Nothing Special   »   [go: up one dir, main page]
Next Article in Journal
AI-Driven Business Model: How AI-Powered Try-On Technology Is Refining the Luxury Shopping Experience and Customer Satisfaction
Previous Article in Journal
The Differential Effects of Augmented Reality and Product Presentation Strategies on Brand Recall: An Embodied Cognition Perspective
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JTAER
Volume 19
Issue 4
10.3390/jtaer19040147
jtaer-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Impact of Enterprise Digital Capability on Supply Chain Digitalization—From the Perspective of Supply Chain Cooperation

by
Sijie Chen
1 and
Zhaobo Tang
2,*
1
College of Economics and Management, Southwest University, Chongqing 400715, China
2
School of Economics and Business Administration, Chongqing University, Chongqing 400044, China
*
Author to whom correspondence should be addressed.
J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 3051-3066; https://doi.org/10.3390/jtaer19040147
Submission received: 28 August 2024 / Revised: 20 October 2024 / Accepted: 25 October 2024 / Published: 4 November 2024
(This article belongs to the Special Issue Digitalization and Sustainable Supply Chain)
Browse Figure
Figure 1
<p>Conceptual model.</p> ">
Versions Notes

Abstract

:
This paper explores in depth the mechanism of enterprise digital capability effects in supply chain digital development by reconstructing the supply chain cooperation capabilities (digital diffusion capability and digital collaborative capability). We use the questionnaire data covering 272 Chinese manufacturing enterprises and apply a structural equation model to test the hypothesis. The empirical result demonstrates that enterprise digital capability does not directly have a significant impact on supply chain digitalization, and the supply chain cooperation capabilities play a mediating role between an enterprise’s digital capability and supply chain digitalization. The results are robust as we thoroughly consider the direction of enterprise capabilities and verify the systematic requirements of supply chain digitalization and the high order of enterprise digital capability. These provide a theoretical basis for enterprises to promote the digital transformation of their supply chain through digital technology.

1. Introduction

Industry 4.0 is not only a technological change, but also an opportunity to seize the initiative in a new round of industrial revolution. Therefore, many enterprises have begun to reshape their development strategies in the guidance of Industry 4.0, emphasizing “cross-border” integration, and promoting the creation of fully linked ecosystems in different functional areas [1] to achieve supply chain digital transformation. Obviously, digitalization has brought significant benefits to the supply chain, such as increased information availability, optimized logistics practices, real-time collection of operational data, improved inventory management efficiency, and enhanced supply chain transparency [2,3,4]. Through digital transformation, enterprises are able to gain more flexibility and agility in developing their supply chain management strategies, enabling them to create more value [5,6,7]. Besides, this seamless end-to-end supply chain connectivity in the digital context helps enterprise more effectively meet the changing needs of customers and gain a competitive advantage [8].
Supply chain digitalization brings great benefits to enterprises; therefore, it has attracted widespread attention from scholars, and has become a vital research topic in operations management [7]. Besides, it also occupied a central position in the strategic planning of manufacturing enterprises [9,10,11]. Specifically, supply chain digitalization not only means the application of digital technology in supply chain planning, procurement, production, and logistics [12], but also emphasizes the systematic use of digital technology to reshape the process and mode of enterprise supply chain management [2,13]. Therefore, the realization of supply chain digitalization not only requires enterprises to reshape their business models and strategies [14], but also requires enterprises to transform their social relations and operational networks [15]. These pose challenges for enterprises, such as the application of digital technologies, the acquisition of new knowledge and skills by enterprises [16], and the establishment of a “digital mindset” by enterprises [15]. To address these challenges, it is necessary for enterprises to develop capabilities such as innovation, agility, and collaborative approaches, establish a support system for digital transformation [15], and restructure their management perceptions [17]. In other words, supply chain digital development requires enterprises to develop a unique set of skills and capabilities [13,18,19].
Many previous studies have indicated that dynamic capabilities contribute to the digital development of enterprises [20,21]. As a dynamic capability in the digital context [22,23,24,25], digital capability is the digital technology capability of an enterprise to respond to external technological changes [22,23]. It is conducive to enterprises digital development [26], and to improving supply chain flexibility and resilience by promoting supply chain digital transformation as well [25]. In fact, many studies have explored the mechanism of digital capability on digital transformation [27,28,29]. Besides, some studies have indicated that digital capability, as a high-order dynamic capability [30,31,32], can generally improve enterprise competitiveness and facilitate digital transformation process by reconstructing low-order dynamic capabilities and operational capabilities [32,33,34].
These years, researchers have fully studied the mechanism of digital capability. However, the role of digital capability in facilitating supply chain digitalization remains poorly understood. At present, most discussions in digital capability are still guided by “atomism”, focusing on “single enterprise capabilities and resources—single enterprise digital transformation process and performance” logic, thus ignoring the “systematization” of digital transformation. In addition, although there has been research exploring the mechanism of digital technology on the digital transformation of supply chains, these studies focus on supply chain digital dynamic capabilities enabled by digital technologies [13], rather than the digital capability within single enterprise. Digital technologies have a “network effect” [35,36], and thus, if the digital transformation of an enterprise cannot radiate to the upstream and downstream [37] for promoting supply chain digitalization, the digital advantage of an enterprise will be greatly reduced. From this perspective, enterprise digital capability should also play a certain role in promoting the digital transformation of a supply chain.
However, regarding an enterprise’s dynamic adaptability to external technologies [22,23], the role of digital capability is mainly to improve enterprises digital competitiveness [26]. Thus, the role of enterprises digital capability lies within the enterprise. So, how does the capability within the enterprise spread to the supply chain system to enhance supply chain digitalization? The current research lacks the discussion on the action boundary of enterprise digital capability, and neglects exploring the external transmission process mechanism of enterprise internal capability. As mentioned earlier, digital technologies have “network effects” [35,36], and in order to maximize the utility of digital technologies, it is necessary to radiate digital technology upstream and downstream [37]. This underscores the importance of supply chain cooperation in digitalization [38]. In this light, enterprise-supply-chain-oriented cooperation capabilities may be a bridge linking an enterprise’s internal capabilities to the external diffusion. However, most of the current research on supply chain digitalization emphasizes the role of digital technology in promoting supply chain cooperation [39,40,41], while ignoring the requirements of supply chain cooperation for the development of supply chain digitalization [42,43].
In order to fill the above gaps, this study focuses on answering two questions. First, can enterprise digital capability help the development of supply chain digitalization? Second, are enterprise supply chain-oriented cooperation capabilities a bridge for the diffusion of enterprise digital capability to the supply chain system? Based on the previous literature on digital capability and cooperation capabilities, this study takes supply chain cooperation as the analysis logic, takes digital capability as a high-order dynamic ability, while taking supply chain cooperation capabilities as the basic operation capabilities for supply chain competition, and explores the mechanism of digital capability to promote the supply chain digitalization by adjusting and reconstructing enterprises’ supply-chain-oriented cooperation capabilities (digital diffusion capability and digital collaborative capability).

2. Literature Framework and Hypothesis Development

2.1. Digital Capability and Supply Chain Digitalization

Emerging technologies such as cloud computing, big data, and AI are subverting and changing supply chain management methods and organizational processes [14]. Digitalization involves a wide range of changes in the organization and supply chain, which requires a shift in organizational culture, operations, and management mindset through the integration of digital technologies, repositioning and organizing enterprise capabilities at all levels [28]. The main goal of supply chain digitalization is to develop new operational processes and innovative business models through the integration of advanced technologies and information systems [44]. As a multidimensional phenomenon, digital transformation requires various organizations in the supply chain to become proficient in the use of various emerging technologies to transform existing human-driven processes into software-driven processes [9]. As the driver of digital transformation, the effective integration of digital technology into supply chain processes is not an easy task, but a difficult “technical challenge” [45]. Therefore, in order to overcome the barriers to the use of digital technologies, enterprises need to develop a set of new skills and capabilities [13,18,19].
According to dynamic capability theory, enterprises should constantly adjust, restructure, and modify their resources and capabilities in a changing environment to ensure sustainable competitiveness [46,47,48]. Therefore, in the context of digital transformation, enterprises need to timely adjust their resources, processes and structures according to environment requirement [28]. Although digital transformation relies on digital technology, it is difficult to drive the transformation of the enterprise and the supply chain without the appropriate skills and capabilities [45]. In fact, the development of the digital economy has made digital elements no longer scarce, and data resources are massive, replicable, and flowable; thus, digital technologies do not directly contribute to the competitive advantage of enterprises and supply chains [49]. It is more important for enterprise to have the capabilities to integrate, orchestrate, and reconstruct digital resources according to the needs of digital production factors and market customers. Enterprise digital capability is manifested in the dynamic adaptability of enterprises to digital technologies [22], through which enterprises are able to effectively acquire, deploy, and leverage digital assets to drive systemic digital transformation. On the other hand, digital capability, as a dynamic capability, are characterized by the reconfiguration of organizational capabilities, which plays an important role in guiding transformational change [50]. Already, previous studies have acknowledged that enterprises digital capabilities are the core drivers of digital transformation [26,34,51]. Therefore, we propose the following hypothesis:
H1. 
Enterprises’ digital capability exerts a positive effect on supply chain digitalization.

2.2. Supply Chain Cooperation Capabilities and Supply Chain Digitalization

Supply chain digitalization is a systematic concept, which not only means that member enterprises in the supply chain use digital technology to optimize and reconstruct the operational process and structure, but also that each member optimizes and reconstructs the process and structure of the entire supply chain through digital links [2], and take digital resources as the core input of supply chain value creation [1]. Therefore, the key to supply chain digitalization lies in the cross-organizational digital link to realize the “integration” of information systems among organizations. To achieve this “integration” of information systems, it is not possible to rely on a single enterprise, but must be a collaborative effort across the supply chain [52]. Previous studies have also emphasized that supply chain collaboration is the pillar of supply chain digitization [42,43]. Therefore, to drive the digitalization of the supply chain, enterprises must develop supply chain cooperation capabilities. Based on the digital development context, this study proposes two kinds of collaborative capabilities for supply chain development, that is, digital diffusion capability and digital collaborative capability.
Digital diffusion capability is reflected in the willingness of an enterprise to share and transmit digital technologies and digital information [49]. It emphasizes that enterprises can selectively export digital resources and digital technologies according to supply chain digital development requirements, which focus on making the digital development of supply chain harmonize with the digital development of enterprise. Most digital technologies and resources are not scarce or imitable [37]. Therefore, in order to maximize the benefits of digital development, enterprises should not adhere to the “monopoly” logic of “atomism”; instead, they must have the capability to diffusion their products, processes, and business models supported by digital technology to drive the common development of supply chain members [53]. From the perspective of supply chain digitalization, first of all, enterprise with digital diffusion capability not only can enhance its influence, but also send a clear signal of its intent to collaborate with supply chain members [54]. Therefore, it is easier for enterprises to gain recognition from on-chain members when they make digital changes. Second, enterprises with digital diffusion capability are easier to embed digital technology into the supply chain process, and use the “network effect” of digital technology [35,36,37] to promote the digital transformation of supply chain members. The digital development of supply chain members will also help the supply chain network to drive the creation and reorganization of more digital elements, so as to finally realize supply chain digital transformation development.
Digital collaborative capability is manifested in the enterprise capability to share and coordinate information with partners through digital channels [55]. Digital collaborative capability emphasizes both the digital “output” and the “digital input”. On the one hand, enterprises need to allow supply chain members to have access to digital assets; on the other hand, enterprises need to absorb other supply chain members’ digital asserts, and timely adjust the organization practices and processes according the requirement of supply chain digitalization development [55]. First, digital collaborative capability can help enterprises achieve “cross-border links”, which can promote the collaboration and integration of digital resources in the supply chain and realize the compatibility of digital interfaces between supply chain members. As a result, it helps enterprises to promote the digital technology embedment of the entire supply chain operation process, which in turn drives the digital development of the entire supply chain. Second, the cross-border compatibility of digital technology interfaces under cooperative development can also enhance the network effect of supply chain resource expansion [56], which is more conducive to the digital value creation of the supply chain, and then promotes the digital transformation of the supply chain value creation process and operational model. Based on the observations, we draw our research hypotheses as follows:
H2. 
Enterprises’ digital diffusion capability has a positive effect on supply chain digitalization.
H3. 
Enterprises’ digital collaborative capability has a positive effect on supply chain digitalization.

2.3. Digital Capability, Supply Chain Cooperation Capabilities, and Supply Chain Digitalization

As a high-order dynamic capability, digital capability can play a role in reconstructing enterprises’ low-order dynamic capabilities or basic operational capabilities [32,33,34]. This study argues that supply chain cooperation is the basic requirement of supply chain competition, and the digital diffusion capability and digital collaborative capability for supply chain cooperation are the basic cooperation capabilities that enterprises need to have in the context of a digital economy. Therefore, with the development and improvement of digital capability, enterprises supply chain-oriented cooperation capabilities will also be reconstructed and adjusted accordingly.
Digital capability is the ability to adjust and reconstruct enterprise operational processes, structure, and business models in a timely manner in response to external technological changes [22], which can help enterprises accumulate knowledge, experience, and digital resources related to the application of digital technology [57,58]. Only with experience in the use of digital technology and digital resources can enterprise carry out digital diffusion according to the requirement of supply chain digital development. As enterprises become more proficient in the use of digital technologies and accumulate more digital resources, the needs for digital technology diffusion will also change; after all, digital technology has a “network effect” [35,36], making enterprises that are more successful in digital transformation more motivated to engage in digital diffusion activities.
Digital collaborative capability is a “two-way” link capability for supply chain cooperation [55]. Digital collaborative capability emphasizes both the “digital resource output” and “digital resource input” of the enterprise. Through the output of digital resources, enterprises can realize the collaborative value co-creation of digital resources with supply chain members. With digital resource input, enterprises need to adjust their digital resource mix based on the newly entered digital elements. This “adjustment” is reflected in the enterprise adaptability to digital technology [22,23], and is also reflected in the enterprise digital capability. Enterprises with digital capability can quickly absorb the needs of digital transformation in the collaborative process [27,59,60], and thus, quickly adjust its organizational processes, structure, and technical elements. As a result, enterprises can better realize cross-border links, so as to better collaborate with on-chain members to reconstruct and innovate the value of digital resources. Based on the arguments presented above, we propose the following hypotheses:
H4. 
Enterprises’ digital capability has a positive effect on digital diffusion capability.
H5. 
Enterprises’ digital capability has a positive effect on digital collaborative capability.
Supply chain digitalization is a “systemic” concept, and the digital transformation of individual enterprises may not be generalized to the entire supply chain [61]. Unlike traditional resources, digital technologies are often not unique or imitable, and other competitors have relatively easy access to the same or similar technologies [37]. A large part of the effect of digital technologies on enterprise is manifested in supply chain synergies [62]. Accordingly, many studies have highlighted the importance of supply chain cooperation in supply chain digital transformation [42,43]. If the enterprises’ digital capability and digital transformation initiatives do not spillover to supply chain members, while supply chain upstream and downstream do not carry out collaborative digital reform and cultivate digital capabilities, the cross-organizational operation interface will not be smooth, and the benefits brought by digitalization to the enterprise will be greatly reduced. Therefore, in order to better play the advantages brought by digital technology, enterprises should actively promote the benefits of digital technology and carry out “cross-border” actions, and collaborate with partners to build the digital infrastructure of the supply chain. Therefore, we propose the following hypotheses and the conceptual model of this study is shown in Figure 1:
H6. 
Enterprises’ digital diffusion capability positively moderates the relationship between digital capability and supply chain digitalization.
H7. 
Enterprises’ digital collaborative capability positively moderates the relationship between digital capability and supply chain digitalization.

3. Methods

3.1. Research Design and Data Collection Method

This study collected data through self-report takes questionnaires by surveying manufacturing enterprises in China. First, the research team drew on the existing mature scales to construct the initial items of the questionnaire, and modified the content according to the suggestions of several experts. Next, we shuffled all the questionnaire items, and sent the questionnaires to 15 senior managers through the university’s MBA program. After one-on-one feedback, we revised the questionnaire, and sent it 150 MBA students for pre-testing. According to the results of Confirmatory Factor Analysis (CFA), we revised, adjusted, and deleted some questionnaire items. The final questionnaires were collected through a professional questionnaire collection platform, and since the online platform required the respondent to complete the questionnaire, there are no missing items in the questionnaires received. In addition, we set up “trap questions” and “verification questions” in the questionnaire to control the quality of the questionnaire data. In total, 382 questionnaires were issued and 292 were recovered. After checking the questionnaire data one by one and deleting the obviously illogical data, 272 valid questionnaires were obtained (Table 1), and the effective recovery rate was 71.20%.

3.2. Measurement of Constructs

The questionnaire was conducted on a Likert seven-level scale, with a numerical score from 1 to 7 indicating “strongly disagree” to “strongly agree”, and “4” indicating neutral or medium level. The measurement of enterprise digital capability has five items, which refers to the research of Khin and Ho [24], including “our enterprise can acquire important digital technologies” and “our enterprise can develop innovative products/services/processes with digital technologies”. The measurement of digital diffusion capability has four items, which refers to the research of Mishra et al. [49], including “our enterprise is willing to share digital technology with partners in the supply chain” and “our enterprise is able to diffusion digital elements into the supply chain in an appropriate form”. The measurement for digital collaborative capability has four items, which refers to the research of Zhang and Zhu [63], Li et al. [64], including “our enterprise has built a digital cooperative management system with different supply chain partners” and “information exchange interfaces between our enterprise and supply chain partners are compatible”. The measurement for supply chain digitalization has five items, which refers to the research of Liu and Chiu [12], including “our enterprise has conducted a large number of transactions with suppliers through digital technology” and “our enterprise has conducted transactions with a large proportion of customers through digital technology”. Since the establishment period, scale, and income of enterprises may have effect on supply chain process and structure arrangement, this study took the asset scale, sales revenue, number of employees, and years of establishment as the control variables.

4. Data Analysis and Results

4.1. Measurement Model

This study used SPSS 28.0 and MPlus 8.0 to test the questionnaire data’s reliability and validity. Reliability is a measure of whether the results presented by the data are consistent over time [65], which can be reflected by internal consistency. Internal consistency refers to the homogeneity between all the measured items that make up a construct, and Cronbach’s α is the most popular research method used in testing internal consistency [65]. Statistically, when α > 0.7, it indicates that there is good internal consistency between the items measured by this variable. As shown in Table 2, the Cronbach’s α of each variable in this study is greater than 0.84, indicating that the measurement of these variables is reliable.
Validity measures the authenticity and accuracy between the measured items and the collected data, including content validity and construct validity [65]. Content validity refers to the appropriateness and consistency of the measured content [66]. Since the establishment of the scale used in this study referred to a large number of literature and sought the expert review, the measurement scale in this study has a certain content validity [67].
Construct validity reflects the degree to which a measurement tool is able to correctly measure underlying traits, including convergent and discriminant validity [68]. Convergent validity refers to the degree to which the scale relates to other measures of the same construct [69], and it can be evaluated by factor loading, Composite Reliability (CR), and Average Variance Extracted (AVE). Statistically, if the factor loading of the variable is > 0.5, it indicates that the item is valid for the explanation of the variable. At the same time, if the CR > 0.6 and the AVE > 0.5, while the AVE value less than CR, it indicates that the measurement of each variable has good convergent validity [65]. As shown in Table 2, the factor loadings in this study are greater than 0.71, CRs are greater than 0.83, and AVEs are greater than 0.56, indicating that the scale in this study has good convergent validity.
Discriminant validity refers to the extent to which a construct is truly distinct from other constructs [70], and can be evaluated by comparing the factor’s square roots of AVE with the correlation coefficient between the factor and other factors. If the square root of the AVE of each variable is greater than the correlation coefficient between the variables, it means that the variables have good discriminant validity (Fornell–Larcker criterion). As shown in Table 3, the correlation coefficients between the variables in this study are all less than the square root of AVE value, indicating that the variables in this study have good discriminant validity.
Due to the high correlation coefficient between several variables in this study, we conducted a collinearity test by testing Variance Inflation Factor (VIF). According to the test results, the highest VIF value is 2.659, which is much lower than the threshold of 10. Therefore, it can be considered that there are no serious multicollinearity problems in this study.

4.2. Common Method Variance

We used self-report questionnaire survey for data collection in this study, and thus, the collected data may be affected by the Common Method Variance (CMV). In order to control and reduce CMV, this study have adopted procedural control measures in advance, such as anonymous response, scrambled construct measurement items, and designed reverse measurement items. In the post hoc control test, CFA was used to verify the hypothesis whether a single factor explains all the variation. According to the test results, the fitting indexes were very unsatisfactory (χ2 = 705.404, df = 135, RMSEA = 0.125, TLI = 0.837, CFI = 0.815), which suggests that there were no serious CMV problems that would affect the conclusions of this study.

4.3. Structural Model

In this study, the Structural Equation Model (SEM) was used to test the research hypotheses, as SEM can be used to estimate complex models and can handle multiple dependent and mediating variables simultaneously. SEM is a comprehensive statistical method to analyze the relationship between multiple variables based on the covariance matrix of variables. It combines the advantages of path analysis and CFA, and can simultaneously test the measurement model between explicit variables and latent variables, as well as the causality model between latent variables and latent variables [71]. In addition, SEM is the most suitable tool for mediating effect analysis because it allows variables to contain measurement errors, which can reduce the underestimation of mediating effects, and thus, make the mediating effect more accurate [71]. Due to the existence of multiple mediating variables in this study, the whole research hypothesis involves many variables and the test relationship is relatively complex, so it is best to use SEM for verification and analysis of such a research model [72].
The traditional method to test the mediation effect is the Sobel test, which requires that the sample data conform to the normal distribution. However, many sample data fail to conform to the normal distribution, which brings difficulties to empirical research. Bootstrapping is a non-parametric resampling method that has no restriction on the distribution of data [72], which can effectively overcome the problem of non-normal distribution of mediating effects. Besides, simulation studies have also found that the bootstrapping method has higher statistical power than other mediating effect test methods [71]. According to Table 1, the sample enterprises in this study did not meet the requirements of normal distribution, so Bootstrapping was adopted in this study to verify the significance of mediating effects.
MPlus 8.0 was used to test all the research hypotheses in this study. The overall model fit was good (χ2 = 320.207, df = 198, RMSEA = 0.048, SRMR = 0.064, TLI = 0.960, CFI = 0.965), so the next test can be promoted.
First, the study tested the effects of each control variable on the dependent variable. The test results show that the number of employees (b = 0.014, p = 0.815), sales (b = −0.098, p = 0.213), total assets (b = 0.001, p = 0.989), and the period of establishment (b = −0.006, p = 0.878) exerts no significant effect on supply chain digitalization. The above results confirm the analysis of this study, that is, the development of the supply chain as a whole is more dependent on the collaborative efforts of supply chain members, and the influence of a single enterprise on the supply chain may be limited.
Next, the study examined the direct effects between the variables. According to the test results, the direct effect of an enterprise digital capability (b = −0.093, p = 0.663) on supply chain digitalization is not significant, so H1 fails to be verified. Both the digital diffusion capability (b = 0.281, p = 0.033) and the digital collaborative capability (b = 0.710, p < 0.01) exert a positive and significant impact on supply chain digitalization. Therefore, H2 and H3 are verified, indicating that enterprises supply chain cooperation capabilities indeed exert significant and positive impact on the digital development of the supply chain. In addition, digital capability exerts positive and significant impact on digital diffusion capability (b = 0.803, p < 0.01) and digital collaborative capability (b = 0.819, p < 0.01), which proves the “high order” of digital capability, indicating that dynamic digital capability can adjust and restructure enterprise basic operation capabilities or low-order dynamic capabilities for coping with changing environment and technology. Thus, H4 and H5 are verified.

4.4. Mediation Role of Enterprise Supply Chain Cooperation Capabilities

According to bootstrapping analysis, enterprise digital capability exerts a positive impact on supply chain digitalization by improving digital diffusion capability (b = 0.226, p = 0.043) and digital collaborative capability (b = 0.581, p < 0.01) (Table 4). Therefore, H6 and H7 are also verified. In conclusion, the total effect of enterprise digital capability on supply chain digital development through supply chain cooperation capability is 0.807 (b = 0.226 + 0.581, p < 0.05). In conclusion, the total effect of enterprise digital capability on supply chain digitalization through supply chain cooperation capabilities is 0.807 (b = 0.226 + 0.581, p < 0.05).

5. Discussion and Conclusions

5.1. Discussion

In line with the supply chain cooperation perspective, this study constructed a theoretical model of “digital capability-enterprise supply-chain-oriented collaboration capabilities (digital diffusion capability and digital collaborative capability) and supply chain digitalization”, and conducted empirical analysis through 272 questionnaire data of Chinese manufacturing enterprises. The results revealed that enterprises’ digital capability has no direct impact on supply chain digitalization, while enterprises’ supply-chain-oriented collaborative capabilities play a full mediation role between digital capability and supply chain digitalization. At present, some studies have explored the impact mechanism of digital capability on supply chain development, such as supply chain resilience [25,73,74], supply chain innovation [75], and sustainable supply chain performance [76]. This study proposes that supply chain development is a “systemic” concept, and a single enterprise’s internal capabilities and resources may not have a direct impact on supply chain development. This begs the question of the action direction of enterprise capabilities, and we believe that this is the reason why H1 in this study has not been validated. According to the direction of capabilities, Day [77] divided enterprise capabilities into three types: inside-out capabilities, outside-in capabilities, and spanning capabilities. Inside-out capabilities are capabilities of an enterprise to meet market demand, carry out competitive challenges, and take advantage of external opportunities, which is reflected in what an enterprise can “do”, including financial management capabilities, cost control capabilities, and human resource management capabilities. Outside-in capabilities are established by the enterprise’s adaptation to the external environment, which shows the enterprise’s pursuit of grasping the external demand in time. Spanning capabilities emphasize both the external information input and the internal information output. The role of this type of capability (such as strategic development capabilities, new product development capabilities, and procurement capabilities) is directed to the supply chain, emphasizing supply chain coordination. Digital capability emphasizes enterprises adaptability to external technological changes [22,23], which is an “outside-in” capability, whose role is focused on the single enterprise. Therefore, there must be a link bridge between enterprise digital capability and supply chain development, and the bridge between the enterprise’s inward capabilities and resources and supply chain development is the “spanning capabilities”. Digital diffusion capability emphasizes the link between internal digital resources and supply chain members, and digital collaboration capability emphasizes the compatibility between internal digital resources and supply chain members, both of which are “spanning capabilities”. These two “spanning capabilities” help enterprises transfer internal digital resources and knowledge to supply chain members, and also help enterprises absorb the digital knowledge and digital capabilities of supply chain members to ensure the compatibility of digital systems between enterprises and members. In this way, it is more conducive to the digital integration of supply chain logistic flow, capital flow, and commercial flow, as well as the co-creation of digital value of supply chain cooperation, thereby contributing to the digital development of the supply chain.
In addition, the research results shows that digital diffusion capability and digital collaborative capability exert direct and positive impact of supply chain digitalization. This conclusion also responds to the research on supply chain digital capabilities [13,78,79] and supply chain dynamic capabilities [25,80,81] in the context of digitalization. The above discussion of supply chain capabilities does not emphasize the role orientation of capabilities, while the results of this study show that the capabilities that can play a role in promoting supply chain development should be “spanning capabilities”. Therefore, our study may provide a guidance for the classification of supply chain capabilities.
Finally, the results provide evidence of the digital capability as a high-order dynamic capability, and this result is in accordance with studies confirming that enterprises’ digital capability can adjust and restructure enterprises’ operational capabilities for supply chain cooperation [32,33,34,82]. On the one hand, digital capability can help enterprises accumulate digital knowledge and resources, and contributes to making enterprise better perceive the demand for digital technologies and resources of supply chain cooperation, which in turn helps enterprises improve and adjust their digital diffusion capability for supply chain digital transformation. On the other hand, digital capability helps the enterprises absorb the digital knowledge and technology of the supply chain partners, thereby enhancing the compatibility of the digital interface between the enterprise and the supply chain members. This conclusion reaffirms the importance of digital capability and provides a reference for enterprises in digital transformation.

5.2. Theoretical Implications

First, this study contributes to the scientific literature in enterprise capabilities, and confirms that enterprise digital capability cannot have a direct impact on supply chain development. In the context of a digital economy, many previous studies have explored the impact mechanism of digital capability on digital transformation, but most of the studies ignore the direction of capabilities. As a high-order dynamic capability, digital capability plays a role in the enterprise adaptability to changes in the external technical environment [22,23], which is an “outside-in” capability [77]. The findings indicate that although “inside-out” and “outside-in” capabilities will exert significant impact on enterprises’ performance and competitiveness, they cannot exert directly impact on supply chain performance. Therefore, future studies need to pay attention to the direction of capabilities when exploring the mechanism of enterprise capabilities, and this insight provides new ideas for the follow-up research of enterprise capabilities.
Second, this study enriches the literature on supply chain capabilities. In the context of digital transformation, many studies have begun to pay attention to supply chain digital capabilities [13,78,79] and supply chain dynamic capabilities [25,80,81], while these studies’ focus is still on single enterprise capabilities. This study proposes that the capabilities which can exert direct influence supply chain digitalization are “spanning capabilities”, which provides guidance for the subsequent characterization of supply chain capabilities.
Finally, this study provides valuable insights for current research on supply chain digitalization. This study explores the mechanism of digital capabilities at the micro-enterprise level to promote the digital development of supply chains, and confirms that the “outside-in” digital capability cannot exerts direct impact on supply chain digitalization. On the contrary, supply chain cooperation capabilities (digital diffusion capability and digital collaborative capability) play full mediation role between digital capability and supply chain digitalization. This study emphasizes the systematization of supply chain digitalization, and thus, puts forward the matching requirements of supply chain research. In other words, this study proposes that the enable factors corresponding to supply chain digitalization should be supply chain resources and capabilities, which provides an important reference for the subsequent research on promoting supply chain digital transformation.

5.3. Practical Implications

First, enterprises should strive to cultivate digital capability. Digital capability is the dynamic capability for enterprises to cope with technological changes, and it can affect the development and reconstruction of other enterprises capabilities. Digital capability is the basic requirement for enterprises coping with technological changes. However, the cultivation of digital capability is not only the digital technology operation of enterprises for micro-operations. Instead, for developing digital capability, enterprises should have a digital baptism from the top down, such as establishing a digital enterprise culture, constructing management models and systems adapted to digital development, cultivating cross-border collaborative thinking, introducing digital technology and talents, and focusing on the accumulation of digital knowledge.
Next, enterprises should have a supply chain development mindset and cultivate spanning capabilities. Digital technology is not scarce and inimitable, but digital technology has network effects. Therefore, in order to maximize the benefits of digital development, enterprises should be guided by the cross-border collaborative thinking of digital development and cultivate supply chain-oriented collaborative capabilities, such as such facilitating the development and utilization of supply chain collaborative information technology, building a supply chain operation platform, and promoting the exchange of digital talents among supply chain members. The construction of collaborative platform helps to smooth the circulation channels of supply chain digital flow, promote the digital integration of supply chain logistic flow, commercial flow, and cash flow, so as to realize supply chain digital transformation.
Lastly, enterprises should establish digital governance mechanisms. Digital development requires enterprises to establish a “cross-border” collaborative mindset and share digital information and technology. Although digital technology may not be the source of enterprises sustainable competitiveness, digital information based on digital technology is the core input of enterprises digital value creation. Therefore, enterprises must establish a set of digital governance mechanisms, stratify the value of digital information, and focus on desensitizing core key data. Accordingly, enterprises should also actively use blockchain and other technologies to promote the establishment of internal “private chains” and supply chain “alliance chains” to ensure the authenticity of digital data and the security of digital data circulation.

5.4. Limitations and Avenues for Future Research

This study has several limitations. First, the research sample in this study comes from manufacturing enterprises in China, which limits the generalizability of the conclusions. On the one hand, China is a developing country with limited resources; on the other hand, most manufacturing enterprises need to invest heavily. Therefore, manufacturing enterprises in developing countries may place more emphasis on supply chain coordination due to the scarcity of resources. On the contrary, as they are equipped with advanced and relatively abundant resources in developed countries, enterprises resource constraints are not so serious. Hence, a single enterprise even has the capabilities to promote supply chain development. Follow-up studies could expand the scope of the study to include other sectors as well as different economies to enhance its generalizability. Second, since the size of the sample enterprises in this study does not meet the requirements of normal distribution, and most of the sample enterprises belong to large enterprises, the usability of the research conclusions and practical implications may have limitations. Although these sample enterprises are in developing countries, large enterprises still have more abundant resources than Small- and Medium-sized Enterprises (SMEs). Therefore, large enterprises are usually different from SMEs in the choice, cultivation, and development path of capabilities. The follow-up research can make a comparative study on capabilities development path and focus of digital capability and cooperation capabilities of large enterprises and SMEs, so as to provide more specific and usable guidance for different enterprises. Third, this study highlights the role of enterprises in using high-order dynamic capability (digital capability) to develop supply chain coordination capabilities, and thus, facilizing to supply chain digitalization. This study takes dynamic capability as the research starting point, and its action process is bound to be dynamic. However, the data in this study are “cross-sectional data” collected through anonymous questionnaires, and they cannot reflect the dynamic process described above. Follow-up studies can try to use “panel data”, so that the above relationship pathways can be more accurately verified. Last, this study raises the question of the enterprise capabilities’ action boundary. Subsequent studies can further distinguish and classify enterprises “inside-out”, “outside-in”, and “spanning” capabilities under the background of digital transformation, which is conducive to clarifying the role of enterprises digital-related capabilities.

Author Contributions

Conceptualization, S.C. and Z.T.; methodology, S.C.; software, S.C.; validation, S.C. and Z.T.; formal analysis, S.C.; investigation, S.C.; resources, Z.T.; data curation, S.C.; writing—original draft preparation, S.C.; writing—review and editing, Z.T.; visualization, Z.T.; supervision, S.C.; project administration, S.C.; funding acquisition, S.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the CHONGQING SOCIAL SCIENCE PLANNING PROJECT (No. 2021NDQN48).

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Seyedghorban, Z.; Tahernejad, H.; Meriton, R.; Graham, G. Supply chain digitalization: Past, present and future. Prod. Plan. Control 2020, 31, 96–114. [Google Scholar] [CrossRef]
  2. Perano, M.; Cammarano, A.; Varriale, V.; Del Regno, C.; Michelino, F.; Caputo, M. Embracing supply chain digitalization and unphysicalization to enhance supply chain performance: A conceptual framework. Int. J. Phys. Distrib. Logist. Manag. 2023, 53, 628–659. [Google Scholar] [CrossRef]
  3. Bigliardi, B.; Filippelli, S.; Petroni, A.; Tagliente, L. The digitalization of supply chain: A review. Procedia Comput. Sci. 2022, 200, 1806–1815. [Google Scholar] [CrossRef]
  4. Ghadge, A.; Er Kara, M.; Moradlou, H.; Goswami, M. The impact of Industry 4.0 implementation on supply chains. J. Manuf. Technol. Manag. 2020, 31, 669–686. [Google Scholar] [CrossRef]
  5. Büyüközkan, G.; Göçer, F. Digital Supply Chain: Literature review and a proposed framework for future research. Comput. Ind. 2018, 97, 157–177. [Google Scholar] [CrossRef]
  6. Choudhury, A.; Behl, A.; Sheorey, P.A.; Pal, A. Digital supply chain to unlock new agility: A TISM approach. Benchmarking Int. J. 2021, 28, 2075–2109. [Google Scholar] [CrossRef]
  7. Zhao, N.; Hong, J.; Lau, K.H. Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model. Int. J. Prod. Econ. 2023, 259, 108817. [Google Scholar] [CrossRef]
  8. Porter, M.E.; Heppelmann, J.E. How smart, connected products are transforming companies. Harv. Busi. Rev. 2015, 93, 96–114. [Google Scholar]
  9. Zangiacomi, A.; Pessot, E.; Fornasiero, R.; Bertetti, M.; Sacco, M. Moving towards digitalization: A multiple case study in manufacturing. Prod. Plan. Control 2020, 31, 143–157. [Google Scholar] [CrossRef]
  10. Wu, L.; Sun, L.; Chang, Q.; Zhang, D.; Qi, P. How do digitalization capabilities enable open innovation in manufacturing enterprises? A multiple case study based on resource integration perspective. Technol. Forecast. Soc. Chang. 2022, 184, 122019. [Google Scholar] [CrossRef]
  11. Papadopoulos, T.; Singh, S.P.; Spanaki, K.; Gunasekaran, A.; Dubey, R. Towards the next generation of manufacturing: Implications of big data and digitalization in the context of industry 4.0. Prod. Plan. Control 2022, 33, 101–104. [Google Scholar] [CrossRef]
  12. Liu, K.P.; Chiu, W. Supply Chain 4.0: The impact of supply chain digitalization and integration on firm performance. Asian J. Bus. Ethics 2021, 10, 371–389. [Google Scholar] [CrossRef]
  13. Queiroz, M.M.; Pereira, S.C.F.; Telles, R.; Machado, M.C. Industry 4.0 and digital supply chain capabilities: A framework for understanding digitalisation challenges and opportunities. Benchmarking Int. J. 2021, 28, 1761–1782. [Google Scholar] [CrossRef]
  14. Eller, R.; Alford, P.; Kallmünzer, A.; Peters, M. Antecedents, consequences, and challenges of small and medium-sized enterprise digitalization. J. Bus. Res. 2020, 112, 119–127. [Google Scholar] [CrossRef]
  15. Freitas Junior, J.C.; Maçada, A.C.; Brinkhues, R.; Montesdioca, G. Digital Capabilities as Driver to Digital Business Performance. In Proceedings of the Twenty-Second Americas Conference on Information Systems, San Diego, CA, USA, 11–14 August 2016. [Google Scholar]
  16. Lammers, T.; Tomidei, L.; Trianni, A. Towards a novel framework of barriers and drivers for digital transformation in industrial supply chains. In Proceedings of the 2019 Portland Int. Conference on Management of Engineering and Technology (PICMET), Portland, OR, USA, 25–29 August 2019; IEEE: Piscataway, NJ, USA, 2019; pp. 1–6. [Google Scholar]
  17. Davies, P.; Bustinza, O.F.; Parry, G.; Jovanovic, M. Unpacking the relationship between digital capabilities, services capabilities, and firm financial performance: A moderated mediation model. Ind. Mark. Manag. 2023, 115, 1–10. [Google Scholar] [CrossRef]
  18. Schlegel, D.; Kraus, P. Skills and competencies for digital transformation—A critical analysis in the context of robotic process automation. Int. J. Organ. Anal. 2023, 31, 804–822. [Google Scholar] [CrossRef]
  19. Sanders, N.R.; Swink, M. How to Build a Digital Supply Chain: Focus on Capabilities; Association for Supply Chain Management: Chicago, IL, USA, 2020; pp. 1–18. [Google Scholar]
  20. Warner, K.S.R.; Wäger, M. Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Plan. 2019, 52, 326–349. [Google Scholar] [CrossRef]
  21. Magistretti, S.; Pham, C.T.A.; Dell’Era, C. Enlightening the dynamic capabilities of design thinking in fostering digital transformation. Ind. Mark. Manag. 2021, 97, 59–70. [Google Scholar] [CrossRef]
  22. Ye, F.; Liu, K.; Li, L.; Lai, K.H.; Zhan, Y.; Kumar, A. Digital supply chain management in the COVID-19 crisis: An asset orchestration perspective. Int. J. Prod. Econ. 2022, 245, 108396. [Google Scholar] [CrossRef]
  23. Shen, L.; Zhang, X.; Liu, H. Digital technology adoption, digital dynamic capability, and digital transformation performance of textile industry: Moderating role of digital innovation orientation. Manag. Decis. Econ. 2022, 43, 2038–2054. [Google Scholar] [CrossRef]
  24. Khin, S.; Ho, T.C.F. Digital technology, digital capability and organizational performance: A mediating role of digital innovation. Int. J. Innov. Sci. 2019, 11, 177–195. [Google Scholar] [CrossRef]
  25. Dubey, R.; Gunasekaran, A.; Childe, S.J.; Bryde, D.J.; Giannakis, M.; Foropon, C.; Roubaud, D.; Hazen, B.T. Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations. Int. J. Prod. Econ. 2020, 226, 107599. [Google Scholar] [CrossRef]
  26. Proksch, D.; Rosin, A.F.; Stubner, S.; Pinkwart, A. The influence of a digital strategy on the digitalization of new ventures: The mediating effect of digital capabilities and a digital culture. J. Small Bus. Manag. 2024, 62, 1–29. [Google Scholar] [CrossRef]
  27. Konopik, J.; Jahn, C.; Schuster, T.; Hoßbach, N.; Pflaum, A. Mastering the digital transformation through organizational capabilities: A conceptual framework. Digit. Bus. 2022, 2, 100019. [Google Scholar] [CrossRef]
  28. Rupeika-Apoga, R.; Petrovska, K.; Bule, L. The effect of digital orientation and digital capability on digital transformation of SMEs during the COVID-19 pandemic. J. Theor. Appl. Electron. Commer. Res. 2022, 17, 669–685. [Google Scholar] [CrossRef]
  29. Leso, B.H.; Cortimiglia, M.N.; Ghezzi, A.; Minatogawa, V. Exploring digital transformation capability via a blended perspective of dynamic capabilities and digital maturity: A pattern matching approach. Rev. Manag. Sci. 2024, 18, 1149–1187. [Google Scholar] [CrossRef]
  30. Wang, C.L.; Ahmed, P.K. Dynamic capabilities: A review and research agenda. Int. J. Manag. Rev. 2007, 9, 31–51. [Google Scholar] [CrossRef]
  31. Parida, V.; Oghazi, P.; Cedergren, S. A study of how ICT capabilities can influence dynamic capabilities. J. Enterp. Inf. Manag. 2016, 29, 179–201. [Google Scholar] [CrossRef]
  32. Chen, Y.; Li, J.; Zhang, J. Digitalisation, data-driven dynamic capabilities and responsible innovation: An empirical study of SMEs in China. Asia Pac. J. Manag. 2022, 1–41. [Google Scholar] [CrossRef]
  33. Kristoffersen, E.; Mikalef, P.; Blomsma, F.; Li, J. The effects of business analytics capability on circular economy implementation, resource orchestration capability, and firm performance. Int. J. Prod. Econ. 2021, 239, 108205. [Google Scholar] [CrossRef]
  34. Annarelli, A.; Battistella, C.; Nonino, F.; Parida, V.; Pessot, E. Literature review on digitalization capabilities: Co-citation analysis of antecedents, conceptualization and consequences. Technol. Forecast. Soc. Chang. 2021, 166, 120635. [Google Scholar] [CrossRef]
  35. Lee, D.; Mendelson, H. Adoption of information technology under network effects. Inf. Syst. Res. 2007, 18, 395–413. [Google Scholar] [CrossRef]
  36. Pontiggia, A.; Virili, F. Network effects in technology acceptance: Laboratory experimental evidence. Int. J. Inf. Manag. 2010, 30, 68–77. [Google Scholar] [CrossRef]
  37. Hassan, S.S.; Meisner, K.; Krause, K.; Bzhalava, L.; Moog, P. Is digitalization a source of innovation? Exploring the role of digital diffusion in SME innovation performance. Small Bus. Econ. 2024, 62, 1469–1491. [Google Scholar] [CrossRef]
  38. Aamer, A.; Sahara, C.R.; Al-Awlaqi, M.A. Digitalization of the supply chain: Transformation factors. J. Sci. Technol. Policy Manag. 2023, 14, 713–733. [Google Scholar] [CrossRef]
  39. Le, T.T.; Nhu, Q.P.V.; Behl, A. Role of digital supply chain in promoting sustainable supply chain performance: The mediating of supply chain integration and information sharing. Int. J. Logis. Manag. 2024, in press. [Google Scholar] [CrossRef]
  40. Salamah, E.; Alzubi, A.; Yinal, A. Unveiling the Impact of Digitalization on Supply Chain Performance in the Post-COVID-19 Era: The Mediating Role of Supply Chain Integration and Efficiency. Sustainability 2023, 16, 304. [Google Scholar] [CrossRef]
  41. Li, N.; Yao, Q.; Tang, H.; Lu, Y. Is digitalization necessary? Configuration of supply chain capabilities for improving enterprise competitive performance. J. Bus. Res. 2025, 186, 114972. [Google Scholar] [CrossRef]
  42. Camarinha-Matos, L.M.; Fornasiero, R.; Ramezani, J.; Ferrada, F. Collaborative networks: A pillar of digital transformation. Appl. Sci. 2019, 9, 5431. [Google Scholar] [CrossRef]
  43. Ma, L.; Chang, R. How big data analytics and artificial intelligence facilitate digital supply chain transformation: The role of integration and agility. Manag. Decis. 2024, in press. [CrossRef]
  44. Deepu, T.S.; Ravi, V. Supply chain digitalization: An integrated MCDM approach for inter-organizational information systems selection in an electronic supply chain. Int. J. Inf. Manag. Data Insights 2021, 1, 100038. [Google Scholar] [CrossRef]
  45. Slavković, M.; Pavlović, K.; Mamula Nikolić, T.; Vučenović, T.; Bugarčić, M. Impact of digital capabilities on digital transformation: The mediating role of digital citizenship. Systems 2023, 11, 172. [Google Scholar] [CrossRef]
  46. Winter, S.G. Understanding dynamic capabilities. Strateg. Manag. J. 2003, 24, 991–995. [Google Scholar] [CrossRef]
  47. Teece, D.J. Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strateg. Manag. J. 2007, 28, 1319–1350. [Google Scholar] [CrossRef]
  48. Eisenhardt, K.M.; Martin, J.A. Dynamic capabilities: What are they? Strateg. Manag. J. 2000, 21, 1105–1121. [Google Scholar] [CrossRef]
  49. Mishra, D.; Luo, Z.; Hazen, B.; Foropon, C. Organizational capabilities that enable big data and predictive analytics diffusion and organizational performance: A resource-based perspective. Manag. Decis. 2019, 57, 1734–1755. [Google Scholar] [CrossRef]
  50. Baiyere, A.; Salmela, H.; Nieminen, H.; Kankainen, T. Assessing digital capabilities for digital transformation—The MIND framework. Inf. Syst. J. 2024, in press. [CrossRef]
  51. Ritter, T.; Pedersen, C.L. Digitization capability and the digitalization of business models in business-to-business firms: Past, present, and future. Ind. Mark. Manag. 2020, 86, 180–190. [Google Scholar] [CrossRef]
  52. Carpitella, S. Overcoming barriers to digital transformation towards greener supply chains in automotive paint shop operations. Sustainability. 2024, 16, 1948. [Google Scholar] [CrossRef]
  53. Kouropalatis, Y.; Giudici, A.; Acar, O.A. Business capabilities for industrial firms: A bibliometric analysis of research diffusion and impact within and beyond Industrial Marketing Management. Ind. Mark. Manag. 2019, 83, 8–20. [Google Scholar] [CrossRef]
  54. Cao, L.; Li, L. Determinants of retailers’ cross-channel integration: An innovation diffusion perspective on omni-channel retailing. J. Interact. Mark. 2018, 44, 1–16. [Google Scholar] [CrossRef]
  55. Chi, M.; Huang, R.; George, J.F. Collaboration in demand-driven supply chain: Based on a perspective of governance and IT-business strategic alignment. Int. J. Inf. Manag. 2020, 52, 102062. [Google Scholar] [CrossRef]
  56. Harland, C.M. Supply chain management: Relationships, chains and networks. Br. J. Manag. 1996, 7, S63–S80. [Google Scholar] [CrossRef]
  57. Zhuge, K.; Lin, W.; Yuan, Y.; He, H.; Zhang, Y. Does digital capability promote sustainable development of new ventures? The dual impact of green knowledge creation and green pressure. Int. J. Env. Res. Public Health 2023, 20, 2274. [Google Scholar] [CrossRef]
  58. Wei, S.; Xu, D.; Liu, H. The effects of information technology capability and knowledge base on digital innovation: The moderating role of institutional environments. Eur. J. Innov. Manag. 2022, 25, 720–740. [Google Scholar] [CrossRef]
  59. Ghosh, S.; Hughes, M.; Hodgkinson, I.; Hughes, P. Digital transformation of industrial businesses: A dynamic capability approach. Technovation 2022, 113, 102414. [Google Scholar] [CrossRef]
  60. Sousa-Zomer, T.T.; Neely, A.; Martinez, V. Digital transforming capability and performance: A microfoundational perspective. Int. J. Oper. Prod. Manag. 2020, 40, 1095–1128. [Google Scholar] [CrossRef]
  61. Ruiz-Benítez, R.; López, C.; Real, J.C. The lean and resilient management of the supply chain and its impact on performance. Int. J. Prod. Econ. 2018, 203, 190–202. [Google Scholar] [CrossRef]
  62. Ye, F.; Wang, Z. Effects of information technology alignment and information sharing on supply chain operational performance. Comput. Ind. Eng. 2013, 65, 370–377. [Google Scholar] [CrossRef]
  63. Zhang, F.; Zhu, L. Firm collaborative capability and new product development performance: The mediating role of heterogeneous knowledge acquisition. Int. J. Emerg. Mark. 2021, 16, 1502–1524. [Google Scholar] [CrossRef]
  64. Li, L.; Zhu, W.; Wei, L.; Yang, S. How can digital collaboration capability boost service innovation? Evidence from the information technology industry. Technol. Forecast. Soc. Chang. 2022, 182, 121830. [Google Scholar] [CrossRef]
  65. Sürücü, L.; Maslakci, A. Validity and reliability in quantitative research. Bus. Manag. Stud. Int. J. 2020, 8, 2694–2726. [Google Scholar] [CrossRef]
  66. Bollen, K.A. The consequences of measurement error. In Structural Equations with Latent Variables; John Wiley and Sons, Inc.: Hoboken, NJ, USA, 1989; pp. 151–178. [Google Scholar]
  67. Almanasreh, E.; Moles, R.; Chen, T.F. Evaluation of methods used for estimating content validity. Res. Soc. Adm. Pharm. 2019, 15, 214–221. [Google Scholar] [CrossRef]
  68. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  69. Hill, C.R.; Hughes, J.N. An examination of the convergent and discriminant validity of the Strengths and Difficulties Questionnaire. Sch. Psychol. Q. 2007, 22, 380. [Google Scholar] [CrossRef]
  70. Rönkkö, M.; Cho, E. An updated guideline for assessing discriminant validity. Org. Res. Methods 2022, 25, 6–14. [Google Scholar] [CrossRef]
  71. Cheung, G.W.; Lau, R.S. Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models. Org. Res. Methods 2008, 11, 296–325. [Google Scholar] [CrossRef]
  72. Preacher, K.J.; Hayes, A.F. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav. Res. Methods 2008, 40, 879–891. [Google Scholar] [CrossRef] [PubMed]
  73. Lin, J.; Lin, S.; Benitez, J.; Luo, X.R.; Ajamieh, A. How to build supply chain resilience: The role of fit mechanisms between digitally-driven business capability and supply chain governance. Inf. Manag. 2023, 60, 103747. [Google Scholar] [CrossRef]
  74. Belhadi, A.; Kamble, S.; Subramanian, N.; Singh, R.K.; Venkatesh, M. Digital capabilities to manage agri-food supply chain uncertainties and build supply chain resilience during compounding geopolitical disruptions. Int. J. Oper. Prod. Manag. 2024, in press. [CrossRef]
  75. Abourokbah, S.H.; Mashat, R.M.; Salam, M.A. Role of absorptive capacity, digital capability, agility, and resilience in supply chain innovation performance. Sustainability 2023, 15, 3636. [Google Scholar] [CrossRef]
  76. Belhadi, A.; Kamble, S.; Gunasekaran, A.; Mani, V. Analyzing the mediating role of organizational ambidexterity and digital business transformation on industry 4.0 capabilities and sustainable supply chain performance. Supply Chain Manag. Int. J. 2022, 27, 696–711. [Google Scholar] [CrossRef]
  77. Day, G.S. The capabilities of market-driven organizations. J. Mark. 1994, 58, 37–52. [Google Scholar] [CrossRef]
  78. Li, N.; Liu, D.; Boadu, F. The impact of digital supply chain capabilities on enterprise sustainable competitive performance: An ambidextrous view. Ind. Manag. Data Syst. 2023, 123, 1670–1689. [Google Scholar] [CrossRef]
  79. Ricárdez-Estrada, J.; Garay-Rondero, C.L.; Romero, D.; Wuest, T.; Pinto, R. Identifying Digital Supply Chain Capabilities. Procedia Comput. Sci. 2024, 232, 1182–1191. [Google Scholar] [CrossRef]
  80. Li, Q.; Zhang, H.; Liu, K.; Zhang, Z.J.; Jasimuddin, S.M. Linkage between digital supply chain, supply chain innovation and supply chain dynamic capabilities: An empirical study. Int. J. Logist. Manag. 2024, 35, 1200–1223. [Google Scholar] [CrossRef]
  81. Eslami, M.H.; Jafari, H.; Achtenhagen, L.; Carlbäck, J.; Wong, A. Financial performance and supply chain dynamic capabilities: The Moderating Role of Industry 4.0 technologies. Int. J. Prod. Res. 2024, 62, 8092–8109. [Google Scholar] [CrossRef]
  82. Gao, S.; Ma, X.; Zhao, X. [Retracted] Entrepreneurship, Digital Capabilities, and Sustainable Business Model Innovation: A Case Study. Mob. Inf. Syst. 2022, 2022, 5822423. [Google Scholar]
Jtaer 19 00147 g001
Figure 1. Conceptual model.
Figure 1. Conceptual model.
Jtaer 19 00147 g001
Table 1. Basic characteristics of samples (number of enterprises = 272).
Table 1. Basic characteristics of samples (number of enterprises = 272).
CategoryPercentage of Respondents
Number of employees
1–49 employees0.74%
50–79 employees1.10%
80–99 employees1.10%
100–199 employees6.62%
200–499 employees29.78%
500–999 employees27.21%
More than 1000 employees33.46%
Asserts (CNY million)
Less than 51.10%
5–104.41%
10–206.62%
20–5019.85%
50–10022.06%
More than 10045.96%
Last year’s sales (CNY million)
Less than 11.47%
1–54.04%
5–109.93%
10–209.93%
20–5016.91%
50–10013.24%
More than 10044.49%
Establishment period
Less than 2 years0.74%
3–5 years1.47%
6–10 years9.93%
11–15 years32.35%
More than 15 years55.51%
Table 2. Convergent validity.
Table 2. Convergent validity.
ConstructItemsMeanSDFactor LoadingCronbach’s αCRAVE
Digital CapabilityDC15.910.9110.8510.9150.9160.686
DC25.820.8320.850
DC35.90.8110.836
DC45.740.9060.855
DC55.920.8270.743
Digital Diffusion CapabilityDDC15.860.8710.7440.8420.8380.564
DDC25.810.8120.755
DDC35.880.8060.792
DDC45.960.8230.710
Digital collaborative capabilityDCC15.70.8210.8220.9000.9010.694
DCC25.710.8150.865
DCC35.690.8200.844
DCC45.770.7840.800
Supply Chain Digitalization SCD15.820.8420.7950.8990.9000.643
SCD25.760.8750.819
SCD35.810.8610.816
SCD45.750.8960.776
SCD55.720.9510.804
Table 3. Discriminant validity.
Table 3. Discriminant validity.
ConstructMeanSD12345678
1 NE 6.791.151
2 Asserts5.951.230.597 ***1
3 Sales5.541.650.559 ***0.771 ***1
4 EP4.400.790.274 ***0.277 ***0.214 ***1
5 DC5.860.740.129 **0.0650.11 *0.134 **0.828
6 DDC5.880.680.145 **0.0810.0930.150 **0.678 ***0.751
7 DCC5.720.710.143 **0.0460.0160.111 *0.719 ***0.728 ***0.833
8 SCD5.770.750.08−0.016−0.0440.08 *0.618 ***0.647 ***0.756 ***0.802
Note: NE: number of employees; EP: establishment period; DC: digital capability; DDC: digital diffusion capability; DCC: digital collaborative capability; SCD: supply chain digitalization; * denotes significant at p < 0.1, ** denotes significant at p < 0.05, *** denotes significant at p < 0.01; diagonals represent the square root of AVE, while the other entries represent the correlations.
Table 4. Mediation results.
Table 4. Mediation results.
PathBeta Coefficients (b)S.E.p-ValuesSignificance
DC- > SCD−0.0930.2140.663
DDC- > SCD0.2810.1320.033**
DCC- > SCD0.7100.1200.000***
DC- > DDC0.8030.0440.000***
DC- > DCC0.8190.0380.000***
DC- > DDC- > SCD0.2260.1120.043**
DC- > DCC- > SCD0.5810.1090.000***
Note: DC: digital capability; DDC: digital diffusion capability; DCC: digital collaborative capability; SCD: supply chain digitalization; ** denotes significant at p < 0.05, *** denotes significant at p < 0.01.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chen, S.; Tang, Z. The Impact of Enterprise Digital Capability on Supply Chain Digitalization—From the Perspective of Supply Chain Cooperation. J. Theor. Appl. Electron. Commer. Res. 2024, 19, 3051-3066. https://doi.org/10.3390/jtaer19040147

AMA Style

Chen S, Tang Z. The Impact of Enterprise Digital Capability on Supply Chain Digitalization—From the Perspective of Supply Chain Cooperation. Journal of Theoretical and Applied Electronic Commerce Research. 2024; 19(4):3051-3066. https://doi.org/10.3390/jtaer19040147

Chicago/Turabian Style

Chen, Sijie, and Zhaobo Tang. 2024. "The Impact of Enterprise Digital Capability on Supply Chain Digitalization—From the Perspective of Supply Chain Cooperation" Journal of Theoretical and Applied Electronic Commerce Research 19, no. 4: 3051-3066. https://doi.org/10.3390/jtaer19040147

APA Style

Chen, S., & Tang, Z. (2024). The Impact of Enterprise Digital Capability on Supply Chain Digitalization—From the Perspective of Supply Chain Cooperation. Journal of Theoretical and Applied Electronic Commerce Research, 19(4), 3051-3066. https://doi.org/10.3390/jtaer19040147

Article Metrics

Back to TopTop