Achieving novelty and efficiency in business model design: Striking a balance between IT exploration and exploitation

Journal Pre-proof Achieving Novelty and Efficiency in Business Model Design: Striking a Balance between IT Exploration and Exploitation Yao Chen (Conceptualization) (Formal analysis) (Methodology) (Software) (Writing - original draft) (Writing - review and editing), Hefu Liu (Supervision) (Project administration) (Conceptualization) (Data curation) (Resources) (Writing - original draft) (Writing review and editing), Meng Chen (Conceptualization) (Formal analysis) (Methodology) (Software) (Writing - original draft) (Writing - review and editing)

PII:

S0378-7206(18)30759-6

DOI:

https://doi.org/10.1016/j.im.2020.103268

Reference:

INFMAN 103268

To appear in:

Information & Management

Received Date:

7 September 2018

Revised Date:

6 January 2020

Accepted Date:

11 January 2020

Please cite this article as: Chen Y, Liu H, Chen M, Achieving Novelty and Efficiency in Business Model Design: Striking a Balance between IT Exploration and Exploitation, Information and amp; Management (2020), doi: https://doi.org/10.1016/j.im.2020.103268

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Achieving Novelty and Efficiency in Business Model Design: Striking a Balance between IT Exploration and Exploitation

Yao Chen School of Management University of Science and Technology of China 96 Jinzhai Road, Hefei, China, 230026 [email protected]

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Meng Chen* Research Center for Smarter Supply Chain Dongwu Business School Soochow University 50 Donghuan Road, Suzhou, China, 215006 [email protected]

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Hefu Liu School of Management University of Science and Technology of China 96 Jinzhai Road, Hefei, China, 230026 [email protected]

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Submitted to the special issue of “Digital Business Transformation in Innovation and Entrepreneurship” *Corresponding author

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This work was supported by the National Natural Science Foundation of China (NSFC: 71622009, 71971202, and 71921001), the National Key R&D Program of China (2018YFB1601401), and the China Scholarship Council (CSC: 201706340023)

Abstract

Digitalization is encouraging an increasing number of firms to design their business models based on information technology (IT) for exploring business opportunities. This study examines the effect of the balance (imbalance) between IT exploration and exploitation on novelty-centered business model design (NBMD) and

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efficiency-centered business model design (EBMD). Using matched data from the IT-related executive and chief executive officer of 183 firms, this study finds that IT exploration is positively related to NBMD and EBMD and that IT exploitation is positively related to only EBMD. NBMD and EBMD are significantly related to firm performance. Polynomial regression and response surface analysis reveal that NBMD and EBMD first decline and then rise with the increase in the level of balance between IT exploration and exploitation. NBMD declines but EBMD rises with the increase in the level of imbalance between IT exploration and exploitation. This study

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contributes to the understanding on leveraging IT capability to influence the business model design and firm performance.

Keywords: IT exploration; IT exploitation; novelty-centered business model;

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efficiency-centered business model; ambidexterity; organizational learning

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1. Introduction

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Digitalization is encouraging an increasing number of firms to design their business models based on information technology (IT) for exploring business

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opportunities [1, 2]. Business model design is thus the main driving force in entrepreneurial opportunity creation [3-5]; as a result, the entrepreneurship literature

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has applied such design, rather than traditional resource possession, to explain

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variance in firm performance [4]. However, transforming IT into new ways of creating business value requires firms to differentiate their business models [6]. For example, IT is “changing the way innovation and entrepreneurship are conceived, initiated and executed and managed” [7]. IT capability, which reflects firms’ ability to leverage IT to support business processes and strategies, is a critical enabler for efficiency [8] and innovation [9]. A large amount of resources have been invested in

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developing IT capability to aid in the design of business models, expecting to realize superior firm performance. However, firms are challenged by the deployment of appropriate IT capability to support the choice of achieving novelty or efficiency in business model design [10]. Although scholars have extensively proclaimed the important role of IT capability in business model design [e.g.,1], our understanding of such a role is still

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limited. Specifically, empirical research has provided limited insights into the impact

of IT capability on various types of business model designs [11]. Business model design can be categorized into the novelty-centered business model design (NBMD)

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and efficiency-centered business model design (EBMD) [11]. The former focuses on

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conducting business using novel approaches, whereas the latter focuses on organizing boundary-spanning activities to achieve enhanced transaction efficiency [11, 12]. The

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two design themes are not mutually exclusive and coexist in any given business

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model [13, 14]. IT uniquely enables firms to not only develop novel business processes for facilitating NBMD but also optimize existing processes for improving

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EBMD [6]. However, due to their various entrepreneurial orientations [11, 12], firms are compelled to pursue NBMD and EBMD, both of which are critical for firm

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performance [11, 13]. Although firms actively manage their IT capability to support business model design [15], specifying their IT capability to support NBMD and EBMD remains a challenge. Firms not only exploit existing IT resources and practices (IT exploitation) but also experiment with new IT resources and practices (IT exploration) [16] to facilitate

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their business model design [17]. Recent information systems (IS) literature has proposed the importance of IT ambidexterity, namely, the simultaneous pursuit of IT exploration and exploitation, for organizational operations [16, 18, 19]. However, firms cannot always reach IT ambidexterity because of resource limitation [20] and different entrepreneurial motives [12]. Firms often encounter a dilemma in allocating a given amount of IT budgets in IT exploration or exploitation [20]. Under this

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condition, extant IS research has helped us understand the importance of IT ambidexterity but has failed to fully explain neither the direction of imbalance nor the

level of balance between IT exploration and exploitation [e.g., 15, 16]. Therefore, we

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should extend the perspective of IT ambidexterity and explore how firms

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simultaneously seek IT exploration and exploitation at equally low or high levels (indicating balanced levels) or pursue either IT exploration or exploitation in varying

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degrees (indicating imbalanced levels) to support the EBMD and NBMD.

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We build on organizational learning theory to examine the complex and nuanced relationships between the two types of IT capability, business model design, and firm

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performance. Organizational learning theory states that the generation and development of distinctive competencies that enable firms to improve organizational

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outcomes rely on organizational learning [21]. Thus, we argue that developing EBMD and NBMD will have different learning needs and may thus require different types of IT capability. Since IT exploration and exploitation act as different enablers of organizational learning to help firms create, transfer, and apply knowledge [8, 22, 23], we propose that the two types of IT capability could support EBMD and NBMD.

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We also investigate the joint effect of IT exploration and exploitation on EMBD and NBMD. The two types of IT capability may function as substitutes or complements because of their different foci in leveraging IT support [24, 25]. Although some scholars have suggested the necessity of building “ambidexterity” [26, 27], others have mentioned the possibility of the “explicit and implicit choices” between the two types [24, 28]. We try to break through these opposing views by

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examining the distinguished impact of the balance and imbalance between IT

exploration and exploitation on NBMD and EBMD. We test the research model using

183 samples gathered through a matched survey of IT-related executives and chief

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executive officers (CEOs). Our use of structural equation modeling, polynomial

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regression, and response surface analysis provides certain support to the model. We endeavor to contribute to existing research in two ways. First, we are expected

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to contribute to the IS and entrepreneurship literature by revealing the complex

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linkages between IT capability and business model design. Prior studies have theoretically considered the impact of IT on business model design [e.g., 1, 6] without

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the exposition of IT capability. We extend this theorization by integrating perspectives from organizational learning and entrepreneurship literature and

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empirically validating IT capability as a critical enabler of business model design. Second, we endeavor to extend IT ambidexterity research by examining the distinguished impact of the balance and imbalance between IT exploration and exploitation on NBMD and EBMD. Our study highlights the necessity to understand

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the strategic management of IT exploration and exploitation for enhancing NBMD and EBMD.

2. Theoretical Background and Hypothesis Development

2.1 Organizational learning theory

Organizational learning theory suggests that organizational learning facilitates

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the generation and development of distinctive competencies that enable firms to

improve organizational outcomes [21]. Specifically, organizational learning reflects the dynamic process of generating, transferring, and applying knowledge to where it

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is needed [23]. This theory further indicates two forms of learning: exploration and

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exploitation [24]. Exploration involves the development of novel knowledge and opportunities, whereas exploitation reflects the reuse and refinement of existing

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knowledge [23, 24]. Exploration and exploitation are extensively recognized as the

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two generic processes that drive entrepreneurship in firms [29]. Existing literature recognizes exploration and exploitation as distinct learning

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activities that need to be appropriately managed [24]. Firms often need to involve sufficient exploration for ensuring future prosperity and simultaneously devote

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sufficient exploitation for guaranteeing existing viability [30]. Thus, the importance of the simultaneous pursuit of exploration and exploitation (i.e., organizational ambidexterity) has increasingly been recognized [24, 31]. However, exploration and exploitation are inherently in conflict because they compete for organizational resources, attention, and routines [27, 28, 32]. March [24] indicated that organizations

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encounter a trade-off in allocating resources to either exploration or exploitation when resources are limited. In this case, firms are advocated to specialize in either exploration or exploitation [24, 33]. Given the benefits and resource allocation conflict of exploration and exploitation, firms often endeavor to find a proper strategy to manage exploration and exploitation for survival and prosperity [32, 34]. The entrepreneurship literature has referred to the business model design as the

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outcome of organizational learning [35]. Organizational learning can facilitate firms’

understanding of their previous experience and external environment to successfully renew their business models and enhance their entrepreneurial outcomes [36, 37].

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Organizational learning, for example, enables firms to come up with a new

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transactional content, structure, and governance configurations by accumulating experiences and newly created knowledge [37]. Sosna, Trevinyo-Rodriguez, and

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Velamuri [35] corroborated the importance of experimentation and trial-and-error

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learning in business model innovation. Therefore, exploration and exploitation are important learning activities that contribute to business model design.

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IT capability can be considered an enabler of organizational learning because it facilitates firms to create, transfer, and apply knowledge [8, 22, 23]. For example,

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Alavi and Leidner [38] affirmed that IT enables the creation, storage, transfer, and application of knowledge within organizations. Iyengar, Sweeney, and Montealegre [8] conceptualized IT use as an organizational learning mechanism and argued that IT use helps

firms

collect,

store,

and

disseminate

knowledge.

Alternately,

the

entrepreneurship literature has contended that organizational learning significantly

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serves in innovating and reshaping business models [35]. Accordingly, IT capability as an enabler of organizational learning not only facilitates the collection and interpretation of knowledge to capture entrepreneurial opportunities but also supports knowledge integration and its application to reshape modes of transactions, thereby spurring a rethink of business model design.

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2.2 Business model design and firm performance A business model is an organizational blueprint for value creation of entrepreneurial opportunities through the design of transaction content, structure, and

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governance [39]. Prior studies have characterized business models with two design

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themes: NBMD and EBMD [11-13, 40]. NBMD focuses on conducting business using novel approaches (e.g., linking partners in a new way), whereas EBMD organizing

boundary-spanning

activities

to

achieve

enhanced

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emphasizes

transactional efficiency (e.g., reducing transaction costs) [41]. The two types of

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business model design themes are neither orthogonal nor mutually exclusive [11]. Zott and Amit [11] indicated that NBMD and EBMD are not exhaustive and “may

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be present in any given business model” (p. 182). Prior literature has confirmed that

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business model design is critical to preserve an entrepreneurial environment in a firm [5, 41, 42]. Thus, facilitating a business model design is attractive and significant in ensuring renewable and sustainable competitiveness in firms. Literature has widely proposed that business model design is critical for enhancing firm performance [43-46]. Specifically, NBMD can create and capture new value for firms to improve firm performance [11, 13]. First, NBMD enables firms to 8

create and capture new value by conducting transactions in novel patterns [11]. NBMD helps firms innovate existing transaction patterns with novel ways and even develop completely novel market segments [11]. In this regard, firms can enjoy first-mover advantages and capture additional value [1, 39, 47]. Second, NBMD helps firms capture additional value by increasing the switching costs of partners [11]. NBMD enables firms to build unique competitive advantages with novel knowledge

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and valuable resources that cannot be quickly replicated and easily acquired

elsewhere [11, 13]. Thus, firms can increase the switching cost of partners and obtain bargaining power to appropriate additional value [11].

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EBMD can enhance firm performance by creating and capturing value through

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decreased transactional costs [48]. EBMD enables information asymmetry reduction by facilitating information flow among stakeholders and simplifies transaction

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processes to reduce transaction uncertainty and complexity [49]. Therefore, firms can

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improve transaction efficiency and reduce transactional costs, which improve firm performance [48]. Simultaneously, EBMD enables firms to increase the pool of

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potential partners and reduce the switching cost of replacing partners [11]. Thus, firms may improve their bargaining power over partners to capture additional value [11].

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Accordingly, we propose that H1. The more novelty-centered a firm’s business model design, the higher is the firm’s performance. H2. The more efficiency-centered a firm’s business model design, the higher is the firm’s performance.

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2.3 IT capability and business model design IT capability reflects a firm’s ability to deploy various IT-related resources in supporting its business processes and strategies [50, 51]. According to the distinction between “exploration” and “exploitation” in the organizational learning literature [24], existing IS researchers have categorized IT capability into IT exploration and

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exploitation that provide firms with distinct IT support [16, 52, 53]. Specifically, IT exploration involves the exploration of promising ITs and experimentation with new

IT resources and practices, such as IT applications, skills, and architecture [16, 18]. IT

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exploitation involves the management of existing IT resources and practices in

different business activities, integration of technologies based on the business process,

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and investment in complementary technologies [16, 18]. Recent literature not only

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presents the independent roles of the two types of IT capability but also realizes the importance of IT ambidexterity, that is, the simultaneous pursuit of IT exploration and

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exploitation [16, 18]. For example, Lee et al. [16] operationalized IT ambidexterity as the product of IT exploration and exploitation at the item level and find that IT

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ambidexterity can improve organizational agility through operational ambidexterity.

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Tai et al. [18] followed Lee et al. [16] in operationalizing IT ambidexterity and find that IT ambidexterity can positively affect strategic decision support. Although March’s [24] original work on exploration and exploitation indicates

that the two types of organizational learning forms are fundamentally incompatible, existing IT ambidexterity research conceptualizes IT exploration and exploitation as orthogonal variables that can be simultaneously achieved at high levels [e.g., 16, 18].

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Existing IS research has operationalized IT ambidexterity as the product of IT exploration and exploitation that cannot account for the direction of imbalance or the level of balance between IT exploration and exploitation [16]. Such conceptualization and operationalization limit the understanding of the role of IT exploration and exploitation in the context of business model design. Business model design is entrepreneurially oriented, which makes firms often encounter a trade-off in

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allocating the scarce IT budgets in either IT exploration or exploitation [20].

Therefore, firms have difficulty maximizing IT exploration and exploitation simultaneously [20]. However, empirical evidence on the relationship between

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business model design and the management of IT exploration and exploitation

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remains limited. The balance between IT exploration and exploitation refers to a scenario where a firm equally pursues both, whereas the imbalance indicates that IT exploitation is

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larger than IT exploration or vice versa. Low levels of balance do not indicate imbalance

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[54] but imply that IT exploration and exploitation are at equally low levels. High levels of balance indicate that IT exploration and exploitation are at equally high

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levels. However, no clear evidence affirms the effect of the level of balance on different business model design themes. In the case of imbalance, few studies have

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examined the effect of IT exploration and exploitation on business model design when IT exploration is high but IT exploitation is low and vice versa. Accordingly, we endeavor to investigate the individual and joint impacts of IT exploration and exploitation on business model design.

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2.3.1 Individual effects of IT exploration and exploitation

IT exploration as an enabler of exploration learning can promote firms to obtain and use knowledge for reshaping its business model design. We propose that IT exploration can support firms’ NBMD and EBMD. First, IT exploration enables firms to leverage diverse knowledge for improving the novelty of business model design [39]. The deployment of novel IT architectures can extend the reach and richness of

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firms’ knowledge base and enable the identification of novel opportunities [55]. Accordingly, firms can generate novel ideas in designing and implementing

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transaction content, structure, and governance. For example, Healx, which is a biotechnology corporation in England, adopts a novel artificial intelligence (AI)

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platform to collect disease data from various sources and develop a knowledge base

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covering over 7,000 rare diseases1. Healx can provide personalization by intelligently matching drug treatments for rare disease patients, which enables the creation of the

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new rare-disease markets [56].

Second, IT exploration can improve EBMD. The experimentation with new IT

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applications and practices introduces new and alternative knowledge domains, which

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lends new perspectives to understand firms’ existing transactions [52]. Thus, firms can reevaluate existing business, eliminate waste, and increase productivity in their transaction content, structure, and governance [12]. In this regard, firms can simplify transaction processes, and achieve considerable transaction efficiency and transaction cost reduction [57], which is the key of EBMD. For example, the adoption of AI

1

Source: https://healx.io/technology/ (Accessed March 3, 2019)

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platform enables Healx to broaden the knowledge base and significantly reduce the time, cost, and risk to discover rare disease drugs. Thus, Healx can efficiently match treatments with rare disease patients. In summary, we propose that H3a. The higher a firm’s IT exploration, the more novelty-centered is the firm’s business model design. H3b. The higher a firm’s IT exploration, the more efficiency-centered is the firm’s business model design.

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Similarly, we suggest that IT exploitation as an enabler of exploitation learning can improve the NBMD and EBMD. First, IT exploitation enables firms to refine and

reconfigure existing knowledge for improving NBMD. The effective utilization of

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existing IT resources improves the fine-grained integration of existing knowledge

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from internal and external sources [58]. Thus, firms can recombine and refine existing knowledge base (i.e., repackaging knowledge in different domains) to create new

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business opportunities and develop novel content, structure, and governance of

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transactions that differentiate them from competitors [59]. For example, leveraging on data warehousing systems helps in redesigning or developing products or services by

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gaining easy access to project information and best practices from prior projects [60]. Second, IT exploitation can support EBMD through enhanced knowledge

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integration and application [61]. IT exploitation enables firms to resolve differences in semantics and standards of data exchange [62], which facilitates the integration of knowledge from relevant partners. In this regard, IT exploitation facilitates timely knowledge and information exchange between partners and enables partners to profoundly understand each other’s needs; this situation further leads to transaction

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uncertainty reduction and efficiency improvement [61, 63]. For example, Zara, which is a Spanish apparel firm, optimizes its IT infrastructure to collect real-time transaction information and consequently compress transaction time [64]. In summary, we hypothesize that

2.3.2 Balance between IT exploration and exploitation

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H4a. The higher a firm’s IT exploitation, the more novelty-centered is the firm’s business model design. H4b. The higher a firm’s IT exploitation, the more efficiency-centered is the firm’s business model design.

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Given the importance of IT exploration and exploitation in business, prior research has asserted that firms can pursue a balanced IT strategy to cope with the

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changing business needs [16]. A balanced IT strategy indicates that IT exploration

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and exploitation are maintained at equal levels. Such balance can occur at a continuum from low to high levels of IT exploration and exploitation. When the level

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of balance increases, firms not only can create novel knowledge and update organizational memory but also can effectively refine and reconfigure the existing

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knowledge base [16]. Therefore, firms can drive organizational renewal and maintain

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transaction efficiency, thereby supporting NBMD and EBMD. For example, a security company called Merrill Lynch leverages high levels of both IT exploration and exploitation to develop an innovative and cost-effective business model [16, 65]. However, when IT exploration is balanced with IT exploitation at low levels, the firm will fail to not only conduct an active and precise experiment on promising IT resources and practices but also maximize the potential of existing IT resources and

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practices [16, 65]. In this case, firms will have difficulty accessing diversified knowledge and generating a seamless integration of existing knowledge. This situation damages the NBMD and EBMD. Therefore, we expect that when the level of IT exploitation and IT exploration increases in a balanced manner, the degree of EBMD and NBMD will also increase.

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H5a. The degree of NBMD is higher when the level of balance between IT exploration and exploitation is high compared to when the level of balance is low. H5b. The degree of EBMD is higher when the level of balance between IT exploration and exploitation is high compared to when the level of balance is low.

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2.3.3 Imbalance between IT exploration and exploitation

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Given the tightly controlled IT budgets [20], not all firms can achieve a highly balanced level of IT exploration and exploitation, that is successfully sustaining them

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at equally high levels. Therefore, discussing the imbalance effects of IT exploration and exploitation on business model design is necessary. Imbalance can be manifested

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in two directions: IT exploitation is larger than IT exploration or IT exploration is

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larger than IT exploitation. Given that NBMD focuses on the creation of novel transactions with existing or new partners [11], the development of novel transactions

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must not only acquire new knowledge to generate creative business processes or offerings but also ascertain capability to utilize and transform such new knowledge for implementation [10]. When a firm’s IT exploitation increasingly exceeds its IT exploration, the firm may run the risk of obsolescence in IT resource management [18]. Firms will acquire less new knowledge and restrict the innovation

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along with a specific trajectory [66]; this situation may narrow the scale of organizational learning and further restrict the effects of IT exploitation. Although a dose of IT exploration can bring in novel knowledge, it may be insufficient to temper the impacts of high IT exploitation due to the high requirements of NBMD in the novelty of knowledge [67]. Therefore, the overemphasis on IT exploitation compared with IT exploration may impede organizational renewal and limit the breadth of

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organizational learning. Accordingly, the adoption of novel transaction content, structure, and governance will be hindered.

Conversely, when IT exploitation is increasingly lower than IT exploration, the

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firm may lack sufficient capacity to assimilate and utilize new knowledge created by

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experimentation with promising IT resources and practices [68]. Excessive IT exploration has difficulty capturing the novel value without the continuous refinement

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of core and fundamental IT infrastructure and practices [69]. Although a dose of IT

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exploitation can help assimilate novel knowledge [53, 70], it may be insufficient to assimilate the large amount of novel knowledge required by NBMD. Therefore, the

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overemphasis on IT exploration can impede NBMD. Based on the above-mentioned reasoning, we expect that NBMD will decrease when the discrepancy between IT

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exploration and exploitation increases. Thus, we propose the following hypothesis: H6a. The degree of NBMD is lower as the imbalance between IT exploration and exploitation increases in either direction. By contrast, we expect EBMD to increase as the imbalance between IT exploration and exploitation increases in either direction. Contrary to NBMD,

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EBMD focuses on improving the efficiency of transactions, which can be achieved through either the reuse or extension of existing knowledge or the acquisition of novel knowledge [11]. Given that the efficiency nature of EBMD requires less novelty of acquired knowledge [71], novel knowledge can be considered a bonus component that supports EBMD. In a mismatched state in which IT exploitation is increasingly higher than IT exploration, firms may suffer the increased loss of the

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bonus component of novel knowledge. Nonetheless, the relatively high level of IT exploitation strengthens firms’ understanding of the existing knowledge base and

facilitates the reuse and refinement of this knowledge [61, 72]. Meanwhile, only a

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dose of IT exploration can be sufficient to help detect existing knowledge that has

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been partially utilized [67]. In this situation, firms can efficiently reuse and refine existing knowledge to improve EBMD.

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In a mismatched situation wherein IT exploitation is increasingly lower than IT

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exploration, firms may be at risk of insufficient application of existing knowledge. However, the lower level of IT exploitation compared with IT exploration also

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indicates that firms are increasingly focusing on the supporting role of IT exploration in firm operations [73]. Such a focus on IT exploration often helps firms to

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efficiently acquire and apply new transaction-specific knowledge [17] that acts as a bonus component for improving existing transaction efficiency [39]. In addition, a dose of IT exploitation can help firms assimilate acquired knowledge and recombine new knowledge with the existing knowledge base [18]. Thus, the organizational learning demand for EBMD is satisfied. Firms can easily and directly apply acquired

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knowledge to improve transaction efficiency because they are familiar with and understand the existing transaction processes [74]. In conclusion, EBMD will increase when IT exploration and exploitation become progressively discrepant. In other words, concentrating on either IT exploration or exploitation may be a viable option to improve EBMD. Thus, we hypothesize that

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H6b. The degree of EBMD is higher as the imbalance between IT exploitation and exploration increases in either direction. 3. Research Methodology

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3.1 Sample and data collection

The data used to test the hypotheses were obtained from an online survey

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conducted in China’s Yangtze River delta area. We worked with a local administrative

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institution, which is responsible for local industrial development. The institution provided us a sample pool of 1,200 domestic firms. With the help of officials in this

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institution, we obtained the contact information of the firms and issued a formal notification to invite managers of these firms to voluntarily participate in our online

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survey. We involved the institution to issue a notification, but we controlled the whole

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data collection process and emphasized the academic nature of our research in the cover letter of our online questionnaire. We specified that the measurement items of IT capability should be filled out by IT-related executives and the measurement items of firm performance and business model design should be filled out by the CEO of each firm. The dual-respondent method can help reduce the potential of common method bias [75]. 18

After the questionnaires from the IT-related executives and CEO were matched and incomplete data were eliminated, we retained 183 firms for data analysis. A response rate of 15.25% is indicated. The response and nonresponse groups were compared in terms of firm age, firm size, and industry type to test the potential influence of nonresponse bias. No significant difference is detected between the responding and non-responding groups. Therefore, the nonresponse bias is not a severe

respondents. Table 1. Profile of the sample firms and respondents (N = 183). Percentage

N

Percentage

<=100

Machinery and equipment

76

42%

57

31%

Food and beverage

25

14%

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N

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problem in our study. Table 1 presents the information of the sample firms and survey

101–200

62

34%

Chemicals

30

16%

201–300

31

17%

Medicine and biology

13

7%

301–400

13

7%

Wood products and furniture

12

7%

>=401

20

11%

8

4%

Firm age (years)

19

10%

<=5

25

14%

6–10

69

38%

54

30%

35

19%

Firm size

Other industries R&D department size 11–20 21–30

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31–40 >=41

40

22%

11–15

64

35%

>=16

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<=10

a

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Electronic

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Industry type

a

20

11%

IT department size

27

15%

<=2

117

64%

24

13%

3–5

38

21%

>=6

28

15%

Age of IT-related

Education level of CEO

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a

Executive

High school and below

13

7%

25–30

9

5%

Junior college

68

37%

31–40

62

34%

Undergraduate

64

35%

41–50

56

31%

Master degree or above

35

19%

>=51

28

15%

Missing

3

2%

Missing

28

15%

4

2%

Education level of IT-related

Age of CEO

Executive High school and below

5

3%

25–30

19

Junior college

69

38%

31–40

21

11%

Undergraduate

93

51%

41–50

73

40%

Master degree or above

13

7%

>=51

68

37%

Missing

3

2%

Missing

17

9%

Gender Gender of CEO

of

IT-related Executive 169

92%

Male

166

91%

Female

11

6%

Female

14

8%

Missing

3

2%

Missing

3

2%

No. of employees

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a

Male

3.2 Measurement

An English questionnaire was compiled on the basis of prior literature to ensure

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the content validity of the measurement items. We invited two IS and strategy

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management scholars to review the questionnaire. Following their comments and suggestions, we further amended the questionnaire to ensure the content validity of all

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items. We used the back-translation method to ensure the equivalence in meaning between the Chinese and English versions of the questionnaire [76]. The questionnaire

agree.”

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adopted a 5-point Likert scale, ranging from “1 = strongly disagree” to “5 = strongly

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Firm performance. The items for firm performance were adapted from Zhou,

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Chi, and Tse [77]. Firm performance reflects the sales growth, market share growth, profit growth, total assets growth, and competitiveness of the firm compared with their major competitors. We used subjective measurement in this study for two reasons [78]. First, it is difficult to collect reliable and complete objective performance data in China [76]. Prior studies have suggested a positive relationship between objective and

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subjective measurements of firm performance [79]. Second, the subjective measure of firm performance can reflect a more comprehensive evaluation on the achieved level of firm goals, including a set of both financial and non-financial aspects [80]. Business model design. NBMD reflects the degree of business model’s novelty, such as new connecting ways with different shareholders and novel combinations of products, information, and services [11]. EBMD reflects the degree of transaction

Strese, and Flatten [13] to measure NBMD and EBMD.

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improvements, such as transaction time and cost [11]. We adapted items from Brettel,

IT capability. IT exploration captures the firm’s capability to explore new IT

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resources and practices [16]. IT exploitation reflects the capability to use existing IT

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resources and practices [16]. We adopted items from Lee, Sambamurthy, Lim, and Wei [16] to measure IT exploration and exploitation.

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Controls. We controlled the firm size, firm age, IT department size, R&D

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department size, and industry type. First, firm size may influence the focal firm’s bargaining power and performance [11, 81]. We utilized the number of regular

ur

employees to measure firm size. Second, mature firms have more managerial experiences than startup ones, which may influence the business model design and firm

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performance [82]. We controlled firm age by using the number of years since founding. Third, the size of the IT and R&D departments may influence the implementation of business model design and affect firm performance. They were measured by the number of employees in the IT and R&D departments. Fourth, different types of industries have dissimilar characteristics, which may influence the design of the

21

business model and the creation of competitive advantages [83]. We included six dummy variables to measure the industry type, with other industries as the baseline. They are machinery and equipment, food and beverage, chemicals, medicine and biology, wood products and furniture, and electronic.

4. Data Analysis and Results

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4.1 Reliability and validity

We conducted a series of tests using SPSS 22.0 to test the reliability and validity of the measurement. Cronbach’s α and composite reliability (CR) were utilized to reflect

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the reliability of the measurements [84]. Table 2 exhibits that the values of Cronbach’s

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α and CR of all variables are greater than the benchmark of 0.70 [84], indicating good reliability.

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We tested the convergent validity of the measurement with the average variance

na

extracted (AVE) and the loading of all items. Table 2 shows that the AVEs of all variables are higher than the benchmark of 0.50, and the factor loadings of items range

ur

from 0.610 to 0.980 (Appendix). This finding confirms satisfactory convergent validity. We compared the relationship between the square roots of AVEs and the

Jo

inter-construct correlations to assess the discriminant validity [84]. Table 2 shows that the square roots of AVEs of all variables are higher than the inter-construct correlations. This result indicates adequate discriminant validity. As shown in Table 2, two inter-construct correlations are greater than 0.60. Although the two correlations are lower than the cutoff of 0.8 [85], we conducted the variance inflation factor (VIF) test to evaluate whether multicollinearity exists. The

22

VIFs of constructs range from 1.144 to 3.129 with a mean of 2.093. Given that the

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ur

na

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re

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values are lower than 10 [86], multicollinearity is not a serious problem in our study.

23

f 1

2

1. IT exploration

0.968

2. IT exploitation

0.695**

3

4

5

6

7

8

0.968

0.500

0.525**

0.773

4. NBMD

0.517**

0.449**

0.699**

0.777

**

0.457

**

0.591**

0.595**

0.843

−0.141

−0.154

−0.114

−0.089

n.a.

0.099

0.131

−0.011

n.a.

0.053

0.059

0.096

0.676** **

6. Firm age

−0.149

7. IT dept. size

0.072

0.071

0.094

8. R&D dept. size

0.037

0.006

0.069

0.032

−0.005

0.100

−0.004

0.006

9. Firm size Machinery

equipment

and

11. Food and beverage a

0.003

a

−0.092

12. Chemicals a

0.069

13.

−0.042

Medicine

biology 14.

a

*

−0.007

0.045

0.088

0.649

0.003

0.023

0.094

Jo ur na l

10.

*

Pr

0.440

Wood

and furniture

and

products

0.026

a

10

11

12

13

14

15

e-

3. EBMD

**

5. Firm performance

9

pr

Variables

oo

Table 2. Correlation matrix, reliability, validity, and descriptive statistics.

−0.118

−0.009

−0.013

0.061

0.083

0.013

0.014

0.077

−0.035

−0.094

−0.047

−0.040

0.013

0.008

0.074

0.003

−0.149* 0.009 0.160

n.a. 0.677**

n.a.

0.029

0.142

0.028

0.085

-0.027

0.101

−0.104

-0.090

−0.110

*

0.039

0.020

-0.017

−0.026

0.016

-0.042

−0.043

n.a. −0.335**

n.a.

−0.373**

−0.176*

n.a.

−0.233

−0.110

−0.122

−0.223**

−0.105

−0.117

−0.073

**

n.a. n.a.

15. Electronica

−0.009

0.023

0.031

−0.020

−0.067

−0.038

−0.062

−0.052

−0.047

−0.180*

−0.085

−0.095

−0.059

−0.057

n.a.

Mean

3.532

3.630

4.209

4.016

4.093

10.951

4.020

27.150

220.440

0.415

0.137

0.164

0.071

0.066

0.044

0.801

0.731

0.429

0.542

0.543

5.422

9.100

38.094

283.590

0.494

0.344

0.371

0.258

0.248

0.205

Cronbach’s α

0.966

0.966

0.888

0.905

0.896

AVE

0.937

0.937

0.598

0.604

0.710

S.D.

24

Note: p < 0.05,

**

p < 0.01, and

0.978 ***

0.898

0.914

f

0.978 *

0.925

oo

CR

p < 0.001. The diagonal elements are the square roots of AVEs. n.a. refers to not applicable. We measured the firm size using the number of

Jo ur na l

Pr

e-

pr

employees and the firm age using the number of years since founding. a Dummy variable.

25

4.2 Common method bias

We used procedural remedies and statistical tests to alleviate common method bias concerns [87]. First, we adopted procedural remedies, including ensuring respondent anonymity, separating the items of independent and dependent variables in different pages, and collecting variables from IT-related executives and CEOs [88]. Second, we

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conducted statistical tests to evaluate common method bias. We performed Harman’s one-factor test to assess the extent of common method bias. The results affirm four

constructs with eigenvalues greater than 1.0, which account for 68.906% of the

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variance; the first construct explains 20.331% of the variance. We also compared the fit of the one-factor model and that of the measurement model. The results show that the

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fit of the one-factor model (χ2(df) = 2398.55 (252)) is worse than that of the

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measurement model (χ2(df) = 603.19 (242)). Moreover, scholars have recognized that the significance of quadratic or interaction effects suggests common method bias may

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not inflate the results [88]. Respondents have difficulty theorizing quadratic or interaction effects [87]. Our use of polynomial regression indicates significant

ur

coefficients of IT exploration×IT exploitation on NBMD, thereby indicating that

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common method bias is not a concern. Thus, common method bias is not a serious concern in this study.

4.3 Structural model

We analyzed our main model using structural equation modeling with SmartPLS 2.0. SmartPLS is appropriate for exploratory research and has been extensively used in

26

the IS area [89]. SmartPLS is advantageous with small sample size and is recommended when the sample size is less than 250 [90]. Thus, SmartPLS is suitable

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for data analysis in this research.

Fig. 1. Path analysis of the research model.

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Note: * p < 0.05, ** p < 0.01, and *** p < 0.001.

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Fig. 1 presents the results of our structural model. The model explains 31.4%– 45.2% of the variance, thereby indicating good predictive power. H1 and H2 suggest

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that NBMD and EBMD are positively related to firm performance. Fig. 1 also indicates that NBMD (β = 0.345, p < 0.001) and EBMD (β = 0.347, p < 0.001) are significantly

ur

and positively related to firm performance, thereby supporting H1 and H2. IT

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exploration is significantly related to NBMD (β = 0.397, p < 0.001) and EBMD (β = 0.249, p < 0.05), thereby supporting H3a and H3b. No significant relationship exists between IT exploitation and NBMD (β = 0.181, t = 1.811), thereby rejecting H4a. However, IT exploitation is significantly and positively related to the EBMD (β = 0.351, p < 0.01), thereby supporting H4b.

27

4.3 Polynomial regression and response surface analysis

We used polynomial regression and response surface analysis [91-93] to test the balance and imbalance effects of IT exploration and exploitation on NBMD and EBMD (Hypotheses 5–6). The polynomial regression and response surface analysis are well suited to analyze the level to which combinations of two predictor variables (i.e., IT

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exploration and exploitation) relate to an outcome variable, particularly considering the balance between two predictors [94]. These methods also allow testing whether an imbalance in different directions has different effects or whether outcome differences

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exist when two predictor variables are balanced at various levels [54]. Therefore, our use of polynomial regression and response surface analysis can overcome the

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limitations of prior empirical research on IT ambidexterity.

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The polynomial regression equations include high-order terms of two components (e.g., IT exploration and exploitation), such as the squared terms of the components and

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their product [92]. Specifically, we regressed NBMD (EBMD) on the control variables and five polynomial terms, namely, IT exploration, IT exploitation, IT exploration×IT

ur

exploitation, IT exploration2, and IT exploitation2 (Table 3). We mean-centered IT

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exploration and exploitation before calculating the higher-order terms to reduce the potential multicollinearity and help interpret the results. When the higher-order terms (i.e., IT exploration×IT exploitation, IT exploration2,

and IT exploitation2) are insignificant, IT exploration and exploitation linearly relate to the dependent variable (i.e., NBMD or EBMD). By contrast, when any of the higher-order terms is significant, the response surface (3D graph) can be used to

28

reflect the effect of the configuration between IT exploration and exploitation on NBMD (EBMD). For the response surface, a significant curvature of the surface along the perfect balance line (i.e., IT exploration = IT exploitation) indicates that the level of balance between IT exploration and exploitation nonlinearly relates to business model design. When the curvature of the surface along the perfect balance line is insignificant and the slope of the surface along the perfect balance line is positive and significant, a

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positive linear relationship exists between two balanced IT capabilities and business

model design. In observing the imbalance effect, a negative and significant curvature surface along the perfect imbalance line (i.e., IT exploration = −IT exploitation)

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indicates a negative effect of the imbalance in IT exploration and exploitation on

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business model design [68].

Table 3. Polynomial modeling and response surface analysis. NBMD

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Variables (Constant)

3.966

Firm age IT dept. size R&D dept. size

na

Firm size

Machinery and equipment

a

ur

Food and beverage a Chemicals a

Medicine and biology

a

a

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Wood products and furniture Electronic

***

a

EBMD 4.158***

−0.001

−0.005

0.000

0.000

0.003

−0.001

0.002

0.000

−0.031

−0.050

0.051

−0.005

−0.117

−0.120

−0.083

−0.120

0.101

−0.009

−0.103 ***

0.028

IT exploration (ITER)

0.255

0.125**

IT exploitation (ITEI)

0.108

0.193***

ITER2

−0.039

0.032 −0.049

*

ITER×ITEI ITEI2

0.283 0.019

0.246***

R2

0.393

0.454

Adj-R2

0.339

ΔR for the three quadratic terms 2

0.405 ***

0.092

29

0.123***

Perfect balance line (ITER = ITEI) Slope

0.362***

0.318***

Curvature

0.263***

0.229***

Slope

0.147

−0.068

Curvature

−0.304

Perfect imbalance line (ITER = − ITEI) *

0.327**

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re

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Note: * p < 0.05, ** p < 0.01, and *** p < 0.001. a Dummy variable.

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ur

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Fig. 2. Response surface for NBMD.

30

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Fig. 3. Response surface for EBMD.

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Table 3 shows the results of the polynomial regression. Figs. 2 and 3 present the response surface results. Specifically, the left side of Figs. 2 and 3 shows the 3D

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response surfaces of NBMD and EBMD generated by polynomial regression analysis. The right side of Figs. 2 and 3 depicts the cross-sections of NBMD and EBMD surfaces

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along the perfect balance and imbalance line.

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H5a and H5b predict that NBMD and EBMD are higher when the level of balance between IT exploration and exploitation is high compared to when the level of balance

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is low. A positive slope of the response surface along the perfect balance line will support H5a and H5b. Table 3 indicates that the slope of the NBMD surface along the perfect balance line is positive and significant (slope = 0.362, p < 0.001), thereby supporting H5a. The slope of the EBMD surface along the perfect balance line is positive and significant (slope = 0.318, p < 0.001), thereby supporting H5b. However,

31

the positive and significant curvature of NBMD (curvature = 0.263, p < 0.001) and EBMD (curvature = 0.229, p < 0.001) suggest that the impact of the level of balance between IT exploration and exploitation is more complicated than expected. Figs. 2 and 3 show that the degrees of NBMD and EBMD decrease first and then increase when IT exploration and exploitation increase in a balanced condition. They illustrate a U-shaped relationship. This result affirms that the degree of NBMD and EBMD

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achieves its high levels when IT exploration and exploitation are balanced at either low or high levels.

H6a suggests that the degree of NBMD decreases as the imbalance between IT

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exploitation and exploration increases in either direction. Table 3 shows that the

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curvature of the NBMD surface along the perfect imbalance line is negative and significant (curvature = –0.304, p < 0.05). Similarly, toward the surface along the

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perfect imbalance line in the right bottom of Fig. 2, the degree of NBMD decreases

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when high IT exploration is accompanied by low IT exploitation, and vice versa. Thus, the degree of NBMD will decrease as the degree of imbalance between IT exploration

ur

and exploitation increases, thereby supporting H6a. H6b suggests that EBMD will be higher when the imbalance between IT exploitation and exploration increases in either

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direction. Table 3 presents that the curvature of the EBMD surface along the perfect imbalance line is positive and significant (curvature = 0.327, p < 0.001). Similarly, the degree of EBMD increases toward the surface along the perfect imbalance line in the right bottom of Fig. 3, where IT exploration and exploitation become increasingly discrepant; thus, H6b is supported. Some other interesting results are found. Figs. 2

32

and 3 exhibit that the firm can simultaneously achieve good EBMD and NBMD when IT exploration and exploitation are at either high or low levels.

5. Discussion This study aims to investigate the relationship between IT capability, business model design, and firm performance. On the basis of organizational learning theory

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and entrepreneurship literature, we explore the individual and joint impact of IT exploration and exploitation on business model design and ultimately firm performance. Our empirical findings on the relationships between IT capability,

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business model design, and firm performance are not only consistent with those of the

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previous literature [11, 13] but also provide novel insights. Specifically, this study provides empirical evidence on the critical roles of NBMD and EBMD in creating and

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capturing value in the relationship between business model design and firm performance [13, 48]. Additionally, the results indicate that EBMD can be

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significantly affected by IT exploration and exploitation, whereas NBMD can be significantly affected by IT exploration. These findings extend existing IT literature

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on the impact of IT on business model design [1].

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However, we do not find support for the association between IT exploitation and NBMD. One possible reason may be that a firm that focuses on IT exploitation to support NBMD may have limited capability in identifying novel business opportunities. The entrepreneurship literature has elucidated that the nature of NBMD often requires completely novel knowledge creation that generates breakthrough ideas

33

and transforms existing knowledge base [10, 48]. Creating new cognitive maps to accommodate the new interpretations of processes, knowledge, and business by exploiting existing IT resources may be difficult [19]. In other words, a firm’s exploitation of existing IT resources does not effectively support the learning needs of NBMD. We also disclose the impact of the balance and imbalance between IT

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exploration and exploitation on NBMD and EBMD. Specifically, the degree of NBMD and EBMD will be higher when IT exploration and exploitation are balanced

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at high levels rather than at low ones. The results further present that NBMD and

EBMD will initially decrease and then increase when the level of balance between IT

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exploration and exploitation increases. This finding indicates that the increase in the

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balance between IT exploration and exploitation at low levels can damage rather than improve the business model design. When firms aim to promote business model design

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by increasing the level of balance between the low IT exploration and exploitation, they may face the challenge of high cost and low benefit of such increasing balance [95].

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When IT exploration and exploitation are at low levels, balancing them usually cannot

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bring sufficient benefits of knowledge integration and application for firms to support business model design. Such increased levels of balance require firms to invest time and other resources [96], which may hamper the development of the business model design. However, when IT exploration and exploitation reach high levels, they can provide strong learning support for business model design. The benefits of increasing the balance between IT exploration and exploitation at relatively high levels will be

34

larger than the related cost, which finally help firms design business model. Therefore, firms can effectively leverage IT capability to integrate and apply knowledge for enhanced NBMD and EBMD when the IT exploration and exploitation are balanced at levels surpassing a certain threshold.

5.1 Theoretical contributions and managerial implications

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Our study contributes to the literature in two ways. First, we contribute to IS literature by empirically revealing the direct relationships between IT capability,

business model design, and firm performance. Although prior literature has

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theoretically recognized the impact of IT on business model design [1, 11], few studies

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have empirically explored such impact. Based on organizational learning theory and entrepreneurship literature, we propose and verify that IT exploration and exploitation

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as enablers of organizational learning can influence NBMD and EBMD. Second, we contribute to existing organizational learning and IT ambidexterity

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literature by highlighting the importance of balance and imbalance of exploration and exploitation in IT resource management. Although prior literature has suggested the

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importance of IT ambidexterity [e.g.,16], few studies have explored how to configure

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the levels of IT exploration and exploitation to achieve specific or better business model designs. We expand insights into this research area by adopting polynomial regression with response surface analysis to explore the effects of balance and imbalance between IT exploration and exploitation on business model design. A full understanding on the complex joint effects of IT exploration and exploitation is also

35

provided. In summary, these findings add to extant knowledge on IT-enabled business model designs. Our findings also have several implications for practitioners. First, firms must pay attention to their business model design. NBMD and EBMD can create and capture value and improve firm performance. Therefore, managers who aim to improve performance need to redesign their business model in terms of novelty- and

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efficiency-centered design themes. Second, managers need to be aware of the

importance of IT capability for business model design in orientating firms toward

entrepreneurial innovations and understand the support of IT capability to business

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model design. Specifically, our findings provide insights into the strategic allocation of

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IT budgets between IT exploration and exploitation to achieve the desired levels of EBMD and NBMD. Firms that simultaneously pursue high degrees of NBMD and

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EBMD should seek the balance between IT exploration and exploitation at either low or

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high levels. Moreover, managers should note that sustainable and significant IT investments are required to achieve a significant boost from the original positing of

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balance between IT exploration and exploitation at low levels. In addition, firms that adjust their balanced level between IT exploration and exploitation when targeting a

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significant boost in NBMD and EBMD should attempt to shorten the transition period as far as possible for reducing the negative influence of being in the middle. Thus, a drip-feed incremental approach toward increasing investment in IT exploration and exploitation should be avoided.

36

However, most firms face tightly controlled IT budgets. Thus, the maximization approach of balance may be unsuitable for all firms. Firms with constrained IT budgets have different choices in the allocation of IT budgets in IT exploration and exploitation for NBMD and EBMD. Specifically, firms that aim for high NBMD can devote IT investments to sustain the balance between IT exploration and exploitation at low levels. Conversely, firms that pursue high EBMD can deliberately devote IT

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investments to either foster balance between IT exploration and exploitation at low levels or keep a high discrepancy between IT exploration and exploitation.

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5.2 Limitation and future research

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Although this study offers several contributions, it contains a few limitations. First, the survey is conducted in China. China has its own political and economic

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peculiarities [76], which may limit the generalization of our results. Nonetheless, such peculiarities are virtually unavoidable for any country with its own socio-political

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environment. Despite this reality, we still suggest that future research should collect data from different countries to further verify our findings. Second, this study uses a

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cross-sectional research design. This design adds difficulty in our exploration of the

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evolution of business model design. A longitudinal study can enrich our understanding by offering information on the causal relationships between independent and dependent variables. Such a study can also reduce the common method bias that invariably threatens the validity of studies collecting data at a single point of time. Third, we use subjective rather than objective performance measures due to our emphasis on the overall performance impact of business model design. Future research can use 37

objective performance measures to further examine the impact of business model design on firm performance. Finally, although IT capability can support a firm’s business model design, their relationship may be influenced by other internal or external factors (e.g., industry environment). Therefore, future studies may consider firms’ circumstances when investigating the potential environmental moderators of the relationships between IT capability and business model design.

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Author Contribution Statement Yao Chen: Conceptualization, Formal analysis, Methodology, Software, Writing – original draft, Writing – review & editing.

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Hefu Liu: Supervision, Project administration, Conceptualization, Data curation, Resources, Writing – original draft, Writing – review & editing.

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Meng Chen: Conceptualization, Formal analysis, Methodology, Software, Writing – original draft, Writing – review & editing.

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CRediT roles:

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ur

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Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Roles/Writing – original draft, Writing – review & editing.

Appendix Variables

Loading

Items

38

Relative to other firms in your industry, please indicate the capability of your IT unit (s) to: IT exploration

0.955

1. Acquire new IT resources (e.g., a new generation of IT architecture, potential IT applications, and critical IT skills)

IT exploitation

0.977

2. Experiment with new IT resources

0.971

3. Experiment with new IT management practices

0.962

1. Reuse existing IT components, such as hardware and network resources

0.980

2. Reuse existing IT applications and services

0.962

3. Reuse existing IT skills To what extent do you agree with the following statements?

EBMD

0.787

1. Transactions are simple from the user’s viewpoint.

0.805

2. The business model lowers the number of errors in the execution of

0.610

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transactions. 3. Costs other than those previously mentioned for participants in the business model are reduced.

4. The business model enables participants to make informed decisions.

0.813

5. The business model enables fast transactions.

0.852

6. Overall, the business model offers high transaction efficiency.

0.672

1. The business model offers new combinations of products, services, and information.

0.738

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NBMD

0.750

2. Our business model links participants and transactions in novel ways (e.g.,

re

through new channels). 0.817

3. The richness (i.e., quality and depth) of some of the enabled links between

0.786

4. The firm claims to be a pioneer with its business model.

0.716

5. No competing business models exist in our industry that are threatening to

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participants is novel.

ours.

6. Other important aspects of the business model contribute to its novelty.

0.852

7. Overall, the company’s business model is novel.

na

0.843 Firm performance 0.809

1. Our firm’s overall performance compared with major competitors over the past year on the sales growth rate

2. Our firm’s overall performance compared with major competitors over the

ur

0.890

past year on market share growth

0.861

3. Our firm’s overall performance compared with major competitors over the

Jo

past year on the growth rate of profit

0.836 0.815

4. Our firm’s overall performance compared with major competitors over the past year on the total assets growth rate 5. Our firm’s overall performance compared with major competitors over the past year on overall competitiveness

39

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[92] L.R. Shanock, B.E. Baran, W.A. Gentry, S.C. Pattison, E.D. Heggestad, Polynomial regression with response surface analysis: A powerful approach for examining moderation and overcoming limitations of difference scores, Journal of Business & Psychology, 25 (4) (2010) 543-554. [93] N.K. Lankton, D.H. McKnight, R.T. Wright, J.B. Thatcher, Research note—Using expectation disconfirmation theory and polynomial modeling to understand trust in technology, Information Systems Research, 27 (1) (2016) 197-213. [94] J.R. Edwards, M.E. Parry, On the use of polynomial regression equations as an alternative to difference scores in organizational research, Academy of Management Journal, 36 (6) (1993)

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1577-1613. [95] C.A. O’Reilly III, M.L. Tushman, Ambidexterity as a dynamic capability: Resolving the innovator's dilemma, Research in Organizational Behavior, 28 (2008) 185-206. [96] S. Raisch, J. Birkinshaw, Organizational ambidexterity: Antecedents, outcomes, and moderators, Journal of Management, 34 (3) (2008) 375-409. Hefu Liu is a professor in the School of Management at the University of Science and Technology of China. He earned his PhD degree with the University of Science and Technology of China and City University of Hong Kong. He has published in MIS Quarterly, Journal of Operations Management,

Decision Sciences,

Decision Support Systems, Information and

Management, International Journal of Operations and Production Management, and in the academic conference ICIS, PACIS and AMCIS.

Yao Chen is a PhD candidate of the University of Science and Technology of China. Her research interest includes IT business

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value and business model design.

Meng Chen is an Assistant Professor at Research Center for Smarter Supply Chain, Dongwu Business School, Soochow University. He earned his PhD degree with the University of Science and Technology of China. His research interests include IT business value, supply chain integration, and innovation management. He has published in Industrial Marketing Management,

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and in the academic conference ICIS.

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