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The effect of digital
transformation strategy
on performance
The moderating role of cognitive conflict
Hecheng Wang, Junzheng Feng, Hui Zhang and Xin Li
School of Management, Hangzhou Dianzi University, Hangzhou, China
Role of
cognitive
conflict
441
Received 29 September 2019
Revised 13 January 2020
Accepted 27 February 2020
Abstract
Purpose – The purpose of this study is to verify whether digital transformation strategy (DTS) could
improve the organizational performance and provide a comprehensive analysis for enterprises on the
necessity of implementing digital transformation in the context of China and draw on the perspectives of
“Skewed conflict,” “minority dissent theory” and “too-much-of-a-good-thing.” This study investigates the
curvilinear moderating role of cognitive conflict between DTS and performance.
Design/methodology/approach – An empirical investigation was used to collect a large sample data of
Chinese enterprises’ digital transformation. A multiple linear regression analysis with SPSS was used to test
the proposed hypotheses such as the inverted U-shaped moderating effect of the cognitive conflict.
Findings – In the Chinese context, DTS has a positive relationship on the short- and long-term financial
performance. Moreover, this relationship was moderated by cognitive conflict such that the relationship
between DTS and short-term financial performance could be further enhanced under the moderate cognitive
conflict; however, the relationship between DTS and long-term financial performance was considerably
influenced for higher cognitive conflict.
Originality/value – Based on the co-evolution of the information technology/information system (IT/IS)
and business strategy, this study clarified the relationships among DTS, digital strategy and business and
information technology strategies. By focusing on corporate strategy, this study further examined the effect
of digital transformation on both short- and long-term financial performance. To further reveal the micropsychological mechanisms underlying the effect of DTS on organizational performance, this study confirmed
the inverted U-shaped moderating effect of the top management team’s cognitive conflict. Therefore, this
research provides a new theoretical perspective for future research in the field of IT/IS, DTS and digital
strategy.
Keywords Cognitive conflict, Digital transformation strategy, Long-term financial performance,
Short-term financial performance
Paper type Research paper
The authors appreciate the anonymous reviewers’ constructive comments and suggestions and
would like to thank Prof. Steven Si for his deep insights and kind support. This research is supported
by Humanity and Social Science Youth foundation of Ministry of Education of China (Project
Number: 18YJC790028), Chinese National Funding of Social Sciences (Project Number: 19BGJ014,
17BJY072), National Natural Science Foundation of China (Project Number: 71372170), The Youth
key Project of the Major Humanities and Social Sciences Program in Zhejiang Colleges and
Universities (Project Number: 2018QN017).
International Journal of Conflict
Management
Vol. 31 No. 3, 2020
pp. 441-462
© Emerald Publishing Limited
1044-4068
DOI 10.1108/IJCMA-09-2019-0166
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31,3
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Introduction
Recently, the digital economy has stormed the whole world and has attracted considerable
attention from governments worldwide. It is gradually becoming the new focus of
competition among countries, industries and enterprises. Currently, one of the most pressing
challenges for enterprises is the integration and use of digital technologies and no sector or
organization is immune to effects of digital transformation (Hess et al., 2016). Digital
transformation is a strategic response to the trend of digital economy and technology and
has thereby become the strategic priority for improving the leadership of top management
team (TMT) (Fitzgerald et al., 2014; Hess et al., 2016; Singh and Hess, 2017). Furthermore,
using digital technologies, enterprises could improve their operation efficiency with office
automation software and fundamentally refresh the corporate commercial strategy with
profound changes in the product and service, organizational framework and the business
model and processes (Hess et al., 2016; Bharadwaj et al., 2013; Sebastian et al., 2017; Tumbas
et al., 2017). Thus, in the digital economy age, digitalization has now become a strategic
management issue for enterprises rather than a technical issue (Rogers, 2016; Besson and
Rowe, 2012; Li et al., 2017). According to the survey of American and British enterprises, 90
per cent of business leaders contended that IT and digital technology would increasingly
contribute to developing the overall business of enterprises in the next ten years (Bonnet
et al., 2012). For pre-digital organizations, the formulation and implementation of the digital
transformation strategy (DTS) have become the core issues (Chanias et al., 2019). Bakos and
Treacy (1986) already proposed that IT is a competitive weapon in that it can
comprehensively impact the corporate strategy but technology-based competitive
opportunities are overlooked for several reasons. Current studies on digitalization and
digital transformation primarily focus on the field of information technology/information
system (IT/IS), commercial economy and social science (Henriette et al., 2015; Reis et al.,
2018), as well as consider digital transformation as a function of IT/TS department or
business strategy. However, studies focusing on the level of corporate strategy are rare
(Hess et al., 2016), indicating the lack of dialogues between IT/IS and mainstream strategic
management theories.
Over the last 30 years, this study focused on digitalization, digital strategy and digital
transformation by considering the extensive and profound influence of digital technology on
the whole society. This digital trend resulted from the corporate strategic changes promoted
by continuous interaction and fusion between the IT/IS strategy of the enterprise and
business strategy. Based on the fusion view, Chanias et al. (2019) indicated that the
corporate IT strategy was equivalent to business strategy. Furthermore, Henderson and
Venkatraman (1993) considered that the corporate IT strategy must be aligned with
business strategy; however, the influence of digital technology development on enterprises
is significantly far out of the range of IT department as well as other functional strategies.
For example, with digital technologies, the internal operation of enterprises could be
considerably influenced, and the context of commercial competition and the social network
structure with suppliers and customers could be remolded. Bharadwaj et al. (2013) proposed
that the strategic role of IT should be reconsidered. Based on the alignment view, they
proposed the digital business strategy – an organizational strategy formulated and
implemented using digital resources to create different values. The digital business strategy
might indicate the prospect of a digital business model for enterprises but it fails to supply
practical guidance for enterprises to achieve digital transformation. Moreover, current
research and practical knowledge of IT strategy fail to inspire new DTSs (Hess et al., 2016).
Yeow et al. (2018) indicated that alignment is insufficient for integrating corporate IT and
business strategies; thus, they integrated the two to form the digital strategy. However,
digital strategy is difficult to be clearly explained in the dynamic environment, indicating a
further clarification of the similar but different definitions such as IT strategy, digital
strategy and digital transformation. In dynamic environment, DTS signposts the way (Hess
et al., 2016) or displays a blueprint (Matt et al., 2015) toward digital transformation and
guides managers integrating and using digital technology to implement digital
transformation. Based on the combinatory view of the strategic process and activity
(Burgelman et al., 2018), Chanias et al. (2019) argued that the realized DTS is the (mental)
outcome of a highly dynamic process that comprises an indefinite number of the recurring
episodes of digital strategy making, which represents the accomplishment of enterprises in
formulating digital strategy at certain times. These studies provide new insight into
exploring DTS; however, they fall short of providing the core connotation of DTS and the
micromechanism by which it influences organizational performance.
To fill this theoretical gap, strategy-as-practice school’s theory (Jarzabkowski, 2004, 2005;
Whittington, 1996; Jarzabkowski and Spee, 2009; Chia, 2004; Whittington, 2006) was used in
this study to bridge the DTS theory and conflict management theory. Moreover, the internal
mechanism by which the digital transformation strategic decision-making improves the
organizational performance was explored. DTS provides opportunities for pre-digital
enterprises to explore new approaches of value creation; however, compared with born-digital
organizations, such as Amazon, Facebook, Google and Tencent, the digital transformation of
pre-digital organizations would cost longer time and face larger challenges than expected
(Zinder and Yunatova, 2016). Digital transformation of business models is a highly complex
process of change involving a series of carefully calculated and interdependent strategic
decisions (Aspara et al., 2013; Velu and Stiles, 2013). Thus, based on the theory of strategy-aspractice school, it is wrong to formulate digital strategy without considering the psychological
construct such as emotion, motivation, social and political interactions as well as the
background (Jarzabkowski, 2005; Jarzabkowski and Spee, 2009; Whittington, 2006). Studies on
the organizational behavior suggest that to solve the difficulty within decision-making,
psychological factors, such as cognition and emotion, must be considered (Luce et al., 1999;
Broniarczyk and Griffin, 2014; Anderson, 2003). Actually, conflict was seen as the source of
decision difficulty in many real world domains, particularly for decisions that include trade-offs
between money vs. time (Cheng and González-Vallejo, 2017), gains vs. losses (Cheng and
González-Vallejo, 2018) and rewards and distance (Scherbaum et al., 2013). Simons and
Peterson (2000) argued that existing cognitive structure and paradigm of TMT would
significantly influence corporate strategic behavior. As the environment becomes more
complex than usual, the organizational change becomes more intense, and the activities are
considerably more non-routine decisions, and the effect would be more important. Therefore,
during the digital transformation of pre-digital enterprises, an important challenge is solving
the mismatch of the digital economy and the cognition of managers (Velu, 2017), while the
significant obstacle is TMT without digitalization experience.
Furthermore, based on the theory of strategy-as-practice school, this study effectively
linked DTS with cognitive conflict using the decision-making theory and proposed that the
influential effect of digital transformation on organizational performance depends on the
cognitive conflict of TMT. To address the strategic decision difficulty (the quality,
consistency and feeling acceptance of decision-making are imbalanced and even
contradictory), conflict that occurs among the members of TMT with different cognitive
structures and levels is the “crux” (Amason, 1996). Because of the editability, scalability, and
openness of digital technology are changing the “rules of the game” (Briel et al., 2018;
Nambisan, 2017), and making firms facing a pervasive threat of innovative competition, the
returns are uncertain and the value creation is complex (Warner and Wäger, 2019).
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Therefore, maintaining moderate cognitive conflict is vital to improving the DTS decisionmaking quality and thereby improve organizational performance as follows:
promoting an agreement of enterprises on whether or not implement the DTS;
optimizing the content of the DTS and determining the implementation range of the
strategy;
promoting an agreement on the intensity and pace of implementing the DTS; and
ensuring the implementation of digital transformation, such as changing the
organizational structure, innovating the business model, integrating suppliers/
customers, and establishing an open ecosystem.
Therefore, from the perspective of IS and strategic management, this study bridged the
theories of DTS and conflict management by the strategy-as-practice theory. The research
questions were as follows:
RQ1. Whether or not DTS reliably improves organizational performance? This study
aimed to improve the importance of digitalization for strategic decision-makers
and managers of IT and business departments, thereby providing concrete
evidence for enterprises to implement a digital strategy.
RQ2. How can cognitive conflict moderate the relationship between DTS and
organizational performance? This study aimed to optimize the conflict
management level in corporate strategic decision-making, thereby providing
theoretical guidance for enterprises to formulate and implement digital
transformation and in turn improve their organizational performance.
Compared with current studies, the contributions of this study on the corporate technology
strategy, information system, digital transformation and conflict management theories are
as follows:
Current studies indicated the effects of the digital technology on enterprise’s
operation efficiency and the DTS on the organizational performance, the industry
and the whole society (Vial, 2019); however, this study focuses on the DTS and
segregates the organizational performance into short-term financial performance
and long-term growth performance, widening and deepening of the current research.
Based on the TMT’s conflict management theory, this study confirmed the
moderating effect of the TMT’s cognitive conflict on the relationship between the
DTS and different types of organizational performance, thereby further revealing
the conditions for enterprises to improve the organizational performance by
implementing DTS.
Moreover, the firm’s age, size, ownership, industry type, TMT size and firm’s past
performance were considered as control variables in this study to improve the reliability of
the conclusion. The theoretical model is provided in Figure 1.
Conceptual framework and hypotheses
Digital strategy, digital transformation strategy and performance
Digital strategy indicates that to seize the new opportunities in the digital economy age,
enterprises embed the digital technology into the whole organizational operations, including
production, marketing and other activities (Bharadwaj et al., 2013; Yeow et al., 2018) as we;;
as create value based on digital resources to obtain and maintain the competitive edge. From
the perspective of strategic process, DTS is neither an event (Hirschheim and Sabherwal,
2001) nor the final state of the strategy; however, it is a process of adjustment and change for
achieving digital strategy; this process is composed of a series of decision-making activities
appearing and iterating continuously (Yeow et al., 2018). Based on the combinatory view of
strategy (Burgelman et al., 2018), Chanias et al. (2019) considered the DTS as a series
of crucial decision-making activities. According to the alignment process, the achievement
of digital strategy requires simultaneous changes for factors at different levels, including the
strategy level and IT and business levels. For implementing DTS, in addition to the
decision-making factors of financial pressure and support, other three critical activities are
included: the use of digital technologies, changes in value creation and structural changes
(Hess et al., 2016; Matt et al., 2015).
For the use of digital technologies, it is universally acknowledged that enterprises maintain
the long-term survival by making strategic investments in the field of IT (Arvidsson et al.,
2014). The use of digital technologies is the foundation for enterprises to implement DTS and
could effectively improve their operational performance. However, it is impractical to expect an
instant effect by one-time investment for digitalization. To unlock the full potential of digital
and improve operation performance, enterprises should constantly accumulate digitalization
experience and make continuous investments within digitalization, thus improving capabilities
and skills of digital management. By the continuous use of digital technologies, enterprises
could promote automated and intelligent internal operations, significantly reduce the cost,
improve the operation efficiency and management quality, achieve business processes change
and business model innovation and ultimately optimize the customer experience. BayoMoriones et al. (2013) showed that the use of information and communications technology by
small- and medium-sized enterprises has a positive relationship with organizational
performance; however, this relationship does not have an instant effect but with a laggedperiod effect varying according to the type of ICT. Bharadwaj (2000) confirmed the positive
relationship between corporate IT capacity and financial indicators such as profit margins,
return on assets (ROA), return on sales (ROS) and average per capita income. Using digital
technologies, the organizational agility would be improved with fast data collection. Moreover,
with the assistance of digital technologies, new organizational routines and common values
could be formed, and their positive attitude toward cross-functional and inter-organizational
goals could be cultured to improve the performance. Neirotti et al. (2008) and Setia et al. (2013)
demonstrated that by taking full advantages of ICT, enterprises could obtain new market
opportunities and information about their customers and effectively improve the development
of new products.
In the digital economy age, an organization could rarely prevent the competitive damage
brought by the new digital technology and new business model (Al-Debei and Avison, 2010).
However, only purchasing some digital products has little effect on the organization because
digital technologies need to be combined with the specific context of enterprises to discover
new approaches of value creation. Thus, in the context of digital transformation, changes in
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Figure 1.
Theoretical model
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value creation take place because of the changes by digital technology to the business model
(Hess et al., 2016; Morakanyane et al., 2017; Piccinini et al., 2015). Zott et al. (2011) proposed
that digital technologies have changed the approaches for enterprises in value creating and
value capturing and are the fundamental driving force for business model innovation. Vial
(2019) systematically summarized the existing literature and proposed that the digital
technology’s role in promoting value creation mainly underlies in:
creating new value propositions;
enabling companies to redefine their value networks;
changing the ways for enterprises to interact with suppliers/customers; and
improving the agility and ambidexterity of enterprises.
Generally, internal mechanisms to improve organizational performance because of changes
in value creation include the following:
In addition to the products, digital technology-based value creation can provide
customers with innovative solutions, meet the individual needs of customers (Porter
and Heppelmann, 2014; Wulf et al., 2017) and improve customers satisfaction.
Digital technology-based value creation can change the traditional role and
interaction ways between enterprises and suppliers or customers such as
transforming the transaction relationship into value co-creation (Lucas et al., 2013).
It is not only to reduce the cost of communication and coordination but also to
continuously create new value for customers.
It can create new communication channels for customers (Hansen and Sia, 2015) to
increase trust between the enterprise and its customers, enabling enterprises to
clearly understand customer demands and seize new opportunities.
The structural change dimension of DTS framework is concerned with who will be in charge of
the transformation endeavor, how to keep balance between new operations and current
operations and how to acquire new digital competencies and skills (Hess et al., 2016). To
improve the competitive edge in digital trends, most enterprises must transform their previous
organizational structures, processes and standards to develop into flexible organization forms.
Westerman et al. (2014) contended that enterprises adapt to the digital transformation by
changing the customer experience, operation process and business model. Chanias et al. (2019)
showed that the critical approach to ensuring a successful digital transformation is to set up
digital transformation governance structures, meeting regularly across functional boundaries
and holding workshops involving multiple organizational levels, networking, collaborating and
exchanging knowledge on digital transformation. Hess et al. (2016) researched the digital
transformation of three multimedia companies in Germany and found that the group’s CEO
should be directly responsible for transformation work. Digital technologies should be applied
to create a new customer experience and optimize business processes. Specifically, the internal
mechanisms to improve organizational performance delivered by structural changes based on
digital technologies is as follows:
The CEO is fully responsible or participation for the DTS contributes to the
achievement of the corporate strategic goals.
The establishment of a unique digital transformation department or team is
beneficial to guide strategic and operational activities based on business and
customer-oriented objectives.
Digital technologies enhance the organizational ambidexterity capability (Vial,
2019), enable enterprises to take full advantages of the potential of existing
resources in current businesses while developing new digital products and business
(Li et al., 2017; Svahn et al., 2017) and support the long-term development of
enterprises.
Based on digital technologies and open digital platforms, building a cooperation
platform for suppliers and customers is beneficial to achieve value creation among
multiple parties (Lucas et al., 2013) and create new value for customers.
Based on this result, the following hypotheses were made:
H1. DTS has a positive relationship with short-term financial performance.
H2. DTS has a positive relationship with long-term financial performance.
The moderating role of cognitive conflict
Cognitive conflict is a task-related conflict caused by different opinions or divergence in
achieving a common goal during decision-making (Amason, 1996; Chenhall, 2004). It occurs
when the members of TMT have different opinions about the understanding of the decision,
allocation of scarce resources, the implementation of relevant policies and strategies and the
choice of different action plans (Bedford et al., 2019). In general, effective decision-making is
closely related to cognitive conflict, while ineffective decision-making is highly correlated
with relationship conflict (Simons and Peterson, 2000). The DTS involves a series of
carefully calculated and interdependent strategic decisions (Aspara et al., 2013; Velu and
Stiles, 2013); the complex strategic decision-making and value creation and the uncertain
returns (Warner and Wäger, 2019) determine the complexity of the improvement of
organizational performance delivered by the DTS. Studies have confirmed that for complex
and unconventional decision-making, cognitive conflict can stimulate creative ideas (Farh
et al., 2010) and thoughts (Chen et al., 2019; De Dreu, 2006), promote members of TMT to
reflect as well as enhance trust and understanding, thereby improving the organizational
performance by making high-quality decisions (Amason, 1996; Chenhall, 2004; Parayitam
and Dooley, 2009; Simons and Peterson, 2000; Sinha et al., 2016; Olson Et al. 2007; Rose and
Shoham, 2004; De Wit et al., 2012). However, when the cognitive conflict is out of control or
transformed into relationship conflict, their positive relationship ceases to exist (De Dreu,
2006; Simons and Peterson, 2000).
In low cognitive conflict, only a few group members disagree with the corporate strategic
decision or no significant opinion divergence occurs among the group members in daily
work. Skewed conflict theory (Sinha et al., 2016) indicated that members who have different
opinions could not influence others and the importance of different opinions would be
neglected by most members. Thus, a low cognitive conflict could hardly generate positive
results such as creative thoughts. Moreover, it is difficult to enhance trust, understanding
and reflection among TMT members, thereby causing the difficulty in improving
organizational performance. In turn, in the context of low cognitive conflict, because a few
team members disagree with the corporate strategic decision-making and objectives and
their opinions fail to win the agreement of others, they would work with resistance, rejective
psycology and behaviors, and even dawdle over their work, thereby hindering the
improvement of organizational performance. In addition, in the context of low cognitive
conflict, team members tend to make decisions based on existing experience and routines,
especially in the cultural context of Chinese collectivism and high power distance. When a
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few team members have different opinions, they are inclined to adopt silence, avoidance,
compromise or even obedience. This result is not conducive to formulating optimal strategic
decisions and damages the improvement of organizational performance.
In the context of moderate cognitive conflict, certain team members disagree with the
corporate strategic decision-making or significant differences appear in opinions among
team members in daily work. Based on the minority dissent theory (De Dreu and West, 2001;
McLeod et al., 1997):
team members are aware of these divergent opinions; and
team members with the different opinions would like actively promote their status
and express their opinions formally (such as meetings) or informally (such as
private gatherings) and in turn affect other team members.
Thus, the context of moderate cognitive conflict enables members to reflect from different
perspectives (De Dreu and West, 2001) and conduct extensive and in-depth discussions on
these issues. When more information exchanges and thought integrations can be achieved
among members (Farh et al., 2010), strategic decisions would be made more effectively by
enterprises, ultimately improving organizational performance. Sinha et al. (2016) confirmed
the positive relationship between the positively skewed task conflict with performance; i.e.
when most team members perceive task conflict at low levels while a few team members
perceive it at high levels, organizational performance would be improved because these a
few team members would express their different opinions in a careful, cooperative and
politically sensitive manner, thereby leading to more open, productive and constructive
discussions (Sinha et al., 2016).
In the context of high cognitive conflict, most team members disagree with the corporate
strategic decision or significant opinion divergency appears among the members in daily work.
According to the effect of too-much-of-a-good-thing, in the context of high cognitive conflict, the
significantly different opinions of members would lead to the failure of TMT members to grasp
and understand the essence of different opinions and to propose a better solution (Farh et al.,
2010; De Dreu and Weingart, 2003). Moreover, high cognitive conflict would result in the
cognitive overload (Carnevale and Probst, 1998), strained interpersonal relationship, emotional
conflict (Yang and Mossholder, 2004; Greer et al., 2008; Simons and Peterson, 2000; Curseu et al.,
2012), bias in using information (De Wit et al., 2013) and excessive pressure (Dijkstra et al., 2005;
Yang and Mossholder, 2004; Jehn et al., 2008). These results would lead to the difficulty in
exchanging and communicating information among members, preventing the emergence of
new ideas, opinions and solutions (De Dreu, 2006; Pelled et al., 1999), thereby affecting the
quality of strategic decisions and improvement of organizational performance. Based on the
skewed conflict theory, the context of high cognitive conflict indicates that divergence among
team members is broad and open and team members need to spend more time and energy on
managing and coordinating conflict rather than focusing on improving organizational
performance (Sinha et al., 2016). In particular, in the Chinese context, high cognitive conflict
among team members would lead to more critical consequences, e.g. TMT would be divided
into different political fractions or small groups, and the members possibly intrigue against
each other and compete for power and scarce resources, leading to a drastic erosion of
organizational performance.
Based on the skewed conflict theory, minority dissent theory and the too-much-of-agood-thing effect (Chen et al., 2019), this study proposed that cognitive conflict has an
inverted U-shaped moderating relationship on the relationship between corporate DTS
and organizational performance; i.e. the relationship between DTS and organizational
performance could be enhanced by moderate cognitive conflict and weakened by low
and high cognitive conflict. The hypotheses proposed by this study were as follows:
H3. The cognitive conflict of top management members has an inverted U-shaped
relationship on the relationship between DTS and short-term financial performance.
H4. The cognitive conflict of top management members has an inverted U-shaped
relationship on the relationship between DTS and long-term financial performance.
Methods
Data collection and procedures
China is an active practitioner in the digital economy and offers a rich context to test DTS.
As the largest electronic commerce market with a fast-growing digital economy, China is a
critical player in shaping the global digitalization landscape. Chinese government considers
the digital economy as a national strategy and conducts a series of supporting policies
because it is expected to be a new driver for China’s economic growth and a new tool for
industrial transformation and upgrade. In China, the digital economy rapidly develops and
has become the new engine for high-quality economic growth, while it is deeply integrated
with real economies, such as manufacturing and service industries, to increasingly
contribute to the GDP. Although the overall construction of digital capabilities of enterprises
is still in the initial stage, certain enterprises have successfully overcome the difficulty of
business transformation and achieved favorable results, making them the leaders in
corporate digital trends (Accenture et al., 2018). Digitalization helps pre-digital enterprises to
rebuild the core competitiveness and business model and accelerate transformation and
upgrading. Moreover, Chinese companies have considered digital transformation as an
important strategic opportunity to catch up with world-class enterprises. Therefore, the
rapid development of the digital economy and the successful implementation of the
enterprises’ digital transformation make China suitable for empirically testing DTS.
Roy et al. (2001) demonstrated that the data collection of enterprises in the context of the
emerging economy is difficult and tedious; therefore, appropriate channels and related
resources are important. To improve the questionnaire return rate and ensure the
effectiveness and reliability, we delivered questionnaires and collected data from business
partners, friends, MBA or EMBA students and government officials. From June to August
2019, a total of 182 questionnaires were collected, while 26 of them were excluded because of
the low answer rate and high consistency of answers. Thus, 156 valid questionnaires were
returned with an effective rate of 85.71 per cent. Overall, in the final 156 valid
questionnaires, traditional enterprises, high-tech industries and knowledge-intensive
services (KIBS) accounted for 37.18, 12.82, and 12.82 per cent of the enterprises studied,
while private enterprises and state-owned enterprises accounted for 59.62 and 21.15 per cent
of all, respectively. The distribution of enterprises’ growth year and the number of
employees are reasonable (Table I).
Measures
We used standard questionnaires to collect data for this research. Once a draft questionnaire
was developed, we obtained feedback from several academic and managerial experts.
Feedback from these experts was then considered and integrated into the final version of the
questionnaire. The original questionnaire was developed in English, and we translated it
into Chinese using a typical careful translation/back-translation process to ensure accuracy
and consistency (Beaton et al., 2000). Several Chinese researchers and managers were invited
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Table I.
Sample features
Sample feature
Industry type
Traditional enterprises
High-tech enterprises
KIBS
Commerce and others
Sample size Proportion (%) Sample feature
58
20
20
58
37.18
12.82
12.82
37.18
93
33
30
59.62
21.15
19.23
Sample size Proportion (%)
Firm age
#8 years
9-12 years
13-19 years
Over 20 years
51
28
20
57
32.69
17.95
12.82
36.54
Number of employees
<100
100-499
500-4999
Over 5000
49
41
40
26
31.41
26.28
25.64
16.67
Owner-ship
Private enterprises
State-owned enterprises
Foreign enterprises and
others
to check whether the Chinese version of the questionnaire was totally clear. Based on their
feedback, a few minor changes were applied to increase clarity. Furthermore, the use of a
multi-respondent data collection procedure (i.e. two respondents per firm) minimizes the
possibility of common source bias. We measured our predictor variables and moderator
variables using a seven-point Likert scale (from “1” = not at all or strongly disagree to “7” =
“to a very great extent or strongly agree”). Harman’s single-factor test was used to examine
potential common method bias (Podsakoff and Organ, 1986). The results of the exploratory
factor analysis (EFA) of all items in the model show that four factors had eigenvalues
greater than 1. In addition, the first factor explained 29.46 per cent of the variance. This
variance was less than 50 per cent; therefore, common method bias was unlikely to be a
problem.
Predictor variable
Digital transformation strategy. DTS was measured using 11 items developed by Hess et al.
(2016). Based on their case studies of digital transformation, they have provided a list of 11
strategic decisions questions for DTS. An example item is “The firm is at the forefront of
innovating new digital technologies.” Moreover, Hess et al. (2016) have grouped the 11 strategic
decisions questions along the three dimensions of the DTS except for financial aspects: use of
digital technologies, changes in value creation and structural changes. EFA indicates DTS
indicators have sufficient information extraction quantitates (>0.5), explanation rate of
variance (66.801 per cent) and well-documented reliability (Cronbach’s a = 0.949).
Moderator variables
Cognitive conflict. The cognitive conflict was measured using four items developed by
Bedford et al. (2019) (Cronbach’s a = 0.909 in the current research). An example item is “How
often do members of your senior management team disagree about the content of strategic
decisions?”.
Outcome variable
Performance. Three types of performance measures are used regularly in the strategy
literature (objective financial performance, subjective financial performance, and subjective
nonfinancial performance). First, as Banker et al. (2000) said, current nonfinancial measures
are better predictors of long-term financial performance than current financial measures.
Second, because of the prevalence of private firms, data on objective financial performance
were not usually available for private firms (Newbert, 2008). Third, the research suggests
that perceptual measures of performance correlate well with objective measures (Powell,
1992). So:
long-term financial performance was measured by nonfinancial performance; and
all performance was measured via subjective financial performance.
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conflict
Subjective financial performance was measured using four items (ROS = Return on Sales,
ROA = Return on Assets, ROE = Return on Equity and ROI = Return on Investments
compared to its direct competitors over the last three years. “1” = much lower to “7” =
“much higher”) used by Newbert (2008). Subjective nonfinancial performance was measured
using four items (“market share,” “product and service quality,” “customer satisfaction” and
“productivity” compared to its direct competitors over the last three years. “1” = much lower
to “7” = “much higher”) mentioned by Said et al. (2003) and Banker et al. (2000). EFA, both
subjective financial indicators and subjective nonfinancial indicators, have sufficient
communality extraction (>0.7), explanation rate of variance (42.785 and 38.624 per cent) and
both financial and nonfinancial indicators have a well-documented reliability
(Cronbach’s a = 0.898, Cronbach’s a = 0.945).
451
Control variables
We controlled for six generally accepted firm characteristics, i.e., age, size, industrial type,
ownership, TMT size and firm’s past performance. Because both age and size may have a
significant influence on entrepreneurial SMES’ performance, competition through digital
platforms (Cenamor et al., 2019) and digital business strategy (Mithas et al., 2013). Chanias
et al. (2019) revealed that unlike born-digital organizations, pre-digital organizations often
need to change their entire organization, business model, and processes (Bharadwaj et al.,
2013; Sebastian et al., 2017; Tumbas et al., 2017), indicating that enterprises of different
industry types have different strategies and behaviors for the digital age. Current research on
strategic management indicated that the diversity of ownership is one of the most important
context factors (Li and Peng, 2008; Peng and Luo, 2000). Enterprises that have different
ownership belong to different strategic groups (Peng et al., 2004) and have different
reactions to the system and environment. Age refers to the number of years after the firm’s
creation, and size refers to the average number of employees within the last three years. Both
the industrial type and ownership are dummy variables. We control for firm’s past
performance, measured as the company’s average sales in the past three years. A number of
studies have confirmed that the characteristics of TMT will affect the manager’s cognitive
model and organizational performance. Therefore, we control for the size of TMT for
different organizations, measured as the number of TMT members.
Results
Confirmatory factor analyses
To test whether our measured variables are distinguishable, confirmatory factor analysis
(CFA) was conducted at the firm level. The analysis results showed that the four-factor
model (i.e. DTS, cognitive conflict, subjective financial performance and subjective
nonfinancial performance) yield a good fit ( x 2= 318.282, p < 0.001; df = 224; TLI = 0.964;
CFI = 0.968; RMSEA = 0.052). Furthermore, all measurement items loaded significantly.
Table II.
Mean, standard
deviation and
correlation values for
all study variables
(N = 156)
2
3
4
5
6
7
8
9
10
11
12
13
Notes: *p < 0.05; **p < 0.01 (two-tailed)
1. Traditional manufacturing
1
2. High-tech manufacturing
0.295** 1
3. KIBS
0.295** 0.147
1
4. Private enterprises
0.255** 0.081 0.192* 1
5. State-owned enterprises
0.334** 0.058
0.130 0.629** 1
6. Firm age
0.146
0.080 0.128 0.028 0.179*
1
7. Firm size
0.040
0.175*
0.064 0.182* 0.318** 0.487** 1
8. TMT size
0.075
0.108
0.075 0.125 0.262** 0.348** 0.690**
1
9. Sales
0.102
0.162
0.072 0.196* 0.380** 0.452** 0.790**
0.666** 1
10. DTS
0.114
0.202*
0.098 0.073 0.155 0.011 0.242**
0.241** 0.357** 1
11. Cognitive conflict
0.170*
0.205*
0.205* 0.033 0.032 0.050 0.165*
0.111 0.214** 0.384** 1
12. Short-term financial performance 0.086
0.238** 0.132 0.037 0.184*
0.081 0.237** 269**
0.341** 0.440** 0.453** 1
13. Long-term financial performance 0.075
0.234** 0.118 0.012 0.037
0.015 0.225**
0.292** 0.311** 0.613** 0.580** 0.619** 1
Mean
0.372
0.128
0.128
0.596 0.212
3.462 2.763
2.474 4.288 4.628
3.386
4.532
4.471
Std. dev.
0.485
0.335
0.335
0.492 0.410
1.388 1.727
1.161 1.924 1.425
1.341
1.687
1.486
1
452
Variable
IJCMA
31,3
Model S1
Notes: †p < 0.1; *p < 0.05; **p < 0.01; ***p < 0.001
#3.335
0.365
0.156
7.527***
0.131 (0.287)
0.174* (0.392)
0.095 (0.376)
0.108 (0.298)
0.206* (0.396)
0.008 (0.099)
0.159 (0.118)
0.131 (0.139)
0.151 (0.106)
0.220** (0.092)
0.313*** (0.095)
0.146†(0.273)
0.180* (0.379)
0.070 (0.361)
0.103 (0.283)
0.200* (0.377)
0.008 (0.094)
0.160 (0.112)
0.161†(0.133)
0.124 (0.101)
0.449*** (0.109)
0.308** (0.128)
0.181* (0.083)
0.245*(0.045)
#3.315
0.435
0.069
8.393***
Short-term financial performance
Model S2
Model S3
Traditional manufacturing
0.133 (0.317)
High-tech manufacturing
0.274*** (0.423)
KIBS
0.175* (0.409)
Private enterprises
0.118 (0.330)
State-owned enterprises
0.206† (0.436)
Firm age
0.082 (0.107)
Firm size
0.162 (0.131)
TMT size
0.119 (0.154)
Sales
0.328* (0.113)
DTS
Cognitive conflict
DTS * Cognitive conflict
DTS * Cognitive conflict 2
VIF
#3.298
0.209
R2
4R2
0.209
F
4.293***
Variable
#3.335
0.202
0.202
4.040**
#3.338
0.586
0.384
18.272***
0.104 (0.201)
0.085 (0.272)
0.032 (0.262)
0.008 (0.208)
0.050 (0.275)
0.020 (0.069)
0.147 (0.083)
0.252** (0.098)
0.011 (0.074)
0.480*** (0.065)
0.361*** (0.067)
0.100 (0.194)
0.045 (0.268)
0.003 (0.255)
0.010 (0.200)
0.033 (0.266)
0.004 (0.067)
0.153 (0.080)
0.267*** (0.095)
0.020 (0.072)
0.496*** (0.077)
0.154† (0.092)
0.258*** (0.059)
0.222* (0.032)
#3.347
0.620
0.034
17.592***
Long-term financial performance
Model L2
Model L3
0.120 (0.276)
0.245** (0.366)
0.143†(0.354)
0.027 (0.286)
0.033 (0.378)
0.132 (0.093)
0.173 (0.114)
0.252* (0.136)
0.316* (0.098)
Model L1
Role of
cognitive
conflict
453
Table III.
Standardized
regression
coefficients (N = 156)
IJCMA
31,3
Descriptive statistics
The means, standard deviations and correlations of all variables are shown in Table II. Two
sets of statistics are worthy of note in Table II. As we are interested in how DTS and
cognitive conflict would have an impact on short-term financial performance and long-term
financial performance, we find that all correlations among them are significant (p < 0.01).
454
Hypothesis testing
The influence of digital transformation strategy on performance. To test H1 and H2, we
conducted regression analyses (Table III). We controlled firm age, size, industrial type,
ownership, TMT size and sales in all analyses. Then, we added the effect of DTS and
cognitive conflict on short-term financial performance and long-term financial performance
(Model S2, Model L2). As shown in Table III, the standardized regression coefficients of DTS
were positive ( b = 0.220, SE = 0.092, p < 0.01; b = 0.480, SE = 0.065, p < 0.001), indicating
a positive relationship of DTS with both short- and long-term financial performance. These
results supported H1 and H2. The R2 and the adjusted R2 values are 0.365 and 0.156 (Model
S2), 0.586 and 0.384 (Model L2), respectively, suggesting that DTS and cognitive conflict
explains 15.6 per cent (38.4 per cent) of the variance of short-term (long-term) financial
performance. This means DTS and cognitive conflict have much more significant impact on
long-term financial performance.
Moderation effect of cognitive conflict. H3 and H4 suggest that the positive relationship
of DTS on short-term financial performance and long-term financial performance were
moderated via cognitive conflict. As shown in Model S3 and Model L3, the interaction
between DTS and cognitive conflict has a positive relationship with short-term financial
performance ( b = 0.1811, SE = 0.083, p < 0.05) and long-term financial performance ( b =
0.258, SE = 0.059, p < 0.001); however, the interaction between DTS and cognitive conflictsquared has a negative relationship with short-term financial performance ( b = 0.245,
SE = 0.045, p < 0.05), thus fully supporting H3. The interaction between DTS and cognitive
conflict-squared has a positive relationship with long-term financial performance ( b =
0.222, SE = 0.032, p < 0.05). Thus, the results do not show significant inverted U-shaped
relationship, thereby H4 is not supported. The R2 and the adjusted R2 values are 0.435 and
0.069 (Model S3), respectively, suggesting that the interaction between DTS and cognitive
conflict and DTS and cognitive conflict-squared explain 6.9 per cent of the variance of shortterm financial performance.
Then, we computed the curves between DTS and short-term (long-term) financial
performance for low (< 1SD), moderate (1SD < X < þ1SD) and high (> þ1SD)
cognitive conflict and graphed the results as per Aiken and West’s (1991) suggestions, as
shown in Figure 2.
Figure 2.
Relationship between
DTS and
performance: inverted
U-shaped moderating
effect of the cognitive
conflict
Discussion
Currently, digital transformation has become the trend of societal, economic and industrial
development; moreover, it has been actively conducted by enterprises. However, enterprises
rarely succeed in implementing digital transformation and achieving favorable
performance. This study was based on the view of fusion between the IT/IS strategy and
business strategy; moreover, it focused on the corporate strategy level rather than function
level such as IT/IS and business units. This study explored how DTS influences the shortand long-term financial performance, and the boundary conditions of TMT’s cognitive
conflict on the improvement of organizational performance delivered by DTS. By examining
156 Chinese enterprises, we determined that DTS can promote both short- and long-term
financial performance. The cognitive conflict of TMT is shown to have an inverted Ushaped moderating effect on the relationship between DTS and short-term financial
performance, while it has a positive moderating effect on DTS and long-term financial
performance. The inverted U-shaped moderating model of TMT’s cognitive conflict
indicated a complex mechanism by which DTS improves organizational performance,
indicating that enterprises should pay attention to different opinions of TMT members
during the formulation and implementation of the DTS.
Theoretical implications
The current results have several theoretical contributions to the existing research:
Hess et al. (2016) and Matt et al. (2015) proposed that the strategic framework of
digital transformation is a multi-dimensional concept involving the use of new
technologies, changes in value creation and structural changes. This study
demonstrated that the 11 digital transformation strategic issues proposed by them
constitute only one construct (factor loading > 0.7, Cronbach’s a = 0.949). This
result indicated that the fact that digital transformation is a strategic issue rather
than technical issue (Rogers, 2016; Besson and Rowe, 2012; Li et al., 2017) has been
generally accepted. Thus, comprehensive changes in product and service,
organizational structure and business model and processes are required for
enterprises to achieve DTS (Hess et al., 2016; Bharadwaj et al., 2013; Sebastian et al.,
2017; Tumbas et al., 2017).
Competition has compelled firms to implement strategic management to overcome
dissatisfaction with traditional short-term financial measurement systems (Said
et al., 2003). Thus, we emphasize the use of a combination of financial and
nonfinancial performance measures. In the Chinese context, this study further
confirmed the effect of using digital technologies and digital transformation on
promoting organizational performance. The results showed that DTS could
significantly improve both short- and long-term financial performance. Thus, this
study sheds new light on the improvement of organizational performance delivered
by digital transformation and provides invaluable support for enterprises to realize
digital transformation.
This study effectively bonded the theories of DTS and conflict management using
decision-making theory. The tangible effect of digital transformation strategic
decision-making on the organizational performance was found to be dependent on
the cognitive conflict of TMT members. This result further verified the boundary
conditions for the improvement of organizational performance delivered by DTS.
The short-term financial performance benefits more from DTS when a TMT’s
cognitive conflict is moderate rather than high or low. However, the long-term
Role of
cognitive
conflict
455
IJCMA
31,3
456
financial performance benefits more from DTS when a TMT’s cognitive conflict is
high compared with when it is moderate or low. To our knowledge, very few studies
have focused on the importance to the practical value of cognitive conflict for DTS
decision, especially for the curvilinear moderating relationship of strategic decision
and performance.
Practical implications
China’s industrial policies to promote the development of the digital economy and firm’s
digital transformation experiences are beneficial for other countries and non-Chinese
organizations. Specifically, this research provides suggestions for managerial practice.
Given that DTS has a positive relationship with short-term financial performance
and long-term financial performance, managers should undertake digital strategy
immediately. The development and use of digital technologies, redesign of the
business model and adjustment of the organizational framework need to be
fundamentally changed to achieve digital strategy through continuous iteration and
development.
Given that cognitive conflict has an inverted U-shaped moderate effect on the
relationship between DTS and short-term financial performance, managers should
task appropriate tactics to undertake conflict management by monitoring TMT’s
cognitive conflict at different degrees. Thus, the managers of enterprises need to
play a key role in managing conflict. Firstly, they should build a corporate culture,
which encourages innovations, tolerates failures and allows each TMT member to
own and express his or her own opinions. Secondly, they should pay full attention to
different opinions of each TMT member and conduct in-depth discussions among
members to reach consensus.
Furthermore, because high cognitive conflict would lead to a series of adverse
consequences such as suppression of information exchange, affective conflict and
barriers to effective communication, top managers of enterprises must be good at
coordinating conflict and keeping cognitive conflict within a reasonable range and
extent. Because of the positive moderating effect of TMT’s cognitive conflict on the
relationship between DTS and long-term financial performance, enterprise
managers should control the range and degree of cognitive conflict according to
different strategic objectives.
Limitations and future research directions
Despite the importance of this research, our results have certain limitations. First, the
generalization of the results might be influenced by sample size, sample source and
the deviation of homology method. The simple delivery and collection channels of the
questionnaires limited the representation of the sample enterprises. The sample source
based on the relationship with friends, business partners, students and officials limited the
universality of the research results. Moreover, although we considered certain skills to avoid
the potential common method bias, the data of DTS, cognitive conflict and organizational
performance could not be fully assured from different TMT members.
Extensive discussions have been conducted from the perspectives of IT/IS; alignment,
fusion and combination with business and digital business strategy has been proposed
(Nadeem et al., 2018; Bharadwaj et al., 2013). However, the relationship of digital, business
and IT strategies has not been clearly explored. In particular, the definitions of digital
strategy and DTS have not been explored from the perspective of strategic management.
Thus, the definitions of digital strategy and DTS remain unclear and inconsistent because
current studies have explored these definitions only from the perspective of basis conceptual
(Chanias et al., 2019) and decision-making practices (Hess et al., 2016). Therefore, a clear
definition and measurement methods of the DTS are required. In this study, the
measurement method mentioned was based on the key decisions in digital transformation
strategic decision-making proposed by Hess et al. (2016). Thus, research on the definitions of
digital strategy and DTS and its measurement methods need to be examined from the
perspective of strategic management.
Considering the complexity of DTS decision-making, value creation and the uncertainty
of returns (Warner and Wäger, 2019), this study proposed and verified the complex
moderating effect of TMT’s cognitive conflict on the relationship between the DTS and
organizational performance. However, limitations remain in the conflict type, mutual
evolution and coordination management such as relationship conflict. Thus, further
research is required to explore other context and moderator variables. In particular, focus
would be on strategic actors’ cognition and emotion (Luce et al., 1999; Broniarczyk and
Griffin, 2014; Anderson, 2003), mood, motivation, social and political interactions as well as
background in decision-making (Jarzabkowski, 2005; Jarzabkowski and Spee, 2009;
Whittington, 2006). Furthermore, considering the complicated processes with regard to DTS
and coordinating conflict, more variables should be explored to improve the quality and
reliability of the results. Such as TMTs’ demographic characteristics and heterogeneity,
firm’s past performance, and Chinese particular cultural configuration.
Conclusion
In the digital economy age, digital technologies can significantly influence corporate
functional departments, such as IT/IS and business operation, and comprehensively change
the organizational business model, structure and processes. Thus, the implementation of
digital transformation has become a strategic management issue for companies. In the
Chinese context, this study indicated that the implementation of a DTS could be beneficial to
improve short- and long-term financial performance and provide robust evidence for
enterprises to formulate a DTS. Moreover, by integrating theories of skewed conflict and
minority dissent and too-much-of-a-good-thing effect, this study showed the inverted Ushaped moderating effect of cognitive conflict on improving organizational performance via
digital transformation and guiding enterprises to coordinate conflicts and make strategic
decisions. Furthermore, we expect that our results can enlighten researchers to develop more
detailed explanations for the psychology and social interactions acting on DTS making and
make managers aware of the contingency nature of conflicts between DTS and performance.
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Corresponding author
Junzheng Feng can be contacted at: firefly0810@hdu.edu.cn
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