ON TIME BUSINESS MANAGEMENT A+ WORK, ON TIME, NO PLAGARIZING; ON TIME

Information technology investment and digital transformation:

the roles of digital transformation strategy and top management

Xin Zhang, Yao Yu Xu and Liang Ma Shandong University of Finance and Economics, Jinan, China

Abstract

Purpose – In the context of the digital economy, information technology (IT) investment has become a necessaryway for enterprises to transformdigitally. However, why and how IT investment can enhance digital transformation is lacking in the literature. Based on the resource-based view (RBV), this study explored the impact mechanism of IT infrastructure on the digital transformation of enterprises from the perspective of the digital transformation strategy. Further, this study examined the moderating role of top management on the relationships between IT infrastructure and digital transformation strategy and between digital transformation strategy and enterprise’s digital transformation. Design/methodology/approach –Through a questionnaire survey of Chinese enterprises, 180 sample data were collected, and the partial least squares-structural equation modeling (PLS-SEM) method was used to test the hypothesis. Findings – Digital transformation strategy fully mediates the relationship between IT infrastructure and enterprise digital transformation. Furthermore, top management has a significant positive moderating effect on the relationship between IT infrastructure and digital transformation strategy, as well as the relationship between digital transformation strategy and digital transformation. Originality/value – This study explores the moderating role of top management in the relationship between IT and enterprise performance, as well as the mediating role of digital transformation strategy in the relationship between IT infrastructure investment and digital transformation performance. As a result, the study adds significantly to the body of knowledge on IT business value, digital transformation and strategic management. The authors’ findings can help update managers’ perceptions of IT value and provide theoretical guidance on deriving digital transformation performance from IT infrastructure investments.

Keywords IT infrastructures, Digital transformation strategy, Top management, Digital transformation

Paper type Research paper

1. Introduction Currently, the new generation of information technology (IT) represented by artificial intelligence, block-chain, cloud computing, big data and the internet of Things is driving the rise of the digital economy and bringing disruptive changes to the organizational structure, business process and business model of enterprises (Vial, 2019). IT has become a critical factor in promoting the digital transformation of enterprises. Thus, enterprises view investments in IT as a way to gain a competitive advantage in the fierce and dynamic market competition environment. Companies in almost all industries are making some moves to explore new IT and take advantage of its benefits. According to Gartner’s latest forecast, IT spending by global enterprises is expected to reach US$4.1 trillion in 2021, an increase of 8.4% over 2020. It is expected that as enterprises’ digital transformation work continues to accelerate, their IT expenditures will continue to grow. However, studies show that only 20% of business digital transformation initiatives succeed and significant company IT expenditures have not had the desired digital impact. The mismatch between IT input and

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This work was supported by Youth Foundation of Social Science and Humanity, China Ministry of Education [grant number 21YJC630098]; Key Projects of the National Social Science Foundation of China [grant number 21AZD022].

The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/1463-7154.htm

Received 2 June 2022 Revised 13 September 2022 29 November 2022 Accepted 6 January 2023

Business Process Management Journal Vol. 29 No. 2, 2023 pp. 528-549 © Emerald Publishing Limited 1463-7154 DOI 10.1108/BPMJ-06-2022-0254

transformation output has once again aroused a new discussion on IT value creation in the context of digital transformation in academia and industry.

Existing research on the business value of IT mainly explores the impact of IT on organizational performance. Previous studies have shown that IT may indeed help improve organizational performance. A consensus has emerged that IT, as a simple hardware and software tool, cannot alone or directly generate value or improve company performance but complement other information systems and organizational factors and function synergistically (Wang et al., 2015; Peng et al., 2016). For example, Wade and Hulland (2004) pointed out that information systems affect corporate performance by complementing other enterprise assets or capabilities. Mithas et al. (2013) further argue that the impact of IT capabilities on enterprise performance is realized by supporting higher-order business capabilities. Similarly,Wang et al. (2015) found that IT assets could not directly and independently affect business performance but through interaction with IT management. Peng et al. (2016) pointed out that IT capability can improve enterprise performance by integrating with enterprise business process management capability and supply chain management capability. However, the existing literature has not reached a consensus on how to give full play to the potential value of IT and effectively enable the digital transformation of enterprises. It is still unclear which precise mechanisms IT uses to influence the results of enterprise transformation.

Digital transformation can be considered the strategic response to digital technology trends and disruptions (Vial, 2019), encompassing profound changes in society and industry caused by the application of digital technology (Agarwal et al., 2010). It’s a complex journey that needs to be guided by a clear digital transformation strategy. The latest view holds that it is strategy that drives digital transformation, not technology (Li et al., 2018). Digitalization has wholly changed traditional strategic rules and redefined competitive advantage and its realization strategy. Indeed, digital transformation must consider how advances in digital technology can bring changes to the organizational business model, structure and processes (Hess et al., 2016), it includes the impact of emerging information technologies on the digital transformation strategy of enterprises. Therefore, the core issue of enterprise digital transformation is how to formulate and implement digital transformation strategy (Chanias et al., 2019). Existing research suggests that organizations need to develop a digital transformation strategy to find innovative applications of technology, manage the changes triggered by technology and coordinate the implementation of the entire digital transformation (Hess et al., 2016). Therefore, some studies believe that digital transformation strategy and organizational change have become a new path of IT-driven digital transformation (Svahn et al., 2017). However, despite these understandings, the specific role of digital transformation strategy in the relationship between IT and digital transformation is still unclear and its relative degree and micro-mechanism have not been tested.

Digital transformation strategy focuses on the changes in products, processes and organizations owing to new technologies (Matt et al., 2015). In a dynamic environment, a digital transformation strategy can guide the integration and use of digital technologies to achieve digital transformation. Research shows that digital transformation strategy positively affects firm performance, mediating between digital technology usage and firm performance (Tsou and Chen, 2021). Digital strategy can improve the digitization level of enterprises through digital capabilities (Proksch et al., 2021). Furthermore, organizational outcomes are predicted by management characteristics (Lim et al., 2011b). Existing studies have shown that topmanagement support and digital leadership enhance the ability to utilize outstanding IT capabilities, promote successful strategic changes and improve business performance (Li et al., 2018). Additionally, the design and implementation of a digital transformation strategy often involve top managers (such as a digital committee and Chief Digital/Information Officers (CDOs/CIOs) who lead and initiate transformation efforts (Haffke et al., 2016). To lessen or avoid risks from incorrect identification and deployment of

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processes and resources, top managers must make the appropriate strategic decisions about the digital transformation of their organizations (Chae et al., 2018). This study argues that digital strategies present an opportunity for companies to explore new ways to create value from IT. IT infrastructure facilitates digital transformation by responding to and supporting selected business strategies. Moreover, top management is complementary to IT infrastructure and digital transformation strategy.

In summary, this study takes digital transformation strategy and top management as the crucial mechanism of IT business value formation in the context of digital transformation. Theoretically, IT infrastructure influences enterprise transformation outcomes by responding to and supporting digital transformation strategies. Top management can strengthen the relationship between IT infrastructure, digital transformation strategy and transformation outcomes. Therefore, this study examines both the mediating effect of digital transformation strategy and the potential moderating role of top management, thereby answering the current research needs on the role of digital transformation strategy and the use of new-generation IT in the context of enterprise transformation and upgrading.

This study has specific theoretical and practical contributions. First, this paper provides a new interpretation of how IT infrastructure can empower an enterprise’s digital transformation. By taking digital transformation strategy as an intermediary condition, we enrich and expand the research on IT value creation. Secondly, this study constructs and empirically tests a model of IT-driven digital transformation realization and takes IT infrastructure, digital transformation strategy and top management as the antecedent configuration of digital transformation, which enriches the research on digital transformation. In terms of its practical value, this study concludes that businesses cannot solely rely on IT to implement digital transformation. Instead, businesses must create a digital transformation strategy to manage the complex transformation brought on by digital technology and use an effective IT-strategy integration to boost transformation performance. The study’s findings offer theoretical recommendations for businesses to achieve digital transformation and a justification based on science for top management competency training in businesses.

2. Theoretical background 2.1 Resource-based view of the firm The resource-based view (RBV) posits that an enterprise’s unique resources and capabilities are the sources of its lasting competitive advantages. In order to explain the sustainable advantages and differences across organizations, it views an enterprise as a collection of resources and focuses on those resources’ traits and strategic elements (Barney, 1991). Resources refer to the assets, technologies, knowledge, capabilities and processes owned by an enterprise. Moreover, RBV emphasizes that only valuable, rare, imperfectly imitable and non-substitutable resources can be used as the basis for competitive advantage.

In information system literature, RBV is widely accepted as the leading theory to explain how IT resources form business value (Barney et al., 2011; Shibin et al., 2020). Based on RBV, existing studies have explored the impact of various IT resources on organizational performance, such as IT infrastructure (Benitez et al., 2018), IT capabilities (Chae et al., 2018) andmanagement of IT investment (Ilmudeen and Bao, 2020) and considers that IT resources, as a source of competitive advantage, can be used to improve internal communication, increase production efficiency, reduce operating costs and increase financial performance (Liang et al., 2010; Devaraj and Kohli, 2003). At the same time, other studies have limited the argument that IT resources have a direct impact on firm performance (Peng et al., 2016) and have proposed a complementary view based on RBV, which argues that IT resources do not generate competitive advantage by themselves, but gain competitive advantage by

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complementing other resources or capabilities (Ravichandran et al., 2005). Spanos and Lioukas (2001) also proposed a composite model and analyzed three paths of the relative influence of firm-specific factors on performance. Among them, the RBV-based strategic effect reflects the direct effects of strategy on performance and the firm asset effects reflect the firm asset’s impact against the strategy. This path indicates that the firm resources can enhance the firm’s ability to design competitive strategies and thus affect firm performance (Rivard et al., 2006), which is precisely in line with our view. We believe that the complementary role of digital transformation strategy as an intermediary structure between IT resources and enterprise digital transformation may be an extension of the aforementioned views. As a result, the complementary view based on RBV theory provides an excellent theoretical foundation for us to explore the complementary role of IT infrastructure and digital transformation strategy.

2.2 IT investment and organizational return In the information systems research field, scholars have conducted some helpful research on the organizational return on IT investment. The issues that must be considered in these studies are themeasurement of IT investment and firmperformance and themechanism of IT investment on organizational performance (Lim et al., 2011a). (1) In IT investment measurement, researchers often employ various alternative measures due to minimal publicly available information on firm-specific IT investments. Through a review of previous research, we identified several major IT investment concepts such as IT spending (IT infrastructure, IT human resources) (Dalenogare et al., 2018; Karhade and Dong, 2020), IT strategy and IT capabilities/management (Chae et al., 2018, Wiesb€ock et al., 2020). (2) The measurement of firm performance brought by IT investment mainly includes financial performance (Mithas and Rust, 2016; Sabherwal et al., 2019) andmarket performance, such as product innovation performance (Benitez et al., 2018) and organizational agility (Ravichandran, 2018). (3) In terms of the research on the relationship between IT investment and organizational performance, a large number of research consensus is that IT investment positively impacts on organizational performance, however it depends on understanding how these investments affect performance and the contexts and conditions. IT may not be able to create sustainable competitiveness on its own (Rai et al., 2006), but it is a part of the business value creating process with other complementary resources and organizational capabilities operating synergistically (Wade and Hulland, 2004). Therefore, the complementary and mediating factors of IT value-creation processes have been extensively discussed in this field. For example, Karimi et al. (2007) argue that the synergistic effect of integrating IT with various complementary resources has a positive impact on enterprise performance. Rai et al. (2006) pointed out that IT resources can affect firm performance by enhancing critical organizational capabilities. Other studies have also proposed that factors such as IT strategy, business strategy, or strategic fitness can enhance firm performance (Ilmudeen and Bao, 2020; Queiroz et al., 2020). Table 1 summarizes some studies on the relationship between IT resources and firm-related value.

Our review of previous literature shows that, despite significant progress in the business value of IT literature, there are still two opportunities for contribution. First, enterprise digital transformation is still a new phenomenon and our knowledge of how IT investment adds value in this context is still limited. The strategic role of digital transformation strategy is not yet clear and the causal relationship between IT, digital transformation strategy and digital transformation outcomes is still challenging to grasp. Therefore, it is necessary to study its micro-mechanisms to increase our knowledge of mediating factors in the IT value-creation process and understand how IT creates differential transformation performance. Second, existing research has not focused enough on the business value of IT infrastructure.

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According to statistics, enterprise IT infrastructure investment accounts for more than 50% of the total IT expenditures, which provides the basis for sharing IT services inside and outside the organization (Aral and Weill, 2007), and is a crucial enabler of business performance (Benitez et al., 2018; Karhade and Dong, 2020). Some scholars even proposed to take infrastructure research as the core of future information system research (Tilson et al., 2010). Therefore, this study focuses on the value creation of IT infrastructure in the digital environment, which has certain practical significance.

2.3 Digital transformation strategy Digital technology has a transformative impact on almost all aspects of enterprises’ internal operations and external environment and this digital disruption requires the coordination and adjustment ofmany corporate strategies (Vial, 2019). In this regard, researchers advocate the integration of IT business strategy. For example, Bharadwaj et al. (2013) argue that digital technologies need to integrate organizational and information system strategies and propose the concept of digital business strategy. Matt et al. (2015) further focused on the transformation of processes, products and organizations brought about by new technologies and proposed the concept of the digital transformation strategy, arguing that in a dynamic environment, digital transformation strategy can guide the integration and application of digital technologies, to achieve digital transformation (Hess et al., 2016). Therefore, the formulating and implementing a clear and scientific digital transformation strategy becomes a critical path for the digital transformation practice of enterprises.

Currently, digital transformation strategy research mainly involves connotation and dimensions, dynamics and impact results. For example, Matt et al. (2015) proposed that digital transformation strategy refers to supporting the strategic transformation of enterprises brought about by the application of digital technology and the strategic positioning of the operation and development of enterprises during or after transformation

Study Independent variable Mediators Dependent variable

Chen et al. (2015) IT capabilities Corporate entrepreneurship Product innovation performance

Ahuja and Chan (2016) IT resource IT leveraging

Dynamic capability (agility) Innovation/Improvisation

Mithas and Rust (2016) IT investment IT strategy (moderator) Firm performance Nwankpa and Roumani (2016)

IT capabilities Digital transformation Innovation

Nwankpa and Datta (2017)

IT capability Digital business intensity Organizational performance

Benitez et al. (2018) IT infrastructure Knowledge ambidexterity Innovation performance Ravichandran (2018) IT competence innovation capacity

(moderator) Organizational agility

Chae et al. (2018) IT capability Industry categories (moderator)

Firm performance

Sabherwal et al. (2019) IT investment strategic IT alignment (moderator)

Firm performance

Wiesb€ock et al. (2020) IT capabilities Digital product innovation capabilities

Digital product innovation performance

Karhade and Dong (2020)

IT investment – Commercialized innovation performance

Ilmudeen and Bao (2020)

Managing IT IT strategy and business strategy

Firm performance Table 1. IT business value- related research

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and divided it into four dimensions: technology use, value creation, structural change and financial gain. Hess et al. (2016) refined these four dimensions into 11 items and verified and adjusted them through case interviews. Sebastian et al. (2017) proposed two digital transformation strategies, customer engagement and digital solution strategies, from the perspective of digital technology investment. Tekic and Koroteev (2019) proposed four general digital transformation strategies from the dimensions of digital technology application and digital operation business model, namely disruptive strategy, business model-led strategy, technology-led strategy and customized simulation strategy. Several studies focus on the dynamics of digital transformation strategy and explore the process of developing and implementing digital transformation strategies. For example, Hess et al. (2016) identified a series of strategic questions and possible answers that managers must consider based on the successful experience of three case companies to provide guidelines for formulating a digital transformation strategy. Chanias et al. (2019) constructed an integrated model of digital transformation strategy development and execution, noting that digital transformation strategy integrates information system strategy and business strategy, is a highly dynamic adjustment and change process and includes a series of crucial decision- making activities. In addition, some scholars have begun to use empirical researchmethods to explore the impact results of the digital transformation strategy. For example, Wang et al. (2020) used data from a sample of 182 Chinese firms to discuss the micro-mechanism by which digital transformation strategies improve digital transformation’s long-term and short-term performance. These studies provide new perspectives for exploring digital transformation strategy and digital transformation. However, there are no relevant empirical studies on the impact of IT on the formulation and implementation of the digital transformation strategy and the assertion that strategy and IT work together to build competitive advantage to achieve digital transformation, which is the meaning of our research.

2.4 Top management The impact of top management has always been an important research issue in the field of enterprise strategic management and information systems. Existing research shows that top management support, engagement, commitment and leadership are the critical factors in IT value creation for three main reasons: (1) top managers with a broader perspective are better able to identify the business opportunities to utilize IT in business processes and provide management guidance for planning, designing, developing and implementing activities (Liang et al., 2007), thus enhancing the effectiveness of the IT management process; (2) top managers with high levels of management commitment and participation can assume significant ownership and are willing to take risks (Woldesenbet et al., 2012), to ensure sufficient human, material and financial input in the IT implementation process (Hu et al., 2012) and (3) top management facilitates the development of process capabilities by participating in executive steering committees and building partnerships across and within companies (Cragg et al., 2013), resolving conflicts and keeping projects on track. An extensive literature base provides theoretical support for the critical role of top management in achieving IT performance.

Recent studies have begun to link top management to the outcomes of innovation or change processes (Christensen et al., 2016; Oreg et al., 2018). As the maker of corporate strategy, top managers directly influence corporate innovation by deciding the innovation strategy (Talke et al., 2011) and resource commitment (Wrede and Dauth, 2020). Digital transformation can be seen as a process outcome based on change and innovation. Therefore, existing research has started to focus on the role of top management, such as manager engagement, agile transformation management and leadership, in digital transformation

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(Osmundsen et al., 2018). For example, Weber et al. (2017) explain the role of the highly authorized team by identifying the human resource capabilities needed to achieve successful digital transformation. Artemenko (2020) explains the role of top management in enterprises digital transformation. These studies provide an initial reference for in-depth investigations into the role of top management in IT value creation, strategy formulation and implementation and enterprise digital transformation.

3. Research model and hypotheses This study, which is based on the IT business value paradigm and RBV theory, proposes an IT-driven digital transformationmodel with a digital transformation strategy as themediator and top management as the boundary condition in order to clarify the value creation mechanism of IT investment in the context of enterprise digital transformation, as shown in Figure 1.

3.1 IT and digital transformation strategy According to RBV, resources are the basic unit of analysis, while the capabilities are the ability of resources to perform a task or activity together (Makadok, 2001). A firm with valuable IT resources may be able to leverage these resources to build their capabilities (Liang et al., 2010). An enterprise digital transformation strategy can be viewed as a capability that reflects the ability to leverage digital technologies in the business (Matt et al., 2015). Therefore, we propose that IT infrastructure is relevant to digital transformation strategy.

Digital transformation is the strategic response of an organization to the disruptive changes brought by digital technologies (Vial, 2019). As technology continues to penetrate organizations, their innovation and change processes need to be orchestrated by a strategy that facilitates IT investments to deliver value along a performance dimension aligned with transformation goals. Digital transformation strategy focuses on the changes in organizations, products and processes brought about by new technologies and guides the integration and adoption of digital technologies to achieve the desired digital transformation goals (Matt et al., 2015). Thus, digital transformation strategy provides insights on how to leverage new technologies to empower the digital transformation of enterprises.

Moreover, the application of new technologies changes organizational practices and organizational structures, facilitates product and business model innovation and becomes a core driver of strategic change and innovation in the firm (Nambisan et al., 2017) while also providing technical support for its effective implementation (Vial, 2019). Research has shown

IT Infrff astrur ctut reIT Infrastructure Digital

Transfoff rmation Strategy

Digital Transformation

Strategy

Digital Transfoff rmation

Digital Transformation

Top ManagementTop Management

H1 H2

H4bH4a

H3 H3

Direct/moderated effects

Mediated effectsControl Variaba les: Firm size; Indud stryrr ; Firm ageControl Variables: Firm size; Industry; Firm age Figure 1. Research model

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that digital technology changes enterprises’ original resource base characteristics in four ways: form, nature, value and structure through standardization, process, data and interconnectedness of resources, thus driving strategic change. The more technological resources a company has, the greater its ability to develop utility-creating strategies (Spanos and Lioukas, 2001) and the more conducive it is to develop a digital transformation strategy (Tsou and Chen, 2021). This study suggests that IT infrastructure is the antecedent of an enterprise’s digital transformation strategy. Firms with higher levels of IT infrastructure have a more remarkable ability to design and implement digital transformation strategies. Therefore, we propose the following hypotheses.

H1. IT infrastructure has a positive effect on digital transformation strategy.

3.2 Digital transformation strategy and digital transformation Digital transformation is a process of disrupting the established ways of value creation and seeking innovation and change (Nambisan et al., 2019). This complex systemic engineering requires a digital transformation strategy to coordinate, organize and guide the implementation of all related activities to achieve the desired digital transformation goals (Matt et al., 2015). Moreover, the RBV emphasizes the critical role of organizational capabilities in the process of gaining competitive advantage for the firm (Eisenhardt and Martin, 2000; Sabherwal et al., 2019). The digital transformation strategy reflects a capability that is considered to help leverage the IT infrastructure to improve the competitive advantage of the firm and, therefore, can facilitate the digital transformation.

Many studies regard digital transformation strategy as a crucial antecedent condition for digital transformation (Bharadwaj et al., 2013), emphasizing that enterprise leaders should do top-level design, create new value propositions by combining digital technology capabilities with existing resources and stuff and realize digital transformation (Sebastian et al., 2017). A digital transformation strategy can support enterprise’s digital transformation by focusing on the innovation and change brought about by technology and coordinating all organizational resources and capabilities (Leischnig et al., 2017). An organization with good digital transformation practices shows a clear and well-defined digital transformation strategy (Kane et al., 2015). Conversely, companies lacking a digital transformation strategy show poor and ineffective decision-making and resource utilization (Hess et al., 2016). Meanwhile, Wang et al. (2020) also verified the positive impact of digital transformation strategy on firm performance using a large sample of data. Successful digital transformation initiatives can lead to sustained performance and competitive advantage (Kane et al., 2017; Vial, 2019; Dalenogare et al., 2018). Thus, we have substantial evidence that.

H2. Digital transformation strategy has a positive influence on digital transformation.

3.3 Digital transformation strategy as mediators Based on RBV, a firm’s competitive advantage is primarily driven by its valuable, rare, unique and irreplaceable resources (Barney, 1991). IT infrastructure, as a replicable resource, does not create sustained firm performance by itself (Rai et al., 2006), but has an indirect impact through resource complementarities or organizational capabilities (Wade and Hulland, 2004). In other words, the impact of IT on enterprise-level outcomes (e.g. firm performance) needs to consider the complementary effects of other organizational resources or capabilities as intermediaries (Chen et al., 2015; Nwankpa and Datta, 2017; Ravichandran, 2018). The H1 and H2 combine to form the mediating role of digital transformation strategies. Companies with an IT edge are more motivated and capable of accomplishing their digital- oriented innovation efforts. Because, previous studies have shown that firm performance is the product of effects involving firm assets (including IT resources) and strategy (Spanos and

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Lioukas, 2001). The more resources a firm has, the greater its ability to develop a utility- creating strategy, which provides sufficient conditions for performance sustainability (Spanos and Lioukas, 2001; Rivard et al., 2006). Digital technology and digital transformation strategy constitute the key elements of enterprise digital transformation. The application of new technologies can promote the ability of digital transformation of enterprises, which in turn affects their innovation activities and performance (Tsou and Chen, 2021). Therefore, this study argues that IT infrastructure resources and capabilities are influencing digital transformation through digital transformation strategies and proposes the following hypothesis.

H3. Digital transformation strategy mediates the relationship between IT infrastructure and digital transformation.

3.4 The moderator role of top management Many researchers have studied the vital role of top management practices in the success of information systems. The involvement of top management seems to have led to effective information system (IS) planning (Sohal and Fitzpatrick, 2002). The top management’s commitment to IT-related programs improves IT success by providing IT resources, support and guidance on IS functions. This commitment also helps to integrate IT with business strategies and processes and to ensure the continuity of IT investments (Wade and Hulland, 2004). Mao et al. (2016) pointed out that if IT investment is properly managed, IT creates favorable conditions for the alignment of IT resources and enterprise strategy. As strategic executors, top managers supports its performance by coordinating the activities of different business units, synchronizing IT and business units, simplifying operational processes, reducing production costs, checking IT priorities frequently and allocating IT assets in a timely manner (Wang et al., 2015).

The resource complementary of RBV argues that the integration of different complementary resources can create synergies that lead to better results (Wade and Hulland, 2004; Melville et al., 2004; Karimi et al., 2007). Top management as a complementary resource can guide IT value creation and digital transformation strategy implementation, leading to better digital transformation performance. Digital transformation is a complex social project and the support of the top management is essential in the process of transformation. On the one hand, top management practices help IT evolve in a direction aligned with strategic objectives, thereby enhancing the ability of IT to support digital transformation strategies. Managers must have a clear vision of the company’s future digital development, be knowledgeable about current digital tools and their applications and foster a culture that supports the enterprise’s digital transformation in order to make the right decisions in the digital environment (Ukko et al., 2019).

On the other hand, top management practices can affect the strategic orientation of digital transformation and provide the necessary resources and capability to support the effective implementation of the digital transformation strategy, thus enhancing the possibility of digital transformation realization. Research shows that the implementation of a digital transformation strategy may encounter resistance from different areas of the company, requiring top management with the ability to mobilize the active participation of different stakeholders (Matt et al., 2015). Furthermore, the implementation of a digital transformation strategy is a highly dynamic process that requires continuous iterations between learning and practice (Chanias et al., 2019), which involves the participation of top management, leading and initiating transformation efforts (Haffke et al., 2016) and may lead to different performance outcomes. Therefore, we assume that the value-adding properties of IT infrastructure and digital transformation strategy are amplified when it is complemented by top management. The specific assumptions are as follows.

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H4a. Top management positively moderates the relationship between IT infrastructure and digital transformation strategy.

H4b. Top management positively moderates the relationship between digital transformation strategy and digital transformation.

4. Research method and data analyses 4.1 Measurement and data collection All constructs in this studyweremeasured using thematurity scale in existing studies and they were slightly modified to fit the context. IT infrastructure is measured using a four-item scale proposed by Lu and Ramamurthy (2011), which is mainly used to evaluate the level of IT assets and capabilities such as enterprise network communication services, data architecture, software and hardware platforms and facility operations, as well as intra- and cross-company communication and systems integration capabilities; The measurement items of digital transformation strategy is adapted from the research of Li et al. (2021) and Gurbaxani and Dunkle (2019), which mainly evaluate the maturity and implementation of enterprises digital transformation strategies; Top management mainly refers to the support and capability of the topmanagement team for IT-driven digital transformation, its scale adopts themeasurement of top management support and commitment by Wang et al. (2019) and the measurement of leadership by Mihardjo et al. (2019). The items of digital transformation are selected from the studies of Nwankpa andRoumani (2016) andAral andWeill (2007), mainly contains three items, in which respondents were asked to evaluate the integration of digital technology in enterprises and the results of using digital technology to carry out business innovation and change. All questions in the questionnaire were answered on a Likert 7-point scale, ranging from “1- strongly disagree” to “7- strongly agree.” In addition, firm size, firm age and industry were used as control variables to explain the variance of dependent variables.

In this study, small andmedium-sized enterprises (SMEs) in various industries in Chinawere selected as survey objects and questionnaires were distributed through a random sampling method.Datawere collected frommanagers as they relate to IT-driven transformation strategies and the digital transformation outcomes of the enterprise. The questionnaires were distributed online and accurately delivered to the middle and senior management through a professional questionnaire service platform (www.wjx.cn). This platformhas been used bymany researchers and has good quality assurance (Zhang et al., 2019). A total of 342 questionnaires were collected in this survey and then 162 invalid questionnaires with incomplete records, the same answers for all items and missing responses were excluded. Finally, 180 valid questionnaires were retained and used, with an effective response rate of 52.63%.

The firm characteristics of the recovered samples are shown in Table 2. The sample data comes from different industries, of which manufacturing (30%) and IT service industry (38.8%) are the central bodies. Regarding the years of establishment, 55% of the firms have been established for more than ten years, followed by those established for 6–10 years, accounting for 31.6% and 12.7% established for 3–5 years. Regarding size, 70% of the firms hadmore than 100 employees during the study period and 71.1% hadmore than 10million in annual revenue. The sample characteristics are basically in line with the situation of Chinese firms.

4.2 Measurement model This study used structural equation modeling (SEM) to test the research hypothesis. The partial least squares SEM (PLS-SEM) was chosen because it can handle complex models, has good parameter estimation efficiency and provides increased statistical power without

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needing a large number of samples or regularly distributed multivariate data (Shiau et al., 2019).

We used Smart PLS 3.0 software to analyze the sample data and tested their reliability, convergence and discriminant validity. First, Cronbach’s alpha (Cα), composite reliability (CR) and average variance extracted (AVE) were used to test the reliability. Table 3 demonstrate that the Cα values in this study range from 0.707 to 0.823 and the CR values range from 0.837 to 0.885, all exceeding the general threshold of 0.7. The AVE values are also above the suggested threshold of 0.5, demonstrating that the indicators in this study have a high degree of reliability. Secondly, the convergent validity and discriminant validity were examined by the factor loading and the square root of AVE. The results show that all the factor loadings of measures are more significant than 0.7, at a significance level of p < 0.01 (Table 4), showing good convergent validity. The square root of AVE for each factor (the bolded values in Table 3) is greater than the correlation coefficient with other factors, indicating good discriminant validity.

In addition, to ensure that the data set was not subject to common method bias, Harman’s single factor was inspected with four constructs (ITI, DTS, TM and DT) and all scale items. The test results show that the highest covariance explained by single factor was 32.769%, which is less than the cut-off value of 50% and no single factor was able to emerge.

Measure Items Size/

Percentage Measure Items Size/

Percentage

Industry Agriculture, Forestry, Animal Husbandry and Fishery

5, 2.7% Firm scale (people)

21–50 18, 10%

Industry and Construction 54, 30% 51–100 33, 18.3% Wholesale and Retail Trade 13, 7.2% 101–300 62, 34.5% Accommodation and Catering Industry

7, 3.8% 301–1,000 49, 27.2%

Transportation, Storage and Post

12, 6.6% More than 1,000

15, 8.3%

Information Transmission, Software and Information Technology Services

70, 38.8% Annual revenue (million)

Less than 1 3, 1.7%

Others 19, 10.5% 1–5 15, 8.3% Firm age (year)

Less than 3 1, 0.5% 5–10 34, 18.9% 3–5 23, 12.7% 10–50 52, 28.9% 6–10 57, 31.6% 50–100 28, 15.5% More than 10 99, 55% 100–500 30,16.7%

Firm scale (people)

20 and below 3, 1.7% More than 500

18, 10%

Items Cronbach’s Alpha CR AVE DTS DT ITI TM

DTS 0.823 0.876 0.587 0.766 DT 0.707 0.837 0.631 0.688 0.795 ITI 0.767 0.851 0.590 0.646 0.462 0.768 TM 0.804 0.885 0.719 0.621 0.648 0.434 0.848

Note(s): Digital transformation strategy (DTS); digital transformation (DT); IT infrastructure (ITI); top management (TM)

Table 2. Sample demographic information

Table 3. Descriptive statistics and inter-construct correlations

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Besides, common method bias can be assessed by examining the statistical significance of factor loadings of the method factor and comparing the variances of each observed indicator explained by its substantive construct and themethod factor. Themethod factor loadings are insignificant and the indicators’ substantive variances are substantially more significant than their method variances in this study. Thus, common method bias is not a serious concern.

Finally, we evaluated the goodness of model fit for the saturate model by examining the standardized root mean squared residual (SRMR), unweighted least squares discrepancy (dULS) and geodesic discrepancy (dG) (Henseler et al., 2016). Generally speaking, a model is considered to have a good fit if the value of SRMR is below 0.08 and the values associatedwith the dG and dULS criteria are below 0.95 (Henseler et al., 2016). After testing, the SRMR value of the proposed model was 0.075, lower than the threshold of 0.08 and the dULS value was 0.678, the dG value was 0.262, all of which are lower than 95% quantiles of the bootstrap difference. Thus, it was demonstrated that the proposed model showed a good structural model fit between the model and the data (Benitez et al., 2018).

4.3 Structural model and hypothesis testing In this study, the consistent PLSs estimation method and PLSs bootstrapping (N 5 5,000) were used to estimate the coefficients and significance of each path. The test results are shown in Figure 2. IT infrastructure can significantly and positively influence digital transformation strategy (β 5 0.288, t5 3.891, p < 0.001), thus H1 is valid, which shows that when providing more incredible IT infrastructure support can enhance the ability of enterprises to develop and implement amore complex and competitive digital strategy. It also demonstrates the importance of strengthening or developing IT infrastructure capabilities in response to changes in strategic posture. A very significant path coefficient (β 5 0.465, t5 6.591, p< 0.001) confirms the positive impact of digital strategy on digital transformation

DTS DT ITI TM

DTS1 0.824 DTS2 0.710 DTS3 0.786 DTS4 0.775 DTS5 0.737 DT1 0.828 DT2 0.737 DT3 0.815 ITI1 0.837 ITI2 0.712 ITI3 0.759 ITI4 0.770 TM1 0.835 TM2 0.842 TM3 0.866

IT infrff astrur ctut reIT infrastructure Digital

transfoff rmation strategy

Digital transformation

strategy

Digital Transfoff rmation

Digital Transformation

Note(s): *p < 0.05; **p < 0.01; ***p < 0.001

0.647*** 0.688***

Table 4. Cross loadings

Figure 2. Results of structure

model analysis

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performance, so H2 is supported, which confirms from the extensive sample practice that the success of enterprise digital transformation needs a digital transformation strategy to promote.

4.4 Mediation analysis This study uses the generally accepted bootstrap method to examine the mediating effect of digital transformation strategy between IT infrastructure and digital transformation. Specifically, we used the PROCESS SPSS macro developed by Hayes to analyze the data and tested the mediating effect of the digital transformation strategy by the bias-corrected method and the percentile method. The confidence level for the confidence intervals is 95%. The test results are shown in Table 5. According to the mediating effect evaluation criteria mentioned in the study of Prebensen and Xie (2017), this study concludes that the digital transformation strategy plays a fully mediating role in the relationship between IT infrastructure and digital transformation, thus supporting H3. In this study, the impact of IT infrastructure on digital transformation is indirect. IT infrastructure can support the capability of enterprise digital transformation strategy, which then influences the performance of digital transformation.

Themoderating effect of topmanagement was tested usingmultilevel regression analysis and the results are shown in Tables 6 and 7.Model 1 illustrates the impact of a single factor on a digital transformation strategy, Model 2 the impact of a single factor and a moderating factor, Model 3 the impact of a single factor, a moderating factor, and their interaction on a digital transformation strategy. By focusing on the interaction effects, our results support H4a (seeTable 6) andH4b (seeTable 7), proving topmanagement’s positivemoderating effect in the relationship between IT infrastructure and digital transformation strategy and between digital transformation strategy and digital transformation.

M/(IV)/(DV) Items Effect Coefficient Bias-coefficient Percentile Mediation

existenceSE T 95% CI 95% CI

DTS/(ITI)/(DT) Direct effect 0.037 0.072 0.521 �0.104 0.179 �0.104 0.179 Full Indirect effect

0.424 0.056 7.571 0.322 0.550 0.319 0.538

Note(s): Bootstrap 5,000 times, M: mediator; IV: independent variable; DV: dependent variable; digital transformation strategy (DTS); IT infrastructure (ITI) and digital transformation (DT)

Effect Variable Model 1 Model 2 Model 3

β T value β T value β T value

Main effect IT infrastructure 0.645 11.269 0.444 6.667 0.541 7.725 top management 0.340 5.111 0.329 5.100

Moderating effect

IT infrastructure 3 top management

0.206 3.556

Adjusted R2 0.413 0.486 0.517 R2 change 0.416 0.075 0.034 F change 126.983*** 26.126*** 12.647***

Note(s): ***p < 0.001; **p < 0.01; *p < 0.05

Table 5. Results of mediating effects

Table 6. Analysis of moderating role of top management in the relationship between IT infrastructure and digital transformation strategy

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Tomore visually represent themoderating effect of topmanagement, wemade Figures 3 and 4, where the dashed and solid lines represent the relationship between the horizontal and vertical axis variables under the conditions of high and low top management respectively. The difference in slope shows the positive moderating effect of top management in the IT-driven digital transformation process.

Overall, the results confirm all the hypothesized relationships among the constructs in the theoretical framework. IT infrastructure positively contributes to digital transformation strategy, which influences the digital transformation. Digital transformation strategy plays a fully mediating role in the relationship between IT infrastructure and digital transformation. In addition, top management can positively moderate the relationship between IT infrastructure

Effect Variable Model 1 Model 2 Model 3

β T value β T value β T value

Main effect digital transformation strategy

0.683 12.489 0.460 7.159 0.473 7.477

top management 0.361 5.607 0.416 6.305 Moderating effect

digital transformation strategy 3 top management

0.155 2.860

Adjusted R2 0.464 0.542 0.560 R2 change 0.467 0.080 0.020 F change 155.976*** 31.442*** 8.178*

Note(s): ***p < 0.001; **p < 0.01; *p < 0.05

1

2

3

4

5

Low IT infrastructure High IT infrastructure

D ig

ita l s

tr at

eg y

Low top management High top management

1

2

3

4

5

Low digital strategy High digital strategy

D ig

ita l t

ra ns

fo rm

at io

n

Low top management

High top management

Table 7. Analysis of

moderating role of top management in the

relationship between digital transformation strategy and digital

transformation

Figure 3. The moderating effect of top management in

the relationship between IT

infrastructure and digital transformation

strategy

Figure 4. The moderating effect of top management in

the relationship between digital transformation

strategy and digital transformation

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and digital transformation strategy and between digital transformation strategy and digital transformation. The results of hypothesis testing are summarized in Table 8.

5. Discussion and conclusion This study aims to explore a new path for IT resources to empower the digital transformation of enterprises by empirically testing themediating role of digital transformation strategy and themoderating role of topmanagement. The findings enrich the insights on IT value creation in the context of digital transformation and the path to achieve digital transformation in enterprises.

In this study, the impact of IT infrastructure on an enterprise’s digital transformation is indirect and the digital transformation strategy plays a fully mediating role in this process. This result reaffirms that IT investment alone does not guarantee to improve the firm performance and that business value can only be created when IT resources are integrated with other capabilities (Dong and Yang, 2019; Peng et al., 2016). Focusing on digital transformation strategic capabilities would be more valuable and meaningful. Our study demonstrates that companies with an edge in their IT infrastructure can better integrate digital resources to react to and support the choice and implementation of firm strategies, allowing companies to reach a greater degree of digital strategic capabilities (Vial, 2019; Isensee et al., 2020). They support organizational change and transformation and achieve better digital transformation expectations (Leischnig et al., 2017). This result is entirely consistent with some IT business value research. For example, several scholars have shown that the impact of IT on firm-level outcomes needs to be combined with other organizational resources and capabilities that act as intermediaries (Melville et al., 2004; Ravichandran, 2018; Nwankpa and Datta, 2017) and that strategic capabilities, as a critical factor in the innovational development of the firm, have a more significant impact on IT-driven firm performance (Hao and Song, 2016).

Second, this study shows that IT infrastructure and digital transformation strategy are viable path for enterprises to achievedigital transformation.On this path, IT infrastructure resources and capabilities are necessary for enterprises to facilitate transformation through digital transformation strategies. Digital technologies are widely embedded in organizational operations, facilitating organizational change and innovation and providing the foundation for formulating and implementing of digital transformation strategies. At the same time, the digital transformation strategy can guide enterprise IT to create value aligned with the transformation goals. The two complement each other to drive enterprise digital transformation (Tsou and Chen, 2021). Therefore, this study supports firms to increase their investment in new technologies and apply digital technologies to change and innovate the value creation pathway that enterprises previously relied on to maintain competitiveness (Vial, 2019). This study is a response to the current calls for research related to digital transformation strategy. Some views suggest that firms need to develop a digital transformation strategy tomanage the complexity of digital technologies and thus leverage the benefits of digital technologies for digital transformation (Matt et al., 2015; Yeow et al., 2018). This study provides theoretical and practical evidence for these views.

Hypotheses Path Results

H1 IT infrastructure → Digital transformation strategy Supported H2 Digital transformation strategy → Digital transformation Supported H3 IT infrastructure → Digital transformation strategy → Digital transformation Supported H4a Top management * IT infrastructure → Digital transformation strategy Supported H4b Top management * Digital transformation strategy → Digital transformation Supported

Table 8. Summary of hypothesis testing results

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Third, top management serves as an essential boundary condition that can facilitate the process of IT infrastructure, enabling digital transformation. Previous literature has shown that excellent management capabilities can facilitate successful strategic changes, such as digital transformation, leading to improved firm performance (Li et al., 2018). Our results support this view and prove that higher top management support, participation and leadership can better tap the strategic value of IT investment and translate it into the effectiveness of digital transformation. Digital transformation is a management issue that requires acquiring and deploying technical resources and addressing management issues such as redesigning business processes, investing in organizational capabilities and implementing strategic responses (Besson and Rowe, 2012; Li et al., 2018). Therefore, a top management team with the appropriate experience, knowledge and skills is more likely to identify and seize opportunities and guide the successful implementation of digital transformation (Ukko et al., 2019).

5.1 Implications for research This study contributes to the research of information system and digital transformation. First, this study extends IT business value-related research by exploring the value creation path of IT infrastructure in digital transformation (Melville et al., 2004; Kohli and Grover, 2008). How firms build competitive advantages based on their IT investments has always been a vital issue for researchers and practitioners in the IT/IS field (Kohli and Devaraj, 2003). While there has been a large number of studies showing the positive impact of IT resources on firm performance (Suoniemi et al., 2020; Ravichandran et al., 2005; Braojos et al., 2019; Chakravarty et al., 2013), there is minimal research on the contribution of IT in the specific context of digital transformation (Nwankpa and Datta, 2017). This study provides empirical evidence of the impact of IT infrastructure on digital transformation through digital transformation strategy, thus providing new ideas on IT value creation. Furthermore, by demonstrating the mediating role of digital transformation strategy between IT infrastructure and transformation performance, we enrich previous explorations of mediating factors between IT and firm-level outcomes and contribute to developing a research stream on imperative strategic perspective (Rivard et al., 2006).

Second, our study contributes to the existing digital transformation theory by demonstrating the impact of the complementary effects of IT resources and digital transformation strategy on digital transformation. Although previous studies have examined the antecedents of successful digital transformation of enterprises, such as technology use (Eller et al., 2020) and digital transformation strategy (Wang et al., 2020). These studies have not provided a conclusive result on the micro-level mechanisms between IT, digital transformation strategy and transformation performance (Tsou and Chen, 2021). This study explores the impact of IT and digital transformation strategy on digital transformation. It forms a new path for IT-driven digital transformation based on a strategic perspective, which has significant theoretical value for developing existing research on the mechanisms of digital transformation.

Third, this study contributes to the literature on organizational management and differentiated value creation by exploring the role of top management in the digital transformation process. We find that the impact of IT infrastructure on digital strategy and the degree to which it transforms into digital transformation performance, depends on top management capabilities. Top management can be complementary to IT resources and digital transformation strategy. It can enhance the extent to which IT supports digital transformation strategy and digital transformation strategy promotes the realization of digital transformation. These results enrich the boundary conditions for the value creation of IT resources and digital transformation implementation while having clear theoretical

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implications for developing both perspective on IT-enabled organizational capabilities and the literature on complementary capabilities (Benitez et al., 2018).

5.2 Implications for practice This study provides valuable insights for enterprises investing in IT and implementing digital transformation. First, IT infrastructure investments are necessary for enterprises undergoing digital transformation. However, managers must focus on digital transformation strategies to realize IT business value rather than seeing only the superficial return on IT investments. IT infrastructure indirectly facilitates digital transformation by supporting enterprises’ digital transformation strategy capabilities. Therefore, managers’ investment decisions in new IT should be guided by digital strategy. An important criterion should be the extent to which IT supports and enhances the digital transformation strategy. This helps managers guide their IT department’s work and evaluate IT investment’s contribution to their transformation performance, rationalizing IT resources and exploiting this IT infrastructure to exploit their relative strength.

Second, this study can help managers address the growing challenges posed by emerging digital resources and digital capabilities. The study finds that superior IT infrastructure capabilities may be a necessary but insufficient condition for digital transformation. A digital strategy must guide digital transformation with competitive advantages to deploying IT resources for transformation purposes. Therefore, managers should look for opportunities to invest in digital resources and build firm digital strategic capabilities. Firms can construct digital transformation strategies through internal innovation and change, or external cooperation and consultation, so as to coordinate and implement digital transformation. Our findings can guide practitioners on how to manage the digital transformation process of enterprises.

Third, it helps to stimulate systematic efforts and practice of top managers in IT management and strategy formulation and implementation. Top management is essential in mining IT value and managing transformation activities to facilitate digital transformation realization. In this context, managers need to support, engage and have the appropriate capabilities to guide IT to deliver value in a direction alignedwith the strategic goals of digital transformation. Therefore, companies should upgrade or update the digital skills and capabilities of their top management teams internally (e.g. through training) or externally (e.g. through recruitment, collaboration and consulting) while introducing new leadership roles (e.g. CDO) to adapt to the ever-changing external environment.

5.3 Limitations and future research direction Several limitations must be considered when interpreting our results and conducting future research. First, this study only uses a sample of 180 Chinese SMEs for validation. Considering that such geographical and sample size limitations may threaten the generalizability of the research results to a certain extent, subsequent research must enrich the sample data sources and compare the obtained and available results. Second, this study only focuses on the nature of digital transformation strategy without further consideration of strategic categorization. Managers may be unable to identify specific strategic actions based on our results. This limitation allows future digital transformation strategy researchers to delve into the mechanisms of differentiation across strategy types. Third, the results of this study are the summary and distillation of relevant theoretical research and the everyday experience of digital transformation in various industries,without further exploringmore complex situational factors in various industries. Digital transformation is an industry phenomenon, so it is essential to analyze the micro-foundations of our models in different contexts. Therefore, we encourage future researchers to expand and refine our results by setting more scenarios.

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Corresponding author Yao Yu Xu can be contacted at: [email protected]

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