emotional cue, that is, to the use
of a particular control mode (input control) and control style (authoritative) because centralization, or the
reallocation of resources, is a classic example of input control (see Table 1 for the criteria used to identify
particular control modes) and because the fact that this was “napalmed” across the organization indicates
a lack of repair and transparency and is thus illustrative of an authoritative style of control.
Table 1. Coding Criteria for Control Modes and Mechanisms (adopted from Wiener et al. 2016)
Control Mode Key Characteristics Control Mechanisms (Examples)
Input control
(formal)
Specify, monitor, and manipulate resource
allocations (human, financial, and material)
Reward or sanction the controllee based on
her ability to utilize allocated resources
• Recruitment, selection, and
replacement of project staff
• Training programs
• Changes in allocation of funding
Behavior control
(formal)
Specify and monitor rules, procedures, and
processes
Reward or sanction the controllee based on
her adherence to the specified behaviors
• Mandated IS development
methodology
• Regular status meetings/calls
• Weekly and monthly reports
Outcome control
(formal)
Specify and evaluate outputs (interim and
final)
Reward or sanction the controllee based on
the outputs delivered
• Defined project milestones
• Functional specifications
• Weekly software delivery
Clan control
(informal)
Shared norms and values as well as a
common vision that motivate goal-directed
controllee behaviors within a peer group
• Ceremonies and rituals
• Socialization (e.g., team events)
Self-control
(informal)
Self-monitoring of controllee behaviors
based on intrinsic motivation and individual
standards and objectives
• Individual empowerment
• Self-management
In the above example, we then examined links between the controllee’s emotional response of loss and the
controllees subsequent activities and evaluated how the latter in turn impacted controller emotions and
activities (see Figure 1). Specifically, in this example, the marketing department’s reaction to the emotion
of loss was the development of a parallel consulting engagement (emotional cue) that was couched as a
marketing endeavor, but also positioned to cater to its unique IS needs. This controllee activity
contributed to controller (IS project manager) perceptions of threat and reduced autonomy (emotional
appraisal), which can be linked to the emotional response of loss from the controller. This emotional
response resulted in a subsequent recalibration of control activities that was manifested in a ‘level setting’
document, which attempted to control the discourse and define the boundaries of HIS initiative.
Generally, this emotional dynamic was assessed in terms of controller-controllee interactions and this
relationship served as the unit of analysis. Due to the vast amount of data collected, the analysis of the
case data is still ongoing. We next provide contextual details on the case.
Page 16 of 21
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 7
Case Context
This study examines a large-scale IS project aimed at implementing an HIS to enable data exchange
between a private health system (referred to as Southeast Health System—SHS) and a community-owned
cancer center (Eagle Cancer Center—ECC).
In June 2007, the National Cancer Institute (NCI) provided a major grant to the SHS’ flagship hospital
(Lakefront Regional Center—LRC) and ECC, which was affiliated with LRC. The grant was the early
impulse for the HIS project and was provided through NCI’s National Community Cancer Center Program
(NCCCP), which was developed with the aim of extending the reach of NCI research beyond its network of
63 designated cancer centers principally based at large research universities to include community-based
treatment centers. The NCI grant was awarded to LRC based on its relationship with ECC. Although LRC
and ECC would share in treatment of individual cancer patients, the two entities maintained separate
electronic medical records for their patients. Thus, one of the key goals of the federal grant was to increase
the synergy that existed between the two entities by creating a mechanism for electronically sharing data
between these organizations (as well as for transferring this data to the NCI database). The initial control
structure for the HIS project consisted of two primary control relationships: (1) the relationship between
the senior management teams of SHS/LRC and ECC (controller) and the IS project manager (controllee);
as well as (2) the control relationship between the IS project manager (controller) and the members of the
different business departments at LRC and ECC (controllees). The two control relationships were
intertwined since, in the second relationship (IS project manager vs. business departments), the project
manager was mainly acting as an agent of the senior management team.
Roughly two years later, with advent of the $787 billion American Recovery and Reinvestment Act of
2009 and its constituent $22 billion Health Information Technology for Economic and Clinic Health
(HITECH) Act, the HIS project was absorbed into a larger initiative. Specifically, instead of completing a
simple interface between LRC and ECC (as had been previously envisioned), the two parties opted to
implement a more complex interface between the two organizations as well as the three other acute care
hospitals run by SHS in order to meet one of the “meaningful use” requirements stipulated by the
HITECH Act for receipt of its incentive payments. At this point, the organizations decided to involve a
third-party vendor to help implement the increased scope of the HIS project, which also marked the
advent of a third controller-controllee relationship between the project manager (controller) and the
vendor (controllee). This control relationship was predominantly contractual. The vendor involvement
also resulted in a shift in project management methods as the vendor utilized an agile approach to project
management while the SHS project management office was used to running its projects in a traditional
waterfall approach.
Preliminary Findings
Based on our preliminary analysis, we were able to identify five prominent emotional events (i.e.,
incidents of heightened emotional content as manifested by a prevalence of emotional terminology in
interviewee depictions of the event) over the course of the HIS project (see Table 2). The first emotional
event occurred in November 2007 after SHS consolidated the management of its IS function by moving it
away from its constituent hospitals to its corporate office. This action was met with a sense of widespread
dissatisfaction among business stakeholders. According to Stein et al.’s (2015) conceptual framework, the
emotions at this stage can be characterized as an instance of loss. There was also heightened emotional
discourse associated with the February 2009 passage of the HITECH Act, which can be characterized as a
stage of mixed emotions. On the one hand, the Act produced expressions of anxiety (deterrence) from
organizational respondents due to substantial penalties that were associated with not meeting the
meaningful use provisions. On the other hand, there were also expressions of hope (challenge) associated
with the $30 million dollars in incentive payments from the federal government that were to be achieved
with a successful demonstration of meaningful use.
Another peak in emotional terminology was observed in discussions of events that occurred in November
2010 when SHS’s meaningful use committee announced its vendor of choice for the HIS project. A
prominent group of business users applied terms of resentment and anger (loss) to depict their reaction to
this event. There was a similar uptick in emotional discourse in January 2011—this time primarily from
respondents in SHS’ senior management team—in response to SHS’ project management announcement
Page 17 of 21
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 8
that the project that was initially chartered at $300,000 was now slated to cost about $3.2 million. Then
in May 2011, within the context of interactions with the vendor of choice, there was another spike of
emotions related to a failure of the project to meet important milestones on time and heightened concerns
that the project would not meet deadlines associated with meaningful use payments.
Table 2. Timeline of Emotional Events in HIS Project
Time Event Emotional Response
November 2007 Consolidation of SHS hospitals’ IS
functions into corporate function
Loss (controllees): Business users had no
voice in decision (low autonomy) and
feared this decision would decrease their
access to IS resources (threat)
February 2009 Passage of the HITECH Act (broadened
the scope of the original grant)
Deterrence/Challenge (controller): Act
contained both rewards for compliance
(opportunity) as well as penalties for non-
compliance (threat)
November 2010 Announcement of involvement of
(external) software vendor to meet
provisions of HITECH Act
Loss (controllees): Marketing department
had no influence on vendor choice (low
autonomy) although this decision
impinged upon a separate relationship
between this department and an outside
consultant (threat)
January 2011 Announcement of significant increase in
project cost from $300,000 to $3.2
million (this increase became apparent
after the contract was signed and new
technical details surfaced)
Loss (controller): Senior management felt
they were locked in the vendor contract
(low autonomy) despite the cost increase
(threat)
May 2011 Failure to meet important project
milestones on time (one of the factors in
delay was the prolonged time that it took
for senior management to approve the
increased cost of the HIS project)
Deterrence/Loss (controller): Senior
management and IS project manager
expressed concern related to a potential
loss of about $30 million in incentive
payments from the federal government
(threat)
On this basis, our preliminary analysis revealed several links between some of the above described
emotional events and the control activities carried out in the HIS project. One example of where control
activities were instrumental in producing the emotional responses that were observed in this project
occurred when SHS’s senior management team consolidated the IS function away from its four
constituent hospitals to a centralized corporate function (input control). This restructuring was decided
and implemented by the senior management team without engaging the business users (i.e., authoritative
control style) and produced the emotional response of loss on behalf of the controllees. While this
emotional response did not have an immediate impact on controller-controllee interactions, it did affect
the behaviors of business users later on in the HIS project. Specifically, the IS project manager expressed
continued exasperation with business users who were rejecting the recommended choice of vendor for the
HIS project based primarily on lingering hurt feelings that still stemmed from the heavy handed execution
of IT consolidation. This was evidenced by the users rejection of the proposal, even though they found no
technical faults with the system.
Interestingly, at this instance, the IS project manager’s use of an enabling control style did not improve
the situation. Rather, the use of this control style seemed to have enabled expressions of pent up emotions
that impacted controllee behaviors and also impacted the control activities of the controller. For example,
prior to this emotional event the IS project manager had relied primarily on input and outcome controls,
but with the advent of user antagonism increasingly relied on behavior controls such as an increased
number of teleconference calls and more frequent meetings with business users. In parallel, there was an
Page 18 of 21
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 9
increased effort to enhance the degree of socialization that took place between the IS project manager and
the business stakeholders (e.g., dinner meetings). Taken together, these findings offer preliminary
evidence for the dynamic interplay between control activities and emotions over the course of the HIS
project.
In addition, our preliminary case analysis indicates that there were heightened emotions in the HIS
project, which were not directly linked to IS project control activities. There was, for example, a noticeable
amplification of emotional terminology when describing the attainment of the NIC grant at the initiation
of the HIS project. Similarly, there was a general increase in emotion related to the passage of HITECH
Act. Although IS project control activities did not seem to have (exclusively) produced these emotional
events, our analysis points to subsequent adjustments in project control activities that could be attributed
specifically to controllers’ emotional responses to these particular events.
Conclusion, Implications and Next Steps
Our preliminary findings suggest that emotions have the ability to impact, or be impacted by, control
activities. We thus expect our study to contribute to the literature on IS project because we highlight the
relevance to adopt a process view to study the dynamic reconfigurations of control activities over the
course of a large-scale IS project and to explore their interplay with emotions. In addition, we expect to
contribute to the literature on emotions by acknowledging the key role of emotional cues and responses in
explaining the effectiveness of control activities as well as in triggering changes in such activities.
Our preliminary results unfold relevant implications. Most notably, learning about the extent to which
emotions can positively or negatively influence the ways control processes unfold over time is of
paramount importance for managers (controllers). In this regard, scholars who focus on non-prescriptive
types of control (e.g., Ouchi and Maguire 1975; Ouchi 1979) suggest that organizational culture,
engagement and leadership might lead to more effective ‘clan control’, where supervision is replaced by
trust and empowerment. While these findings are being widely applied in modern organization dynamics,
it seems managers have not yet fully embraced a leadership philosophy that accounts for understanding
the relevance of emotions at the work place and therefore often do not leverage emotions, as they should.
For instance, in a recent Harvard Business Review article, Herminia Ibarra (2015) quotes a senior
manager at a transportation company who claims that “I can do the storytelling too, but I refuse to play on
people’s emotions. If the string-pulling is too obvious, I can’t make myself do it.” This is illustrative of the
lack of awareness that managers currently have which is related to the ‘power of emotions’ (Newell and
Marabelli 2016). To this end, and following Stein et al. (2014), emotions are produced relationally (Thrift
2008); that is, relations between actors (e.g., controllers and controllers) not only produce emergent task-
related outcomes, but also produce human emotions, which can result in a particular felt quality or mood
that characterizes our being-in-the-world (Ciborra 2006). Thus, emotions are not simply experienced as
an afterthought of action that is produced by an individual’s interpretation of a specific control-related
situation; rather, emotions are a psychosocial phenomenon that emerges from collective action. Indeed,
Dreyfus (1991) argues that a mood is always present, shaping and being shaped by our collective actions
and this mood can generate a collective energy (or its opposite—apathy). This, in practical settings, might
represent a powerful asset that can be used by controllers (but also by controllees, paradoxically) to shape
the ongoing dynamics of complex control systems.
In terms of the future development of our work, during fall 2017, we plan to undertake an in-depth
analysis of the 40 interviews as follows: first, one of the authors (the lead contributor of this work) will
review the already existing open codes and perform an exhaustive mapping of these codes to the focal
study concepts, namely control modes and styles (Wiener et al. 2016) as well as emotional cues and
responses (Stein et al. 2015). Second, the lead author will analyze the instances (codes) identified and look
for interactions between control activities and emotions. After each step, we will involve a second
researcher (another author of this study) to perform reliability testing. Also, a third researcher will do an
additional reliability test on 10% of the codes. We will then reflect on particular instances where control
activities stimulated emotional responses by the controllees, and/or when emotional responses triggered
changes in control activities. We will take this as the starting point to look back at the literature on IS
project control and emotions with the aim of extending prior research.
Page 19 of 21
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 10
References
Adler, P. S. 1999. "Building Better Bureaucracies," Academy of Management Executive (13:4), pp. 36-47.
Adler, P. S., and Borys, B. 1996. "Two Types of Bureaucracy: Enabling and Coercive," Administrative
Science Quarterly (41:1), pp. 61-89
Barsade, S. G., and Gibson, D. E. 2007. "Why Does Affect Matter in Organizations?," Academy of
Management Perspectives (21:1), pp. 36-59.
Adler, P. S. 1999. "Building Better Bureaucracies," Academy of Management Executive (13:4), pp. 36-47.
Adler, P. S., and Borys, B. 1996. "Two Types of Bureaucracy: Enabling and Coercive," Administrative
Science Quarterly (41:1), pp. 61-89.
Barsade, S. G., and Gibson, D. E. 2007. "Why Does Affect Matter in Organizations?," Academy of
Management Perspectives (21:1), pp. 36-59.
Baskerville, R. L., and Myers, M. D. 2002. "Information Systems as a Reference Discipline," MIS
Quarterly (26:1), pp. 1-14.
Beaudry, A., and Pinsonneault, A. 2010. "The Other Side of Acceptance: Studying the Direct and Indirect
Effects of Emotions on Information Technology Use," MIS Quarterly (34:4), pp. 689-710.
Boss, S. R., Kirsch, L. J., Angermeier, I., Shingler, R. A., and Boss, R. W. 2009. "If Someone Is Watching,
I'll Do What I'm Asked: Mandatoriness, Control and Information Security.," European Journal of
Information Systems (18:2), pp. 151-164.
Bowen, G. A. 2008. "Naturalistic Inquiry and the Saturation Concept: A Research Note," Qualitative
Research (8:1), pp. 137-152.
Choudhury, V., and Sabherwal, R. 2003. "Portfolios of Control in Outsourced Software Development
Projects," Information Systems Research (14:3), pp. 291-314.
Chua, C. E. H., Lim, W.-K., Soh, C., and Sia, S. K. 2012. "Enacting Clan Control in Complex IT Projects: A
Social Capital Perspective," MIS Quarterly (36:2), pp. 577-600.
Ciborra, C. U. 2006. "The Mind or the Heart? It Depends on the (Definition of) Situation," Journal of
Information Technology (21:1), pp. 129-139.
Cram, W. A., Brohman, K., and Gallupe, R. B. 2016. "Information Systems Control: A Review and
Framework for Emerging Information Systems Processes," Journal of the Association for Information
Systems (17:4), pp. 216-266.
Das, T. K., and Teng, B.-S. 1998. "Between Trust and Control: Developing Confidence in Partner
Cooperation in Alliances," Academy of Management Review (23:3), pp. 491-512.
De Guinea, A. O., and Markus, M. L. 2009. "Why Break the Habit of a Lifetime? Rethinking the Roles of
Intention, Habit, and Emotion in Continuing Information Technology Use," MIS Quarterly (33:3), pp.
433-444.
Dreyfus, H. L. 1991. Being-in-the-World: A Commentary on Heidegger's Being and Time, Division I. MIT
Press.
Easterby-Smith, M., Golden-Biddle, K., and Locke, K. 2008. "Working with Pluralism Determining
Quality in Qualitative Research," Organizational Research Methods (11:3), pp. 419-429.
Gregory, R. W., Beck, R., and Keil, M. 2013. "Control Balancing in Information Systems Development
Offshoring Projects," MIS Quarterly (37:4), pp. 1211-1232.
Gregory, R. W., and Keil, M. 2014a. "Blending Bureaucratic and Collaborative Management Styles to
Achieve Control Ambidexterity in Is Projects," European Journal of Information Systems (23:3), pp.
343-356.
Henderson, J. C., and Lee, S. 1992. "Managing I/S Design Teams: A Control Theories Perspective,"
Management Science (38:6), pp. 757-777.
Ibarra, H. 2015. "The Authenticity Paradox," Harvard Business Review (93:1/2), pp. 53-59.
Jaworski, B. J. 1988. "Toward a Theory of Marketing Control: Environmental Context, Control Types, and
Consequences," Journal of Marketing (52:3), pp. 23-39.
Kirsch, L. J. 1996. "The Management of Complex Tasks in Organizations: Controlling the Systems
Development Process," Organization Science (7:1), pp. 1-21.
Kirsch, L. J. 2004. "Deploying Common Systems Globally: The Dynamics of Control," Information
Systems Journal (15:4), pp. 374-395.
Kirsch, L. J., Sambamurthy, V., Ko, D.-G., and Purvis, R. L. 2002. "Controlling Information Systems
Development Projects: The View from the Client," Management Science (48:4), pp. 484-498.
Page 20 of 21
Dynamic Interplay Between Control and Emotions
Thirty Eighth International Conference on Information Systems, South Korea 2017 11
Kirsch, L. S. 1997. "Portfolios of Control Modes and Is Project Management," Information Systems
Research (8:3), pp. 215-239.
Mähring, M. 2002. "IT Project Governance," in: Doctoral Dissertation. Stockholm School of Economics:
Stockholm.
Miles, M. B., and Huberman, A. M. 1984. Qualitative Data Analysis: A Sourcebook of New Methods.
Newbury Park, CA: SAGE Publications.
Myers, M. D. 1997. "Qualitative Research in Information Systems," MIS Quarterly (21:2), pp. 241-242.
Newell, S., and Marabelli, M. 2016. "Knowledge Mobilization in Healthcare Networks: The Power of
Everyday Practices," in Mobilizing Knowledge in Healthcare: Challenges for Management and
Organization, J. Swan, D. Nicolini and S. Newell (eds.). Cambridge: Oxford University Press.
Nicolini, D. 2011. "Practice as the Site of Knowing: Insights from the Field of Telemedicine," Organization
Science (22:3), pp. 602-620.
Orlikowski, W. 1991. "Integrated Information Environment or Matrix of Control? The Contradictory
Implications of Information Technology.," Accounting, Management & Information Technology (1:1),
pp. 9-42.
Orlikowski, W. J. 2002. "Knowing in Practice: Enacting a Collective Capability in Distributed Organizing,"
Organization Science (13:3), pp. 249-273.
Orlikowski, W. J., and Scott, S. V. 2015. "The Algorithm and the Crowd: Considering the Materiality of
Service Innovation," MIS Quarterly (39:1), pp. 201-216.
Ouchi, W. G. 1979. "A Conceptual Framework for the Design of Organizational Control Mechanisms,"
Management Science (25:9), pp. 63-82.
Ouchi, W. G., and Maguire, M. A. 1975. "Organizational Control: Two Functions," Administrative Science
Quarterly (20:4), pp. 559-569.
Remus, U., Wiener, M., Mähring, M., Saunders, C., and Cram, A. 2015. "Why Do You Control? The
Concept of Control Purpose and Its Implications for Is Project Control Research," Thirty Sixth
International Conference on Information Systems, Fort Worth, pp. 1-19.
Roberts, J. A., Hann, I., and Slaughter, S. A. 2006. "Understanding the Motivations, Participation, and
Performance of Open Source Software Developers: A Longitudinal Study of the Apache Projects.,"
Management Science (52:7), pp. 984-999.
Scott, S. V., and Orlikowski, W. J. 2014. "Entanglements in Practice: Performing Anonymity through
Social Media," MIS Quarterly (38:3), pp. 873-893.
Stein, M.-K., Newell, S., Wagner, E., and Galliers, R. D. 2015. "Coping with Information Technology:
Mixed Emotions, Vacillation and Non-Conforming Use Patterns," MIS Quarterly (39:2), pp. 367-392.
Stein, M.-K., Newell, S., Wagner, E. L., and Galliers, R. D. 2014. "Felt Quality of Sociomaterial Relations:
Introducing Emotions into Sociomaterial Theorizing," Information and Organization (24:3), pp. 156-
175.
Thompson, M. 2012. "People, Practice, and Technology: Restoring Giddens' Broader Philosophy to the
Study of Information Systems," Information and Organization (22:3), pp. 188-207.
Thrift, N. 2008. Non-Representational Theory: Space, Politics, Affect. London and New York: Routledge.
Walsham, G. 1993. Interpreting Information Systems in Organizations. New York, NY: John Wiley &
Sons, Inc.
Walsham, G. 2006. "Doing Interpretive Research," European Journal of Information Systems (15:3), pp.
320-330.
Wiener, M., Mähring, M., Remus, U., and Saunders, C. 2016. "Control Configuration and Control
Enactment in Information Systems Projects: Review and Expanded Theoretical Framework," MIS
Quarterly (40:3), pp. 741-774.
Zhang, P. 2013. "The Affective Response Model: A Theoretical Framework of Affective Concepts and Their
Relationships in the ICT Context," MIS Quarterly (37:1), pp. 247-274.
Page 21 of 21
