Week 3 redesign of business processes

Attachments

Technology A d o p tio n by
G lo b a l V ir tu a l Teams:

D e v e lo p in g a Cohesive
A pproach

W illia m J. Harris, University o f Maryland University College

International trade and collaboration continue to
expand in the development of products, services, and
interdependent-m arket activities. Such expansion
has resulted in an increase in global engineering
groups’ interaction across cultures. These groups
exist, in part, because technology now supports
geographically distributed organizations, which
allows them to improve perform ance and outcome.
However, in many instances, the cultural differences
among group members have become problematic in
their work (Clear, 2010; Nisbett, 2003). Both research
and practice have shown that these groups, and the
technology they use, may form working structures
that are incompatible with many culturally diverse
organizations. This essay explores and uncovers
pertinent issues and provides a conceptual framework
that will allow company managers to adopt technology
that is compatible across global virtual teams (GVT)
and organizations. The aim of this paper is to identify
implications and provide guidance to managers who
may be faced with designing and leading m ulti­
national groups tasked with solving complex problems.
In short, this research will provide guidance to those
managers that will allow them to put theory into
practice.

Background and C ontext o f G lobal
V ir tu a l Teams

Global engineering teams in the public sector are
tasked to provide various capabilities for government
agencies. Contractors that serve various government

agencies and tasked to integrate global technical
capabilities employ many such teams. Often, groups
are formed without a physical presence as enabled
by technology (Brynjolfsson & McAfee, 2014). These
engineering team members, being diverse both
in their fields of expertise and in their geographic
location, are expected to work and perform together,
fully exploiting their abilities and accumulation
of knowledge to design capabilities and/or resolve
unique problems (Pavlak, 2004). Often, these teams
are comprised of a variety of engineers from fields
such as software, hardware, systems, mechanical, and
other disciplines. For these teams, team work agility
and decision making are essential (Lowry, Schuetzler,
Giboney, & Gregory, 2015). An engineering team’s
advantage, then – as well as their challenge – is their
collective diversity and trem endous knowledge and
expertise (Harris, 2018).

Team tasking evolves from the first stage of
identifying a problem or requirements to creating
capabilities, introducing new features to existing
products, and then, through to production, technical
services, sustainment, and operations (Defense
Acquisition System, n.d.). The full lifecycle of a project,
whether creating products or providing technical
services, will eventually include the interchange of
ideas, design elements, and solution implem entation
for global team m embers (Harris, 2018).

Many requirements and problems that companies
encounter simply cannot be resolved in-house or at a
single country location; yet, their solutions are critical

4 SAM Advanced Management Journal – Volume 83 Edition 1

for these companies to launch a product, rectify issues
that arise, or sustain their businesses (Harris, 2018).
Moreover, international trade and collaboration have
continued to evolve, resulting in companies receiving
an increase of revenues from global operations
(Thomas, Beilin, Jules, 8c Lynton, 2014). And along
with these increased global opportunities and
international trade, the development of products and
services has expanded internationally and has become
more globally interdependent. Thus, engineering teams
are tasked to accomplish a variety of critical functions
across geographical boundaries (Thomas et al., 2014).
In as much, global virtual teams form and reform as
their tasking progresses or as a response to events that
unfold over the life cycle of a system or product (Clear,
2010). These engineering teams exist, in part, because
technology now supports geographically distributed
organizations, which allows them to effectively
communicate to improve perform ance and outcome
(Harris, 2018).

The Challenges o f Global Virtual Teams
As a result of this virtual environment, managers

of these teams are faced with efficiently providing
effective resources along with guiding teams through
the entire life-cycle process from determ ining
requirements through finding and implementing
solutions. These virtual teams rely on technology to
execute engineering processes, collaborate in their
activities, and to validate and share knowledge (Harris,
2018). Furtherm ore, these teams are often faced with
conflict and disagreement within their ranks yet must
still implement effective solutions (Lowry et al., 2015).
The project manager m ust be prepared to plan and
to coordinate effective resources to support the GVT.
Thus, the need to manage the adoption and use of
technology that supports the GVT to accomplish their
tasking is critical for successful outcomes (Harris,
2018).

Research has found, there are a num ber of cultural
challenges that these teams face based on their
diversity (Clear, 2010; Mejias, 1995; Thomas et
al., 2014). These challenges include bridging their
languages, cultures, time zones, experience, and so
forth – through effective management. This in itself
is not an easy task, as it requires a level of agility to
orchestrate and bridge those differences (Thomas et
al., 2014, p. 38). These groups are not always wholly
successful in this endeavor, and consequently, their
differences, be they cultural, linguistic, or logistical,

can become problematic (Nisbett, 2003). Because
these cross-cultural issues pose inherent problems in
the interaction of GVTs, they also form an im portant
com ponent of this research.

Inspite of the fact that these global teams may
be spread out geographically, they are nonetheless
expected to engage in collective behavior to solve
problems quickly, coordinate product design, initiate
start-up activities, brainstorm innovative solutions,
and perform other nonroutine functions. Gains in
technology that support these teams have increased
the expectations of their perform ance and abilities
to better manage interactions, share knowledge, and
predict outcomes. One such Advanced Information
Technology (AIT) designed to support these teams
is collaboration software (Coleman 8c Levine,
2008). The capabilities contained within this type
if software are available off the shelf, and they are
also configurable. Among these AIT technologies is
SharePoint enterprise software, which uses third-party
applications, such as BPM CRM. However, we must
not lose sight of the fact that people are as complex as
the systems they adopt. As such, adding the variable
of cultural differences among teams may com pound
tasking problems for virtual global groups (Clear, 2010;
Mejias, 1995). This study examines the issues faced by
organizations as they prepare to launch global teams
using AIT.

Companies and agencies that do business
internationally may run into unique problems with
political consequences. Harris (2018 p. 14) provided
a poignant example: For nearly 2 decades, both the
U.S. D epartm ent of Defense (DOD) and NASA have
used the Russian RD-180 rocket motors for the heavy
lift Atlas V rocket to resupply the International Space
Station and for launching military satellites (Dilanian,
2016). In order to use this Russian rocket motor,
the U.S. military contracts with the United Launch
Alliance (a joint venture between defense contractors
Boeing and Lockheed Martin; Dilanian, 2016). Yet,
this practice is particularly problematic given the
adversarial nature of US/Russian relations (e.g., their
opposing roles in Syria and the Ukraine). Thus, when
a failure occurs, as it did during the 2016 Cygnus
OA-6 International Space Station’s resupply (“By the
Numbers: How Close Atlas V Came to Failure,” 2016),
both countries put together tiger teams to perform
failure analysis to determ ine the root cause. One can
easily see that a failure of one country’s product may
become exploitive political news overnight, regardless

SAM A d vanced M a n a g e m e n t Journal – Volum e 83 Edition 1 5

of sound engineering and business operations.
Regardless of the situation, GVTs come together

with specific tasks, goals, and objectives to achieve
outcomes for unique problems; they accept difficult
challenges and ultimately are able to achieve acceptable
outcomes (Harris, 2018). Not surprisingly, putting
together these teams and then supporting them is a
problem global managers frequently face, especially
when unanticipated critical issues arise that must
be addressed w ithin a short am ount of time (Harris,
2018). In other words, the ability of a company
operating globally to successfully operate across
country and cultural boundaries is only viable if the
company’s m anagement is able to solve difficult and
sometimes time-sensitive problems – whilst satisfying
global stakeholders.

Advanced Information Technology’s Role and New
Social Norms

The late 1950s and early 1960s saw the advent
and proliferation of computers, which enhanced
the scientific technology revolution (Harris, 2018).
And as part of this information revolution, both
routine and nonroutine activities were improved
upon by the use of technology by teams (Geels &
Kemp, 2007). Then in the early 1980s, technology
advancements progressed once again, fully developing
the inform ation digital revolution, which continues
today (Brynjolfsson 8c McAfee, 2014). W hat were
once localized hardware platforms with dependent
software-supporting engineering functions have given
way to ubiquitous applications compatible with a
variety of devices that support global group interaction
(Brynjolfsson 8c McAfee, 2014). These group support
technical capabilities have led to expanded and new
social com m unication norms. In fact, a new form of
sociology – digital sociology (Lupton, 2015) – has
emerged to address hum an interaction with both
computer-based group support tools and today’s
social media. Thus, as technology has advanced,
so, too, have m ethods of com m unication and team
production (Harris, 2018). These phenom ena have
resulted in a shift in social interaction, bringing forth
new concepts in sociology in-step with group support
technologies that impact the way GVT’s communicate
to accomplish their tasking: digital sociology (Lupton,
2015).

Research Q uestion
The exploratory research question presented below

is designed to drive this systematic study, as will
perm it identification and examination of emerging
themes and relationships, which will ultimately allow
conclusive findings that will inform managers of GVTs.
These findings will provide insight for both researchers
and practitioners into the m anagement of global
virtual teams and the adoption of support technology.
To that end, the following research question forms the
context and drives this research:

W hat specific issues do global problem-solving teams
face when adopting advanced inform ation technology
(AIT) for collaborative support?

L ite ra tu re Review
Whereas the adoption of technology by groups

within singular cultures has been thoroughly
researched for over 3 decades (Nikas & Poulymenakou,
2008, p. 1; Turban, Liang, & Wu, 2011, pp. 140-
141), literature on the adoption of technology to
support global teams across cultures is not as prolific.
Drawing from eight sources (see Appendix B), this
literature review addresses major themes and issues
with supportive evidence. The eight sources are
conventionally identified in the reference section with
a preceding *. First, theoretical underpinnings are
considered, covering concepts on group interaction
and structured adaptation of technology for
m ultinational groups. The eight articles that support
the major topics explored herein, which include both
scholarly and “gray literature,” are then addressed.

Theoretical Underpinnings for Group Interaction
and Technology Adoption

This researcher identified two prim ary theories
upon which collective group behavior in the adoption
of technology can be understood. These theories are
Hofstede’s theory, which provides a model of cultural
differentiation (Hofstede, 1980; Hofstede, Van Deusen,
Mueller, Sc Charles, 2002), and adaptive structural
theory (AST; DeSanctis & Poole, 1994; DeSanctis et al.,
2008; Gopal, Bostrom, & Chin, 1993).

Hofstede’s theory: Model o f cultural
differentiation. Three of the selected studies
(Davidson & fordan, 1998; Mejias, 1995; Paul,
Samarah, Seetharaman, & Mykytyn, 2005) specifically
based their conclusions on Hofstede’s (1980) seminal
research on the cultural differences of global teams. In
the early 1980s, Hofstede researched and identified the
collective characteristics of countries and their cultures
based on data gathering research from 53 countries

6 SAM Advanced M anagement Journal – Volume 83 Edition 1

and 116,000 respondents. Hofstede discovered that
there are five dimensions in cultural differentiation:
Power-Distance, Uncertainty-Avoidance,
Individualism-Collectivism, Masculinity-Femininity,
and Tim e-Orientation. In Mejias’s study (1995), the
author referred to four out of five of the dimensions
described in Hofstede’s cultural differentiation model:
“Cultural differentiation described four dimensions
of national culture along which value systems may
vary…. [H]is Model of Cultural Differentiation
framework may be useful in hypothesizing specific
predictions of cultural tendencies” (pp. 56-69).

Davidson and Jordan (1998) and others have
concurred with Mejias’s assertion that the dimensions
of uncertainty avoidance and power distance have
the greatest influence in relating cultural aspects
of interdependent groups operating across cultural
boundaries. However, these dimensions also represent
the underlying characteristics of individualism
or collectivism, in varying degrees, for each of
Hofstede’s five dimensions (See Figure 1). Notably,
Paul et al. (2005. p. 190) viewed the fifth dimension
of individualism/collectivism as a dom inating aspect
across the power distance and uncertainty-avoidance
scheme. Here, Mejias (1995, pp. 59, 61) provides a apt
description of both power distance and uncertainty-
avoidance:

Power Distance describes the relationship and
relative distance between a supervisor and a
subordinate … the extent to which a particular
national culture accepts and recognizes the
unequal distribution of power and influence
in institutions and organizations. Countries
that score high on power distance appear to
emphasize autocratic or paternalistic, boss-
employee relations. In these countries the
powerful have more privileges over others….
Countries scoring low on Power Distance
favor participative management relations and
prefer the use of “equal rights” and legitimate
power over the use of coercive or referent
power. D uring group decision making, higher
status individuals are more likely to dominate
the group discussion and influence group
outcomes more than low status individuals.
Uncertainty-avoidance expresses the extent
to which members of a particular national
culture feel uncomfortable or threatened by
uncertain or unknow n outcomes (Hofstede,
1980, 1991). Countries that scored high on the
Uncertainty Avoidance dimension tended to
have a low tolerance for uncertainty (expressed
by higher levels of anxiety) and a greater need
for formal rules. Additionally, countries with

F ig u r e 1 . R e l a t i o n s h i p B e t w e e n U n v e r t a i n t y A v o id a n c e a n d P o w e r D is t a n c e

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as

– w

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s –
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CL

Uncertainty Avoidance
Low High

Family Model – clannish

Countries:
Southeast Asia, Singapore,
Hong Kong, India, Philippines

Pyramid Model – fiefdom

Countries:
Latin America, Mexico, Brazil, Chile,
Venezuela, Yugoslavia

Market Model – structure Machine Model – bureaucracy

Countries: Countries:
Anglo/Scandinavia, United States, Germanic, Israel, Austria
Australia, Canada, The Netherlands,
United Kingdom

SAM Advanced Management Journal – Volume 83 Edition 1 7

strong (high) Uncertainty Avoidance scores
also had less tolerance for people or groups
with deviant ideas or behavior and were more
likely to resist innovative ideas (Hofstede; 1980,
1991). Countries with weak or low Uncertainty
Avoidance scores were inclined to take more
risks and were more likely to tolerate deviant
behavior and innovative ideas when making
group decisions (Hofstede; 1980, 1991).

Figure 1 depicts the relationships between the
variables of power distance and uncertainty-avoidance
and the countries whose cultures align with each. In
sum, Hofstede’s theory is param ount in anticipating
cultural issues associated with multinational teams
as they come together to work.Figure 1. Hofstede’s
Regional/Countries Matrix of Cultural Differentiation
(Mejias, 1995, p. 66; Davidson & Jordan, 1998, p .41).

Adaptive structuration theory (AST). Giddens’s
(1984) original structuration work unified an approach
to social organization theory, resulting in a holistic
view of people acting together to achieve com m on
goals. In doing so, Giddens shifted the focus from the
individual to groups of actors who are knowledgeable
about the systems they produce and reproduce (Harris,
2016, p. 3). Adaptive structuration theory (AST)
expands upon Giddens’s theory that by incorporating
AIT as a com ponent of group activities (as proposed
by researchers, including Gopal et al., 1993, and
DeSanctis et al. 1994; 2008, p. 552), a unified AST
would result.

Harris’ (2016, p. 7) earlier research described the
relationships of groups and technology from an AST
perspective, finding: AST posits that the impacts
of AIT “on group and organization processes and
outcomes depend on the structures incorporated in
the technology and on the structures that emerge as
users attempt to adapt the technology to the tasks
at hand” (Poole, 2013, p. 22). DeSanctis and Poole’s
(1994) foundational description of AST first defines a
system as an observable pattern of relationships among
actors as part of a group. Structures are the rules and
resources that members employ in their activities
and interactions that give the system its pattern. As
members develop rules and resources from their tasks,
norms, and AIT, they enact and sustain structures
to make them part of an ongoing organization of a
system. In other words, groups produce and reproduce
rules and resources as they interact to accomplish
their tasking. As a result, AST posits the effects of
AIT on group processes and outcomes depend on the

structures incorporated w ithin technology (structural
potential) and the emergent (adaptive) structures that
form as members interact with the technology and
themselves over time (DeSanctis & Poole, 1994, pp.
22-23).

DeSanctis and Poole (1994) also describes how
AST works by identifying the two AIT structural
elements: spirit and features. Spirit being the general
intent with regards to values and goals of the specific
rules. Capabilities and usage rules make up structural
features of the technology… The result being a novel
structural ensemble tailored to the group’s n eed s… and
interactions (DeSanctis & Poole, 1994, pp. 22-23).

Harris (2016) also found that the components of
structural adaptations from the interactions of group
members with regard to appropriated AIT (depicted
in Figure 2) are segregated by input-process-output
functions. These elements (changing rules, resources,
group/technology products, and tasking environment)
dynamically come together during social interaction
(see center of Figure 2), appropriating and applying
ongoing influences of new and emerging structures.

Literature from four of the eight studies reinforces
the applicability of AST for this research. For example,
Watson (1994, pp. 47-48) noted that AST makes an
im portant distinction between system and structure:
“The system is a social entity such as a group …
structures are the norm s of behavior that maintain
the system” (p. 47). Nicolas-Rocca and Coulson
(2014, p. 83) then expanded upon AST with task-
technology-fit to build a framework that explains the
interrelationships of global virtual teams and their
functional abilities. Finally, Nikas and Poulymenakou
(2008, pp. 4-6) applied AST in their research on
adopting web-based collaboration technology to global
teams. Based on the studies of these researchers, AST
became a foundational theory for this paper.

Adopting Advanced Information Technology and
Features

Group support systems (GSS) are a form of AIT.
Watson’s (1994) early work informs us: “GSS is a
blend of technical and social facilities … and because
GSS design is often based on the customs of the
particular culture in which it was developed … both
technical and social features may need modification
for successful adoption” (p. 45). Davidson and
Jordan (1998, p. 44) provided research on technology
adoption for GSS as it relates to global teams with a
focus on barriers to adoption in cross-cultural settings.

SAM Advanced Managem ent Journal – Volume 83 Edition 18

Figure 2. Adaptive Structuration Theory Domain and IPO Diagram

I n p u t s P r o c e s s O u t p u t s

/
S tru c tu re o f Advanced

\

In fo rm a tio n Technoloev
• Features

V. Spirit (in te n d e d use) /
Task & E n v iro n m e n t

Structures
Task ty p e

S itu a tio n , ex pe c tation s

In te rn a l G ro up System
In d iv id u al preferences
In te ra c tio n

N o rm s, processes,
A IT fa c ilita tio n

G r o u p S o c i a l I n t e r a c t i o n

Tech A D o ro o riatio n GrouD Processes
* D e gre e o f Respect • Id e a g e n e ra tio n
* Faithfulness • P a rtic ip atio n
■ Consensus • D ec is io n -M a kin g
■ In s tru m e n ta l v a lue • C onflict M g t
• A IT A ttitu d e s • Influen ce
■ Ease o f use • Process M g t

_____ ■P
E m erg ent Sources of

Stru ctu re
A IT Products & O u tp u ts

Task Products &
O utp uts
Changes in E n viro n m en t
D ue to A IT Use

O utcom es
• Q u a lity o b je c tiv e

perceived

• Consensus
• C o m m itm e n t
• C onfidence in

Decisions
• Satisfaction w ith

O utcom es and
Process

Figure 2. Adaptive Structuration Theory Domain and IPO Diagram (DeSanctis et al., 2008, p. 555;
Gopal et al., 1993, p. 49)

Davidson and Jordan pointed out a num ber of failures
in adopting technology within these environments that
included mismatching software tools, lack of group
interrelations awareness, and insufficient experience in
facilitating the use of AIT (p. 39). These authors also
relied on Hofstede’s theory of cultural differentiation to
explain technology adoption across teams:

GSS may be used as a source of inspiration, but
its underlying assumptions should be tested
to see if they [technology features] fit with
local assumptions about how groups should
function. W here necessary, the assumptions
should be reconceptualised according to local
traditions.

A more recent study on adopting technology was
conducted by Nikas and Poulymenakou (2008).
Their study directly linked AST to the adoption and
adaptation of technology by global groups. These
authors also found that faithfully appropriating
technology (Figure 2) depends on task structures as
well as group social systems (e.g., norms, personal
preferences, facilitation).

Group support and collaboration systems have

dom inated AIT team based research for the past
30 years (Nicolas-Rocca & Coulson, 2014). At first,
technology emerged as stand-alone proprietary
software designed for specific hardware platforms.
These initial systems, which were predom inantly
used for record keeping, data analysis, and reporting,
were feature-limited. More complex systems evolved
that included high perform ance workstations rich
in features and information management, such as
AutoCAD® in the 1980s for engineering support.
Advancing in AIT for GSS now provide open access
cloud applications and social media, thereby advancing
capabilities in support of decision making and other
im portant group needs (Turban et al., 2011, p. 141).

W ithin enterprise support systems, automated
decision technologies include rule-based engines,
statistical or numeric algorithms, workflow
applications, and outcome prediction. Social software
capabilities, described as Collaboration 2.0-3.0, and
products such as SharePoint and SalesForce are
examples of enterprise GSS (Harris, 2016). In fact,
newer AIT features create collaborative platforms
that reflect the way knowledge work is naturally

SAM Advanced Management Journal – Volume 83 Edition 1 9

accomplished rather than adjusting behaviors around a
system (Harris, 2018; Nicolas-Rocca & Coulson, 2014;
Turban et al., 2011, p. 141).

Global Virtual Team Composition, Structure, and
Use o f Technology

Global virtual teams (GVT) have evolved into groups
that assemble using combinations of technology to
accomplish an organizations task (Paul et al., 2005,
p. 188; Tung & Turban, 1998, p. 177). GVTs are more
complex than traditional face-to-face. These teams
may be comprised of individuals with a collection of
differing skills and professions using tools specific to
their areas of expertise. Or, teams of like professions
are brought together to tackle a common issue within
their area. Both research and practice have shown that
both teams and technology structures change based
on ongoing influences (see Figure 2, AST diagram).
New structures emerge with the dynamic nature of
work that create new rules, thereby changing the tasks
and capabilities of both hum ans and machines. That
is, a multiphase project comprised of both people and
technology transform s as the tasks and environment
change. For example, Paul et al. (2005) linked bipolar
dimensions (see Figure 1) to group composition while
tying perform ance to Hofstede’s theory.

Team structure – centralization/decentralization.
The literature reviewed in this research concluded that
decentralization is a direct benefit of AIT, especially
as it relates to decision making. The studies reviewed
make a clear distinction between decision making and
control, as facilitated by AIT (Robey, 1977, p. 974).
Halal (2013) argued that it is essential to determine
which technology is best suited strategically for a
particular type of organization. As a result, Harris
(2018) found Halal (2013, p. 1640) established the
concept for understanding the impact of technology
on organization centralization or decentralization.

Robey (1977, p. 974) also concluded that AIT has
supported greater degrees of formal and informal
decentralization. For example, as explained by Harris
(2018): Robey (1977) claimed that AIT supports stable
environments, which are best suited to organizations
with central authority where routine operations are
the main focus. However, under dynamic conditions
(i.e., nonroutine operations), technology reinforces
decentralization (Robey, 1977, p. 974). However,
Harris (2018) also found that Pheffer and Leblebici
(1977) came to a different conclusion, claiming that
technology supports centralization (personal control)

as a substitute for formalization. However, Pheffer and
Leblebici (1977) also found that technology supports
rapid environmental changes, which may result in
increasing and enabling decentralization (pp. 245-
246). Huber (1990, p. 57) took decision making one
step further, claiming that AIT provides a uniform
approach to decision making, acting as a decentralized
function for centralized organizations and visa versa.
Nault’s (1998, p. 1322) later work provided a more
detailed organizational application of technology,
asserting that it allows both centralized (hierarchy) and
decentralized (local market) decision support w ithin
the same organization.

Team structure – organization complexity.
Organization complexity is also a com m on theme
in the literature. An early empirical study viewed
knowledge work and technology complexity as
a systems functioning under uncertainty within
organizations (Hickson, Pugh, & Pheysey, 1969,
p. 380). Harris (2018) found in this earlier study,
Hickson et al. characterized technology complexity,
in relationship to organizations, by looking at the
num ber of exceptional cases encountered, the degree
of logical analysis, and how the inform ation was used
in workflow (p. 380). Robey (1977, p. 974) concluded
that the structure of an organization does not depend
upon any type of technology, “but rather the nature
of the task environment,” inferring complexity. Pfeffer
and Leblebici (1977, p. 248) added to the organization
complexity discussion by submitting that technology is
positively associated with both vertical and horizontal
differentiation within organizations, as this allows “the
manager to control and coordinate …

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