The status quo of digital transformation in China: A pilot study

Abstract

BACKGROUND:

As the digital economy evolving as a nation-level strategy of China, firm decision-makers have shown increased interest in implementing digital transformation. However, they lack strategic guidance towards the realization of digital transformation.

OBJECTIVE:

This study aims to provide a holistic and comprehensive understanding of the status quo of Chinese firms’ digital transformation.

METHODS:

We fulfill this task by combining qualitative and quantitative methods. First, a conceptual model and an associated survey tool are developed based on an in-depth literature review and field practitioners’ opinions. The status quo of digital transformation is decomposed into 5 dimensions. Second, empirical survey data collected from 282 Chinese firms are analyzed and interpreted both in general and across industry types and ownerships.

RESULTS:

We find that the majority of Chinese firms reach a consensus on the strategic importance of digital transformation and agree on the importance of technological and human resources. In general, firms in the information technology sector scored higher in all five dimensions compared with firms in the manufacturing sector, and private-owned firms scored higher in all five dimensions than state-owned firms.

CONCLUSIONS:

This pilot study set a basis for the development of a maturity model of digital transformation and offers practical insights for Chinese firms to initiate and implement digital transformation projects.

Keywords

Digital transformation China status-quo survey

Mengling Yan is an assistant professor, she received her Ph.D. in Management from Peking University. Her research interest focuses on ICT-enabled organizational learning, organization strategic renewal, and digital transformation.

Jiapeng Liu is an undergraduate at the School of Economics and Management of Beijing University of Posts and Telecommunications, Beijing, China. His major is E-commerce.

Shengwen Dou is an undergraduate at the School of Economics and Management of Beijing University of Posts and Telecommunications, Beijing, China. His major is E-commerce.

Yueyi Sun is an undergraduate at the School of Economics and Management Beijing University of Posts and Telecommunications. Her major is Information Management and Information Systems.

Yishu Dai is an assistant professor of Information Management and Information System at Beijing Technology and Business University. She received her Ph.D. in Management from Peking University. Her research interest focuses on ICT-enabled value co-creation, digital transformation and innovation.

Xiaoying Dong is an associate professor of Guanghua School of Management at Peking University. Her research interest focuses on knowledge management, organizational learning, enterprise competitive intelligence System, enterprise informatization and digital transformation.

1 Introduction

Digital transformation is defined as the use of digital technology to enable major business improvements, including enhancing customer experience, streamlining operations, or creating new business models [1, 2]. Since 2016, the Chinese government has listed the digital economy high on the agenda of the blueprint of innovative growth [3]. And the development of the digital economy has been an important topic in the government work report in the past consecutive three years. In the meanwhile, Chinese firms have actively initiated digital transformation projects.

Despite surging attention from the Chinese government and practitioners, many firm decision- makers are still facing many challenges in implementing digital transformation projects. These challenges include articulating the perception, goals, roles of leaders, and investments of digital transformation at the strategic level, identifying the key technological resources, human resources, and key activities at the operational level, and cultivating firm-level capabilities and performance at the outcome level.

Extant studies shed light upon these challenges by discussing related theoretical concepts or by focusing on specific aspects of digital transformation with empirical support. For example, some pioneering studies have discussed the formation of digital transformation strategies [4], the assumptions of digital innovation management [5], the data integration capabilities[6], and the value-capture problem in the digital economy [7]. Vial et al offered a framework of digital transformation based on an in-depth review of 282 digital transformation-related studies and related theoretical perspectives [2]. In terms of empirical studies, the majority of studies employ case studies and other qualitative methods to gain a deeper understanding of a specific issue [8, 9]. For example, Gaurav conducted a longitudinal study of two digital startups in the crowdfunding domain and identify the core attributes driving such transformation in digital ventures [10]. Yeow and his colleagues conducted a longitudinal analysis of a B2B company’s journey to enact its B2C digital strategy, using the dynamic capabilities approach [11]. Thor $\overset{´}{e}$ n and his colleagues examine managerial control and tensions caused by digital open practices by drawing on qualitative interviews with managers from a prominent corporation [12]. Although abundant, extant studies are limited in providing a holistic description of the status quo of digital transformation. A holistic description is important because digital transformation is a comprehensive and systematic project that involves improvements at all levels of the firm. A holistic description of the status quo helps firms to gain insights into the trend and overall processes of initiating digital transformation at a micro-level. At the same time, it also helps institutions or governments to develop maturity models and evaluate the progress of the digital transformation of enterprises at a macro-level.

This study aims to understand the status quo of Chinese firms’ digital transformation through a holistic and quantitative description. We fulfill this task by combining qualitative and quantitative methods. First, a conceptual model and an associated survey tool are developed based on an in-depth literature review and field practitioners’ opinions. As a result, the status quo of digital transformation is decomposed into 5 dimensions, namely the strategy, the resource, the process, the capability, and the performance dimensions. Second, empirical data collected from 282 Chinese firms are analyzed and interpreted both in general and across industry types and ownerships. The findings set a basis for the development of a maturity model of digital transformation and offer practical insights for Chinese firms.

In the following section, we first introduce the research design that consists of a qualitative study followed by a quantitative study. Then we describe the status quo of digital transformation based on the survey data collected from Chinese firms. Next, we conclude our study by discussing the theoretical and practical implications of our findings.

2 Methods and materials

To provide a holistic and quantified description of the status quo of digital transformation in China, the research team employs a mixed-method design characterized by a qualitative study followed by a quantitative study [13]. The qualitative study aims to propose a conceptual model and a survey tool, and the quantitative study aims to depict the status quo based on a set of nationwide survey data. Figure 1 shows the logical connections between the qualitative study and quantitative study. In the following, the data collection, data analysis, and data interpretation steps of the qualitative study and quantitative study are introduced respectively.

Fig.1

A mixed method research design.

2.1 The qualitative study

The qualitative study was based on a systematic and in-depth review of academic studies, industrial reports from domestic and international leading consulting companies, and one-on-one interviews as well as symposiums with experts and practitioners in the digital transformation field. In total, the academic studies include 31 theory-driven research articles and 32 practice-oriented research articles, typical journals including MIS Quarterly, Research Policy, Strategic Management Journal, MIS Quarterly Executive, Harvard Business Review, MIT Sloan Management Review, and California Management Review. The number of industrial reports we have collected is 77, typical consulting companies include Forrester, Gartner, General Digital, IDC Consulting, IDG consulting, Mckinsey, PWC, SAP, and Accenture. Besides, we conducted interviews and symposiums with 24 field experts, which consisted of 5 scholars and 19 field practitioners, who paid close attention to the digital transformation trends in China and held the position of CIO or executive positions in leading companies. They were invited to share their observation and own experience of implementing digital transformation in China. As a result, we select six representative and revelatory case companies to identify key activities during digital transformation, which offers empirical support to the key dimensions that depict the status quo.

The research team went through the research studies and industrial reports and coded a set of key dimensions that depicted the status quo of digital transformation [14 –16]. Then, based on this result, a team of experts consists of both scholars and practitioners in the digital transformation field were called on to discuss the relative importance of the initial dimensions and to generate higher-level dimensions to depict the status quo using the Delphi method. The Delphi method took several rounds. Experts proposed individual opinions separately in each round, and each opinion was discussed among experts before the start of the next round. By the end of the Delphi method, field experts converged on 5 dimensions to depict the status quo of digital transformation in China, namely the strategy dimension, the resource dimension, the process dimension, the capability dimension, and the performance dimension. Figure 2 shows the 5 dimensions and their sub-dimensions.

Fig.2

The conceptual framework for depicting the digital transformation.

First, the strategy dimension reflects organizational blueprint that supports firms in governing the transformations to create value [4, 17]. The digital transformation strategy explains the motivation and targets of transformation and determines subsequent resource allocation and associated change behaviors. In this study, the sub-dimensions of digital transformation include the motivation, the scope, the targets, investments, and transition period estimation. Second, the resource dimension reflects digital-related resources needed or exploited by firms in the transformation [18]. The resource dimension includes the knowledge resource and the technology resource as two types of key resources that are dispensable in the digital transformation process [19]. While the knowledge resource is hard to be directly measured, we use the most needed types of human resources and the responsibilities of key human resources as proxy variables [20]. Third, the process dimension depicts the detailed activities that a company initiates during its digital transformation. While the operation and innovation sub-dimensions describe the internal activities, the marketing and ecology sub-dimensions describe the external activities with customers and cooperative partners [21, 22]. Fourth, the capability dimension reflects the organizational capabilities enabled by IT and data resources [23, 24]. The capability dimension is further divided into resource integrating capability, data analyzing capability, and insights predicting capability. Finally, the performance dimension is embodied both in financial and non-financial indicators.

2.2 The quantitative study

Based on the qualitative study and the conceptual framework shown in Fig. 2, the research team developed a survey tool by referring to existing mature scales, converged descriptions in case studies, and expert opinions. Some of the questions in the survey are based on mature scales from widely cited academic literature, including the innovation culture, the resource integrating, analyzing, and predicting capability [25] and financial and non-financial performance indicators. Some of the questions in the survey are based on the converged findings in multiple interviews with representative companies, such as the perception of government policies, innovation incentives, and transformation activities under the process dimension. As an exploratory and pilot study, some of the questions in the survey are based on expert opinions. For example, the majority of questions under the strategy dimension are developed by the research team.

To ensure the reliability and validity of each measurement, we carefully performed the translation and back-translation between Chinese and English with the help of three bilingual scholars [26]. Besides, we conducted a careful pre-test before we formally collected our survey data. The pretest was conducted in 2018 between July and October, it includes complete and valid answers from 160 Chinese firm senior managers, who are MBA and EMBA students of one of our authors. We refined the structure, questions, as well as the wording of the survey based on the results and suggestions from the respondents.

To reach a wider range of respondents, we collaborated with a Chinese consulting company, which provides consultancy services to both small and large firms in the digital transformation field. The formal survey was distributed to more than 1000 firms, and 282 complete and valid answers were recycled. The final sample spanned across 19 industries and 25 provinces in China. In the final sample, state-owned firms, private-owned firms, and foreign-owned firms take the percentage of 39.0%, 51.4%, and 9.6% respectively. Firms in the manufacturing industry take a percentage of 30.2%, and firms in the information and service industry take a percentage of 12.8%, while firms in other industries take a percentage less than 7.5%.

The quantitative data were analyzed by descriptive analysis using SPSS and visualized using radar maps. In the next section, we introduce and interpret the survey results in each of the strategy, resource, process, capability, and performance dimensions to give a coarse-grained description of the status quo of digital transformation in China. Besides, we contrast results between state-owned and private-owned firms, as well as firms in the manufacturing industry and firms in the information and service industry to give a fine-grained description.

3 Findings

3.1 The strategy dimension

In general, the majority of Chinese companies reach a consensus on the strategic importance of digital transformation.

The strategy dimension is further divided into sub-dimensions include perception of policy and competition environments, the importance of the digital strategy, scope of the digital strategy, goals of the digital strategy, and the duration period estimated.

The surveyed firms pay close attention to government policies (see Fig. 3a) and competitive environments (see Fig. 3b). Typical activities of paying attention to the government policies include paying consistent attention to the release of domestic and international policies, maintaining close cooperation with government departments, and responding to policy calls. Using a five Likert scale, we find that the average score of “paying attention to the policies of digitalization from the Chinese government” is 4.17, and the average score of “maintaining close cooperation with relevant government departments” and “responding to policy calls regarding digitalization” are both 3.95. And the average score of “paying consistent attention to the international policies” have dropped in 2019 compared with that in the last year, showing that Chinese companies pay more attention to domestic government policies than international policies on digital transformation. In terms of competitive environments, many companies perceived fiercer competition within industries than that across industries.

Fig.3

Perception of environment.

Digital transformation has been a key strategy for companies, but its importance still needs to be improved. There are 26.1% of the surveyed companies believe that the digital strategy supports their core business strategy. 22.4% of companies believe the digital strategy assists companies with other functional strategies and 21.3% of them believe the digital strategy as important as the company’s core business strategy. Only 11.6% of companies believe that digital strategy is the core of the companies’ overall strategy. Besides, private-owned companies tend to pay more attention to the digital strategy than state-owned companies (T = 1.48, p < 0.05). Most of the state-owned companies believe that the digital strategy plays a supportive role in assisting the development of other businesses. Similarly, companies in the information technology sector place greater emphasis on digital transformation then companies in the manufacturing sector (T = 2.011, p < 0.05). As only one-third of the surveyed companies believe that the importance of digital strategy is no less than the core business strategy of the companies, we argue that the importance of digital strategy remains to be improved as the key strategy.

The scope of digital transformation may include the digitalization of final products, customer service, business processes, and business models [27]. In our survey, 32.5% of companies focus on the digitization of business processes and 26.8% of companies focus on digitization of customer service, 21.1% of companies focus on the digitization of final products and 19.7% of companies focus on the digitization of business models. It is worth noting that the percentage of digitization of final products has increased slightly in 2019 compared with that in 2018.

Companies initiate digital transformation to reach many different goals. Some of the goals are short-term goals and oriented to internal processes, some of the goals are long-term goals and oriented to external relationships and opportunities. Therefore, these goals are divided into three categories. The first category is to enhance market competitiveness, including increasing industry influence, expanding business boundaries, seizing future development opportunities, and improving environmental adaptability. The second category of goals is to improve customer loyalty and satisfaction. The third category of goals is to reduce operating costs and improve the efficiency of operations (production operations, service operations, etc.). As is shown in Fig. 4, the survey result shows that the third category of goals, namely reducing operating costs and improving operating efficiency, are the most frequently selected goals, taking a percentage of 40.7%. Meanwhile, 47% of companies aim at the first category of goals, and 12.3% of companies select the second category of goals.

Fig.4

The main goals of digital transformation.

Abundant academic studies have shown that digital transformation is a type of transformation that calls for senior support and participants [28]. According to our survey, CEO (35.7%) or chairmen (33.3%) is in charge of digital transformation in two-thirds of companies. CIO is in charge of digital transformation in 14.7% of companies. Compared with last year, the proportion of senior managers leading digital transformation has increased from 49.4% to 68.9%. Besides, nearly 40% of CEOs are directly involved in the promotion and implementation of digital strategies, which adequately proves that the management attaches great importance to digital transformation.

More than half of companies have started digital transformation for less than 3 years and more than half of companies estimate that it will take 3–5 years for digital transformation. Our research shows that by 2019, 59.2% of companies started digital transformation 0–3 years ago, 26.4% of companies started digital transformation 4–10 years ago and only 5.7% of companies started digital transformation for more than 10 years. Also, 61.6% of companies estimate that it will take 3–5 years for digital transformation. 22.5% of companies estimate that it will take 6–10 years for digital transformation. 2.6% of companies estimate that it will take more than 10 years for it, and only 13.3% of companies estimate that it can be completed in 1–2 years. Besides, the estimated time of private-owned companies is significantly less than state-owned companies.

3.2 The resource dimension

In general, Chinese companies have reached a consensus on the types of leading technological resources but differ greatly in the technological basis of implementing digital transformation projects. As for human resources, the attention of digital project leaders is scattered in a wide variety of activities, and the most needed talents are digital project managers, strategic leaders and people who can implement the strategic plans.

According to our survey, the top 4 widely used digital technologies are big data analysis and mining, mobile technology, cloud computing and the Internet of Things, each taking a percentage of 18.6%, 17.3%, 16.1%, and 13.7% respectively. While technologies like 3D printing, blockchain, virtual reality, and other technologies are rarely used by companies. Besides, the application of digital technology in the information technology sector is ahead of the manufacturing sector.

System and data interoperability are the technological basis of implementing digital transformation projects. As is shown in Fig. 5, the proportion of company information systems that achieve data interoperability is close to 30%. Our research shows that 20.8% companies have a variety of information systems, but they have not achieved system interoperability, 25.8% companies have a variety of information systems which can achieve system interoperability, but not data interoperability, 21.9% companies have a variety of information systems which can achieve data interoperability, and only 3.1% of the companies do not use information systems. The results show that the data interconnection of company information system needs to be further improved. System and data interoperability in the information technology sector are better than those in the manufacturing sector (T = 1.672, p < 0.05), but the system and data interoperability in private-owned firms have no significant differences from that in state-owned firms (T = 0.554, p > 0.05).

Fig.5

The construction of information systems in companies.

We depict the condition of human resources investment from aspects including the key attentions of digital project leaders, the organization of digital projects, and the most needed digital talents. The survey results show that the attention of digital project leaders is scattered many activities. As is shown in Fig. 6, 23.5% of leaders focus on integrating digital technology, business and resource, and only 5.7% of leaders focus on reducing the security risk of digital technology. Compared with last year, the percentage of leaders that focusing on generating profits by digital technology has risen from 7.4 percent to 15.1 percent.

Fig.6

The primary focus of leaders in digital transformation projects.

The information technology (IT) department is still the core department that implements the digital transformation projects. Our survey shows that 40.6% of the digital strategy is directly driven by the information technology (or IT) department; 15.7% of companies did not have related teams or departments; 13% of digital transformation is mainly responsible for the Digital Transformation Committee, which is composed of senior managers. Only 3.8% of companies set up relatively independent digital subsidiaries for digital transformation.

During digital transformation, digital project managers, strategic leaders and people who put the plans into practice are the most needed talents. Our survey shows that 22.2% of companies lack digital project managers. 20.8% of companies lack digital company strategic leaders. 8.5% of companies lack a practitioner who implements these strategic ideas. Compared with the survey results of 2018, we find companies paid more attention to the organizational arrangement rather than technological application during digital transformation.

3.3 The process dimension

The process dimension depicts the detailed activities that a company initiates during its digital transformation process. Overall, companies have carried out diverse activities actively both within and beyond the organizational boundaries. Within the boundary, companies initiate changes in original operation processes and innovation systems. Beyond the boundary, companies shift their ways of communication with customers and pay more attention to the ecosystem they have taken part in. In general, private-owned companies score higher than state-owned firms in almost all sub-dimensions, and companies in the information technology and service sector score higher than companies in the manufacturing sector. In the following, findings regarding each of the sub-dimensions of the process dimension, namely digital operation, digital innovation, digital marketing, and digital ecology, are reported.

3.3.1 Digital operation

For manufacturing companies, digital operations are embodied in the following five aspects: (1) production materials, components, semi-finished products, and finished products have digital labels; (2) manufacturing facilities, machines, and production lines are equipped with data collection functions; (3) real-time collection of production process data, (4) the information system runs through all production procedures, and (5) firm executives can obtain production information immediately. Different from last year’s finding where the fifth aspect was selected as the most digitized aspect in manufacturing firms, the second aspect becomes the most digitized of the five indicators above with a score of 3.31. Therefore, we argue that collecting data from equipment and machinery has attracted more attention and investment from the manufacturing firms. More details of digital operation can be found in Fig. 7. Overall, private-owned companies scored higher in the above (3), (4), and (5) sub-dimensions of digital operation than state-owned companies except for the second aspect (T₍₃₎ = 2.889, p < 0.05; T₍₄₎ = 2.195, p < 0.05; T₍₅₎ = 2.015, p < 0.05).

Fig.7

Process digitalization in the manufacturing industry.

Since the digital operation is closely related to information system implementation, we also survey questions like to what extent different systems are connected and to what extent different formats of data can be exchanged. The data shows that the information system implementation condition of private companies is slightly better than that of state-owned companies. The two types of companies scored relatively high in terms of “the firm has all realized mobile office” and “the firm has constructed a reasonable, standard and flexible digital platform”. Most state-owned firms have not yet achieved “connection of systems”, “connection of databases&rdquo, “access to management data at any time”, and “timely communication between people, things and equipment”.

3.3.2 Digital marketing

Digital marketing is the process by which companies acquire user information, interact with users, and apply user data through various digital channels. This work describes the digital marketing activities from three aspects, namely user interaction channels, user data acquisition, and user data usage.

The most commonly used interaction method that companies employ to get in touch with their users is the company’s official website. Survey data shows that companies use a variety of online and offline interaction tools, and the company’s official website is the most frequently adopted way, with an average score of 3.63. WeChat platform ranks second with an average score of 3.53, and email ranks third with an average score of 3.42. By contrast, Weibo and crawler programs are rarely used for interaction. Compared with the survey results of 2018, the top three popular methods that companies use to interact with their users remain unchanged in 2019. The only difference is that the WeChat platform becomes the most popular method in 2019. Private-owned firms scored higher in almost all communication methods with users, and firms in the information and service sector scored higher than companies in the manufacturing sector. Also, we find that the information industry tends to focus on the mobile-based methods, such as WeChat platforms and firm apps, while the manufacturing industry tends to rely more on the PC-based methods, such as the company’s official website and emails.

In terms of user data acquisition, the survey shows that firms have acquired data regarding user demographics and transaction, but have limited data on users’ behavior, preference, and transaction situations. As is shown in Fig. 8, companies scored highest in user’s demographic data with an average score of 3.3, which is followed by the score of user transaction data and user view and click data, both have a score of 3.16. The scores of online behavior data, user scene data and user preference data are low, which are 2.98, 3.0 and 3.04 respectively.

Fig.8

Types of user data obtained by the companies.

The survey results show that companies are better at using user data to providing personalized services, reproduce business processes and provide precise marketing. According to the survey data, the use of user data by firms is mainly reflected in provide personalized services, reproduce business processes, and providing precise marketing, with average scores of 3.40, 3.39, and 3.37. However, companies scored relatively lower in using user data to guide innovation research and optimize logistics distribution. Besides, in all aspects of data use activities, companies in the information industry scored significantly higher than companies in the manufacturing industry, and private-owned companies scored higher slightly higher than state-owned companies.

3.3.3 Digital ecology

Digital ecology mainly provides companies with partners from different industries and promotes the integration of resources between companies and partners [29]. In this section, we describe the digital ecology of Chinese companies from the following two aspects, namely changes of corporate partnerships in a digital environment, and the types of resources to integrate in an ecology.

First of all, the changes in the companies’ ecological network are mainly reflected in (1) the number of partners within the same industry, (2) the number of partners from other industries, (3) the number of digital companies, (4) whether there are loosely-coupled partnerships, (5) the frequency of data exchange among partners, and (6) the number of technological products and services that are delivered by partners. Our data shows that while the ecological network between companies has established, the data exchange between partners is infrequently. Many companies reported that “partners come from more industries”, “more technology products and services are delivered by partners”, and “the number of digital companies among partners has grown significantly”.

Secondly, the most important resource that a firm integrates into the ecosystem is market resources, while the least important resource is traffic resources. As is shown in Fig. 9, market resources and technology resources are the most important resources integrated by the firm in the ecosystem, with average scores of 3.54 and 3.53, followed by the knowledge resources, service resources and relationship resources, with average scores of 3.51, 3.49, and 3.48. In contrast with the findings in 2018, while the top three resources were technology resources, relationship resources and service resources in 2018, the top resources in 2019 is the market resource. Besides, private-owned companies scored higher than state-owned companies in integrating all types of resources, and companies in the information industry scored higher than companies in the manufacturing industry.

Fig.9

Resources integrated by a company in its ecosystem.

3.3.4 Digital innovation

Digital innovation is an important step for firms to realize digital transformation. This work approach digital innovation activities from two aspects, namely innovation methods and innovation incentives [30].

Leveraging internal resources for innovation is the most important way for Chinese companies. As is shown in Fig. 10, among all the innovation method, the most adopted way is innovating internally with an average score of 3.62, while “cooperative innovation with partners’ resources” ranks second with an average score of 3.38. And the least adopted way of innovation is “acquiring new capabilities through incubation of startups”. A more fine-grained analysis reveals that companies in the information industry have more diverse innovation methods and stronger innovation capabilities, while companies in the manufacturing industry mainly rely on internal innovation and partner innovation.

Fig.10

Methods that companies prefer to initiate digital innovation.

Among the six main innovation incentives, job promotion is the main incentive mechanism for digital innovation. The survey data shows that providing employees with career promotion opportunities scored highest with an average score of 3.32; followed by providing employees with generous remuneration, with an average score of 3.07. Setting up a separate KPI assessment for the digital transformation team ranks third, with an average value of 2.92. And the least adopted incentive mechanism is providing shareholding opportunities for employees, with an average score of only 2.57. In the evaluation of various incentive mechanisms, it is obvious that private-owned companies scored significantly higher than state-owned firms, and companies in the information industry scored higher in all incentive mechanisms than companies in the manufacturing industry.

3.4 The capability dimension

Overall, Chinese companies scored lower on the capability dimension than the other four dimensions. In terms of the three sub-dimensions, their resource integration capabilities scored slightly better than the data analyzing and insights predicting capabilities. However, in different industries and ownerships, the scores of the capability dimension reflect obvious differences. The private-owned companies scored higher than state-owned companies (T = 3.469, p < 0.01), and companies in the information technology and service industry scored higher than companies in the manufacturing industry (T = 3.059, p < 0.01).

The ability to integrate resources is reflected in four aspects: (1) independent development of big data analysis platforms, (2) real-time access to various forms of internal and external data, (3) continuous learning of cutting-edge technologies, and (4) rapid recruitment of talents. As is shown in Fig. 11, the survey data shows that the average score for resource integration capacity is 3.04 on the five-Likert Scale, indicating that the majority of companies have a moderate level of resource integrating capability. The scores of the second and third sub-dimensions are better than the first and fourth dimensions, indicating that the company mainly focuses on data acquisition and new technology learning, but is weak in the ability to integrate talents and technical resources. There is a gap between state-owned companies and private-owned companies in terms of resource integration capability, especially in terms of “independent development of big data analysis software platforms”. Companies in the information industry scored higher in resource integration capabilities than those in the manufacturing industry.

Fig.11

Companies’ self-evaluation of the resource integration capability.

Data analysis capabilities are reflected in the ability to: (1) use big data analysis software and tools, (2) analyze unstructured data in real-time, (3) extract effective information and (4) support decision-making. As is shown in Fig. 12, the average score of a company’s data analysis capability is 2.84, indicating that on average, the firm does not yet have the data analysis capability. The second aspect has the lowest score, with an average of only 2.79. Although both state-owned and private-owned companies are weak in data analysis capability, state-owned companies still fall behind. Compared with companies in the information industry, companies in the manufacturing industry scored lowest in analyzing unstructured data such as text and voice in real-time, rather than supporting decision-making with the support of big data analysis.

Fig.12

Companies’ self-evaluation of the data analysis capability.

The company’s insights predicting capability is reflected in the ability to: (1) real-time insights into the market (2) predict the competitive environment (3) understand and predict customer behaviors (4) release early warning signals for public opinions, and (5) predict the behavior of competitors. As is shown in Fig. 13, the overall average score for this capability is 2.90, indicating that the majority of companies lack this capability. Besides, the score in the fifth dimension is significantly lower, with an average score of 2.84. The survey data shows that private-owned companies have significantly better insights predicting capability than state-owned companies. And companies in the information industry scored higher than companies in the manufacturing industry. Information industry companies have weak capabilities in “real-time insights into the market” while manufacturing companies have the lowest scores in “accurate prediction of the competitive environment”.

Fig.13

Companies’ self-evaluation of the insights predicting capability.

3.5 The performance dimension

The performance dimension looks at both process and outcome performance indicators as well as financial and non-financial performance indicators. In general, the companies score higher in non-financial performance indicators than in financial indicators. Across different industries and different ownerships, the scores of both financial and non-financial performance dimensions show significant differences. Companies in the information industry scored higher than companies in the manufacturing industry (T_Financial = 2.987, p < 0.01; T_{Non - financial} = 2.645, p < 0.01). And private-owned companies scored higher than state-owned companies in both types of indicators (T_Financial = 2.748, p < 0.01; T_{Non - financial} = 2.429, p < 0.05).

As is shown in Fig. 14, companies have a higher average score in non-financial self-evaluation than self-reported financial performance. Financial performance indicators like total sales and market share have an average score of 3.00 and 2.99, and non-financial performance indicators like industrial influence, future development opportunities, customer response speed, and business boundary expansion have an average score of 3.29, 3.24, 3.20, and 3.11 respectively. Companies in the information industry scored higher than companies in the manufacturing industries in both financial and non-financial indicators. It is reported that companies in the information industry have significantly improved their market competitiveness, customer service, and financial performance, while manufacturing firms have improved their firm competitiveness and customer service level, but has not yet achieved short-term financial performance. In general, the benefits brought by digital transformation to firms have been reflected in non-financial indicators, but not yet in financial indicators. Private companies scored higher than state-owned companies. On average, state-owned firms have made some progress in “improving industrial influence” and “grasping future development opportunities”. The biggest benefits for private firms are “become more responsive to customers”, “improving industrial impact” and “improve companies’ ability to seize future opportunities”.

Fig.14

Companies’ self-evaluation of financial and non-financial performance.

Operational efficiency is measured with indicators like operational costs, communication and decision efficiency, business process refinement, individualized employee development, and cross-functional collaboration efficiency. As is shown in Fig. 15, on average, companies scored highest in business process optimization with an average score of 3.42. And companies scored lowest in “obvious drop in operational costs”, with a score of 3.21. The digital operation efficiency of private firms is obviously better than that of state-owned firms. From the self-evaluation results, private-owned companies scored higher than state-owned companies in terms of corporate communication and decision-making efficiency, business process optimization, and cross-department collaboration. The biggest gaps between the two are “operating costs” and “individualized employee development”.

Fig.15

Companies’ self-evaluation of Operational efficiency.

4 Discussion

Driven by policy guidance and market competition, Chinese firms have realized the necessity of digital transformation and have formulated digital transformation strategy for development. Digital transformation strategy has risen as a corporate-level strategy, and has been highly valued by senior managers. All of the functional and process strategies are encompassed under the digital transformation strategy, with a close focus on policy and the competitive environment. For most firms, digital transformation is initiated at an early stage, and their strategic goals are to improve internal operation efficiency and reduce operation costs, so as to improve their competitiveness [31]. For the time being, most companies still need a long time to complete their digital transformation.

Technical resources and human resources are the key resources in the digital transformation. In terms of digital technologies, big data technology, mobile technology, cloud computing and Internet of things are the main technologies currently invested by firms. However, investment in emerging technologies alone cannot effectively carry out digital transformation. Firms are suggested to build a solid foundation of infrastructure and achieve internal data interchange through system integration, standard unification and other means, so that data can be useful and valuable. In terms of talents, senior managers who have rich experience in implementing digital projects are the most needed talents. Technical experts who are familiar with cutting edge technologies are also in great need. However, at present, firms mainly introduce talents related to technology application, and fail to consider the security management of digitalized technology. Since the current strategic goals of the firm are still firm-oriented and lack of attention to external customers, there is no obvious demand for talents related to digital customer interaction and service.

Along the process dimension, companies gradually realize that data is the key resource and begin to focus on data collection in the process of production and operation. However, some companies still have many problems in the construction of information systems. In terms of the marketing sub-dimension, the differences between industries are significant, the information industry tends to focus on the mobile-based methods, while the manufacturing industry tends to rely more on the PC-based methods. Currently, companies are good at using user data to provide personalized services, reproduce business processes and provide precise marketing. In terms of ecology, firms have increased cooperation with digitalized technology firms, but the depth of cooperation and resource mobility among members in the ecosystem have not been significantly improved. In terms of the innovation sub-dimension, firms still focus on innovation with internal resources. Career promotion opportunities and generous remuneration are the main ways for firms to encourage internal innovation.

Driven by digital technology, the capability building of firms mainly centers on resource integration, data analysis and insights prediction. Resource integration capability is the first step, but at present, firms are still weak in the construction of integration capability. If data integration cannot be realized, then in-depth analysis capability and insights prediction capability cannot be realized at all. The weakness of capacity building is more evident in traditional manufacturing firms than firms in the information industry. We conclude that firms should pay more attention to the value of data, and there is still more work to be done in the collection, management and utilization of data.

Along the performance dimension, companied reported a higher self-reported in non-financial than financial performance. Besides, in terms of the overall performance outcomes, companies in the information industry scored higher than companies in the manufacturing industry, and private-owned companies scored higher than state-owned companies. The findings indicate that digital transformation projects have significantly altered the operational processes, but have not yet generate impressive financial outcomes.

5 Conclusion

This work depicts the status quo of digital transformation in China by elaborating the trends, distributions of selections, and detailed activities from the strategy, resource, process, capability, and performance dimensions with survey data from 282 Chinese firms across 19 industries and 25 provinces. These dimensions and their sub-dimensions are derived from a qualitative study based on in-depth literature review, consulting reports, and expert opinions. We find that the majority of Chinese firms reach a consensus on the strategic importance of digital transformation and key technological and human resources. In general, firms in the information technology sector scored higher in almost all dimensions compared with firms in the manufacturing sector, and private-owned firms scored higher in almost all dimensions than state-owned firms.

As a pilot study, there are several limitations to note in interpreting the survey results, which also points out future direction for subsequent research. First of all, a larger sample size is encouraged in future work to generate more accurate depiction for national situation. Second, future studies are encouraged use structured equation modeling to understand the interrelationships between these five dimensions. Third, this pilot study set a basis for the development of a maturity model of digital transformation and offers practical insights for Chinese firms. However, to establish the maturity model, future studies are encouraged to determine the weights of each dimension and sub-dimensions [32].

Footnotes

Acknowledgments

This work is financially founded by National Natural Science Foundation of China (71802028) and Young Scholar Research Foundation of BTBU (QNJJ2020-25).

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