Supply Chain Diversification, Digital Transformation, and Supply Chain Resilience: Configuration Analysis Based on fsQCA

Abstract

To determine the influence of COVID-19 on supply chains, previous research has examined the impact of supply chain diversification and digital transformation on supply chain resilience, but few studies have integrated these two aspects to understand their impact on supply chain resilience. Given this, our study implements the fuzzy set qualitative comparative analysis (fsQCA) method to investigate the influence of supply chain diversification (supply base diversification and customer base diversification) and digital transformation (digital transformation depth and breadth) on supply chain resilience. Using data from 191 listed manufacturing firms, it is shown that the dimensions of supply chain diversification and digital transformation do not have the necessary conditions to achieve high supply chain resilience, while the analysis of sufficient conditions shows that three paths can achieve high supply chain resilience—namely, those driven by digital transformation, supply chain diversification, and supplier centralization and customer base diversification. This study demonstrates the numerous and complex linkages between antecedent and outcome, and firms can choose the path that is best for them to improve supply chain resilience based on their size, degree of digital transformation, and supply chain diversification.

1. Introduction

In recent years, the world economy has increasingly taken on the characteristics of VUCA due to global tensions, the outbreak of COVID-19, and the impact of climate change and natural disasters [1,2]. Responding to supply chain disruption crises caused by uncertain events is now an urgent priority for firms, and therefore, they need to be able to withstand and recover from supply chain disruptions, which can severely damage a firm’s performance and are detrimental to long-term survival and growth. Therefore, to improve the ability of supply chains to withstand and recover from disruptions, increasing numbers of scholars and practitioners are addressing the risk of supply chain disruptions by building supply chain resilience [3,4]. Supply chain resilience refers to the ability of a supply chain to cope with the risk of supply chain disruption and quickly return to its original performance after a disruption [5]. For firms, supply chain resilience can be improved by adopting redundancy, flexibility, visibility, collaboration, backup suppliers, safety stocks, etc. [6,7,8].

Supply chain diversification can improve the ability of firms to cope with supply chain disruptions and risks [9]. For example, supply base diversification [10] can help firms to avoid production shutdowns due to supply interruptions. Previous research has demonstrated the ability of supply chain diversification to address the risk of supply chain disruption [11]. A diversified supply chain base can improve the operational flexibility of firms and help firms promptly meet the needs of the market and customers. Similarly, a diverse customer base can help firms achieve higher financial performance, even if some customer needs are affected by supply chain disruptions, and can help firms sell products more effectively, thereby improving the capability to withstand supply chain disruption. On the one hand, a diversified customer base can help firms better cope with the risk of supply chain disruptions, while, on the other hand, the supply chain structure brought about by supply chain diversification is more complex, which may require firms to spend more time and energy coordinating the relationship between supply chain members.

The digital transformation of manufacturing is also an important way for firms to adapt [12]. The core of digital transformation is the use of digital technology to empower firms through the in-depth deployment and configuration of digital capabilities, facilitating the timely prediction of possible risks to firms, a reduction in the uncertainties faced by firms, and an improvement in their ability to cope with risks. Therefore, the implementation of digital transformation is also an important way for firms to cope with supply chain risks and improve supply chain resilience [13]. At present, most of the research on digital transformation regards it as one-dimensional, which explains why some firms improve their performance by implementing digital transformation, while others hurt their performance. According to the resource orchestration theory, firms not only need to possess specific resources, but, more importantly, they need to orchestrate, configure, and utilize resources correctly. Therefore, based on the perspective of resource orchestration [14], we divide the digital transformation of firms into digital transformation breadth and digital transformation depth; in such a classification system, digital transformation breadth refers to the digital technology adopted by the firm, and digital transformation depth refers to the scale of digital transformation or the extent to which the firm uses the digital technology. Firms that deploy digital technology with greater “depth” can better complement organizational practices.

Through the above analysis, we found that although supply chain diversification and digital transformation can improve supply chain resilience, these two dimensions are mostly studied as independent research streams, and few studies have combined the two to explore how they affect supply chain resilience. Therefore, based on configuration theory, this study investigates the configuration of supply chain diversification and digital transformation to produce high supply chain resilience. The research questions in this paper are as follows:

(1)

What are the dimensions of supply chain diversification and digital transformation?

(2)

Are the dimensions of supply chain diversification and digital transformation necessary for achieving high supply chain resilience?

(3)

How can supply chain diversification and digital transformation be configured to achieve high supply chain resilience?

The results show that the dimensions of supply chain diversification and digital transformation do not form the necessary conditions for high supply chain resilience. The sufficient conditions analysis shows that three paths can achieve high supply chain resilience: The first path is driven by digital transformation, the second by supply chain diversification, and the third by supplier concentration and customer base diversification. This shows that multiple methods can be used to achieve high supply chain resilience. The innovative aspect of this study is the combination of supply chain diversity and digital transformation to explore how their configuration contributes to high supply chain resilience.

2. Literature Review

2.1. Supply Chain Diversification and Supply Chain Resilience

To maintain the normal operation of the firm, the firm needs to establish a certain degree of anti-risk ability and improve the supply chain resilience [4]. Recent research in the field of supply chain operations management proposes to increase supply chain flexibility and respond to the impact of supply chain disruptions by establishing flexibility [3,15,16]. For firms, building supply chain resilience can be accomplished by establishing some redundancy since redundancy can help firms build and improve resilience by providing some degree of buffer against the risk of supply chain disruption [3,17]. This could occur through means such as the establishment of multiple procurement strategies that will be more resistant to risks than the traditional single procurement strategy; in addition, establishing a diversified supply base can help firms reduce the single supply risk. Diversity is also considered a key determinant of resilience [18]. In this regard, supply diversification increases supply flow and profitability, while customer diversification increases demand flow [11,19,20]. Similarly, firms with a diversified customer base can help protect against downstream demand disruption events, and by developing a diversified customer base, they can help improve their ability to recover from disruptions and improve their financial performance. In addition, studies have shown that the diversification of a city’s food supply chain can improve a city’s resistance to food disruption shocks, and policies that increase diversity in food supply chains can improve their resistance to food shocks [21]. Diversification can increase supply chain resistance, resilience, adaptability, convertibility, and innovation, which can help the supply chain to improve resilience, convertibility, and innovation [22]. Supply chain diversification can improve the responsiveness of the supply chain to risks and help firms maintain their original functions and performance in a changing and uncertain environment [17].

From the above analysis, we found that flexibility [23,24], redundancy [3,17], and other methods can help firms to establish a certain degree of resilience. Additionally, supply chain diversification belongs to the scope of flexibility and redundancy. Firms with a high degree of supply chain diversification are more able to cope with the risk of supply chain disruption and improve the supply chain resilience. We hypothesize that firms with a high degree of supply chain diversification have a higher ability to cope with risks, thereby improving the supply chain resilience. In this study, we mainly divide supply chain diversification into two dimensions: supply base diversification and customer base diversification. Firms with high diversity in their supply base have more suppliers, while firms with a highly diverse customer base have more customers. Therefore, there is a certain causal relationship between supply chain diversification and supply chain resilience.

2.2. Digital Transformation and Supply Chain Resilience

For firms, the key to improving their ability to respond to supply chain risks is to improve supply chain resilience. Digital transformation of firms can help firms improve the visibility of their supply chains [25] and improve their ability to predict risks, thereby helping firms better formulate strategies to deal with risks and improve supply chain resilience. In the current environment, in particular, the only feature we can be sure of is uncertainty. As supply chain networks particularly become increasingly complex and intertwined [26], traditional linear thinking is not the best way to solve problems. Supply chains are also increasingly characterized by nonlinear, unstable coupling systems, so supply chains also need to enhance their adaptability and stability to cope with changing external environments.

Digital capability contains three main dimensions—data, permission, and analytics—without which it is difficult to find value from the data; therefore, all three need to be combined to measure digital capability [27]. Digital transformation is a multidimensional concept [25] that can affect the firm’s performance and organization to certain degrees. The ability of firms to embrace digital transformation is affected by many factors [28], such as the external competition intensity, technology maturity, etc. Digital transformation also has the potential to impact supply chain resilience in complex causal asymmetries. For example, in the study of agile supply chains and digital transformation, digital technologies seem to be a necessary but not sufficient condition for achieving flexible supply chains [29]. In the study of digital transformation and supply chain resilience, digital supply chains mainly include digital maturity and the adoption of digital tools. Supply chain resilience is affected by digital maturity and the adoption of digital tools [30].

Previous research has linked supply chain digitization to supply chain resilience, a key concept for managers who develop capabilities to enhance the ability of their supply chains to cope with unexpected turbulence. Supply chain digitization is characterized by digital maturity and the adoption of digital tools for supply chains, and supply chain resilience is positively influenced by digital maturity and digital tool adoption [30]. Evidence from emerging market environments (particularly the automotive industry) also demonstrates the role of digital supply chain technologies. Additionally, firms are encouraged to adopt supply chain resilience practices that support the achievement of supply chain performance goals [31]. The practical impact of implementing digital transformation is often more complex, as the role of technology can be better realized if digital technologies are implemented in the right environment [32]. Digital transformation can improve resource sharing and integration and help improve supply chain resilience [32]. Studies in the field of supply chain management have highlighted relationships [33], flexibility [34], agility [29,35], and collaboration [36,37,38] as some of the main strategies to achieve supply chain resilience. Resilience is not simply about recovery after a disrupting event, but about the ability to adapt and transform. Therefore, implementing digital transformation can help firms improve their ability to predict potential risks [32]. According to resource orchestration theory [14], firms that want to have a competitive advantage require their resources and, more importantly, the ability to orchestrate resources. Therefore, based on the resource orchestration theory, we divide digital transformation into two dimensions: digital transformation breadth and digital transformation depth. Additionally, the relationship between the dimensions of digital transformation and supply chain resilience is examined.

2.3. Conceptual Model

Previous studies have confirmed the relationship between supply chain diversification and supply chain resilience [11], and the relationship between digital transformation and supply chain resilience [32]. However, there is little research to confirm how supply chain diversification and digital transformation work together to enhance supply chain resilience. Although supply chain diversification increases the ability of a supply chain to withstand risk, a diversified supply chain also often leads to a more complex supply network, which makes the supply chain less transparent. In this regard, digital transformation can improve the transparency of supply chain processes and information transfer, thus helping to manage a more complex supply chain. Given the complex interplay between supply chain diversification and digital transformation, this study mainly combines supply chain diversification with digital transformation to study how to improve supply chain resilience. To this end, we classified supply chain diversification into supply base diversification and customer base diversification. In addition, based on resource orchestration theory [14], we summarized digital transformation into two dimensions—digital transformation breadth and digital transformation depth. The digital transformation breadth mainly refers to the types of digital technologies adopted by firms, while the digital transformation depth refers to the degree to which firms use digitalization. At the same time, in this study, we also hypothesized that the contingency factor (firm size) will also affect the supply chain resilience to some extent. Therefore, based on the configuration theory, we examined how supply chain diversification and digital transformation, as well as firm size, work together on supply chain resilience from a holistic perspective; the concept model is shown in Figure 1. Using the resulting data, we investigated whether there is a complementary relationship or a substitute relationship between supply chain diversification and digital transformation in improving supply chain resilience, as well as the relationship between the firm size and supply chain diversification and digital transformation.

3. Methods

3.1. Introduction to QCA Methods

QCA was introduced by Ragin [39], while traditional research has mostly been from the perspective of linear regression to study the linear relationship between independent variables and dependent variables. The QCA approach examines how the interaction between components affects the whole from a configuration perspective rather than analyzing components in isolation. The QCA method is more suitable for studying the combined effects of multiple antecedent conditions to produce the same result [40]. There are currently three types of QCA: crisp set QCA (csQCA), the multivalue set QCA (mvQCA), and fuzzy set QCA (fsQCA) [41]. Given that the fsQCA can well reflect the degree and level of membership of the set, it has the advantages of both qualitative and quantitative analyses [42]. In this study, we used the fsQCA method. FsQCA can identify both necessary and sufficient conditional relationships; therefore, the fsQCA method was used to study the complex causal mechanisms between supply chain diversification, digital transformation, firm size, and supply chain resilience. In FsQCA, configuration theory is used to conduct a cross-case comparative analysis, and the method ensures the exploration of which conditional elements of the configuration cause the expected results. At the same time, the fsQCA method combines the advantages of qualitative and quantitative research, thus not only solving the generalizability problem inherent in a qualitative analysis of a few cases but compensating, to a certain extent, for the lack of qualitative changes and phenomena analysis inherent in a purely quantitative analysis with large sample sizes.

3.2. Sample Selection and Data Sources

The sample of this study was collected mainly from the CSMAR database, and we mainly used the digital transformation data in the CSMAR database and the data from the supply chain research database. The most important ability of supply chain resilience is the ability of the supply chain to recover from the interruption to its original state after the supply chain is subject to the risk of interruption. Therefore, in this study, we focused on 2020 data, as Q1 2020 is the quarter in which businesses were most affected by COVID-19, while Q2, 3, and 4 are the quarters of gradual economic recovery [11]. Therefore, we mainly chose the data of manufacturing firms in 2020 as supporting data, because the manufacturing industry usually has more suppliers and customers, and its supply network is more complex and more in line with the increasingly complex and intertwined nature of supply chains. We first screened manufacturing firms by manufacturing industry code using digital transformation data, as well as CSMAR data, based on which C13–C42 represent manufacturing firms; then, data were filtered by industry type, and then the data of 2020 were screened. Additionally, by matching the data with the scale of the firms, the obtained data were matched with the indicators found in studies focusing on the supply chain in the literature, and the data of a total of 191 firms completed our obtained data.

3.3. Measurement and Calibration of Results and Antecedent Conditions

3.3.1. Measurement of Results and Antecedent Conditions

In this study, we focused on multiple causal relationships between supply chain diversification, digital transformation, firm size, and supply chain resilience. Supply chain diversification was divided into supply base diversification and customer base diversification, and digital transformation was divided into two dimensions—digital transformation breadth and digital transformation depth. In what follows, a detailed definition of each dimension is provided.

Supply base diversification: The more suppliers a firm has, the better it can cope with the supply disruption risks and improve supply chain resilience. The higher the supply chain concentration index, the lower the degree of supply base diversification.

Customer base diversification: Customer base diversification refers to the number of customers that a firm has. The more customers a firm has, the more it can avoid the risks associated with concentrating on a single customer and improve supply chain resilience. A higher customer concentration indicator indicates a lower degree of customer diversity.

Digital transformation breadth: The digital transformation breadth mainly refers to the type of digital technology that is adopted by firms, and the measurement of the digital transformation breadth is mainly based on the relevant data on the degree of digital transformation provided by the CSMAR database, which is a digital transformation database. Digital technology mainly includes artificial intelligence technology, blockchain technology, cloud computing technology, big data technology, and digital technology applications; we assessed the digital transformation breadth according to the number of types of these technologies adopted by firms; for instance, if the firm adopts five technologies at the same time, it indicates that the digital transformation breadth of the firm is higher, and vice versa, in which case it indicates that the digital transformation breadth is lower.

Digital transformation depth: This refers to the degree to which firms apply digital technologies. In this study, we mainly measured the digital transformation depth based on the sum of the frequency of the above five technologies publicly disclosed by listed firms and provided by the CSMAR database. The larger the total number of frequencies, the deeper the digital transformation depth of the firm, and conversely, which indicates that the digital transformation depth is not enough.

Firm size: We mainly used the total firm asset size to measure a firm’s size, because the total asset size of the listed company is relatively large, so we drew on the mature academic research—namely, the natural logarithm of the total assets of the firm [43]. The greater the natural logarithm value of the total assets of the firm, the larger the firm, and the smaller the number, the smaller the size of the firm.

Supply chain resilience: Supply chain resilience refers to the ability of a firm to recover from supply chain disruption risks to its original state. For the measurement of supply chain resilience, we mainly used data from firms in 2020 since the first quarter of 2020 was the most severe quarter affected by COVID-19, and the second, third, and fourth quarters were the recovery quarters. Thus, we measured the supply chain resilience as the average of the second to fourth quarters minus the value of the first quarter divided by the absolute value of the first quarter. The larger the indicator obtained, the higher the supply chain resilience, and vice versa, the lower the obtained value, the lower the resilience of the supply chain.

3.3.2. Calibration of Results and Antecedent Conditions

The most important issue of using the QCA method is to calibrate the measured conditions so that they are converted into the concept of sets, as uncalibrated data have no universal significance. Due to the lack of reference from external standards in our study, to avoid errors caused by a lack of theoretical and practical experience, in this study, we mainly used quantiles for calibration; that is, 90%, 50%, and 10% of the antecedent conditions and outcomes were used to represent anchor points falling fully within the threshold, crossover points, and full out anchor points falling fully outside the threshold values [44]. Therefore, based on quantile calibration, the calibration anchor points for this study are shown in

Table 1. Fuzzy set calibration.

Sets	Fuzzy Set Calibration
	Full In	Crossover Point	Full Out
Firm size	24.1	22.22	20.8
DT breadth	4	3	1
DT depth	61	11	2
Customer concentration	74.35	40.28	13.853
Supplier concentration	54.182	28.02	15.43

.

4. Results

4.1. Analysis of Necessary Conditions

In QCA analysis, a necessary analysis is performed before a sufficient conditional analysis is performed; it identifies whether there are necessary conditions that will cause the results to occur. In a necessity analysis, a causal condition is considered necessary for the outcome if the consistency score exceeds 0.90. We used fsQCA software to analyze the antecedents for achieving high supply chain resilience and low supply chain resilience, as shown in

Table 2. Necessity test of single conditions using the QCA method.

	High Supply Chain Resilience		Low Supply Chain Resilience
	Consistency	Coverage	Consistency	Coverage
Firm size	0.670655	0.622703	0.587007	0.657952
~Firm size	0.631611	0.558866	0.663385	0.708587
DT breadth	0.621110	0.619606	0.570782	0.687364
~DT breadth	0.686605	0.569918	0.684123	0.685502
DT depth	0.608029	0.599938	0.558647	0.665410
~DT depth	0.660897	0.553661	0.664126	0.671630
Customer concentration	0.633993	0.598506	0.671630	0.693860
~Customer concentration	0.675708	0.588657	0.647690	0.681145
Supplier concentration	0.603511	0.565489	0.606532	0.686060
~Supplier concentration	0.664951	0.583324	0.615857	0.652182

. From Table 2, we can derive that there was no antecedent condition of consistency exceeding 0.9 in the analysis of high supply chain resilience and low supply chain resilience. This shows that these five antecedents did not have the necessary conditions for the result, and the individual parameters’ conditions were not sufficient for the result. Therefore, multiple antecedent conditions had to be configured for analysis.

4.2. Analysis of Sufficient Conditions for Supply Chain Resilience

The above-mentioned analysis of the necessary conditions shows that there were no necessary conditions for the results to be produced. Sufficient conditional analysis was, therefore, required. In this study, we used fsQCA 3.0 software to analyze configurations that produced high supply chain resilience and low supply chain resilience.

4.2.1. Configurations That Lead to High Supply Chain Resilience

In conducting the analysis, we set the threshold of original consistency to 0.8 and the frequency number to 1.5% of the total number of cases, according to the recommendation of previous studies; therefore, the frequency number in this study was set to 3. Additionally, based on the results, we identified the conditions that appeared in both the intermediate and parsimonious solution interruptions as core conditions, while the conditions that appeared only in the intermediate solution were identified as peripheral conditions. Taking this into account, the results of the QCA analysis in this study are shown in

Table 3. Configuration of high supply chain resilience in fsQCA.

	High Supply Chain Resilience
	Digital Transformation Driven	Supply Chain Diversification Driven	Supplier Concentration and Customer Base Diversification Driven
Firm size	⬤	⊗	⬤
DT breadth	●	⊗	⊗
DT depth	⬤	⮾	⊗
Customer concentrate		⊗	⊗
Supplier concentrate		⊗	⬤
Raw coverage	0.432094	0.278673	0.23396
Unique coverage	0.252733	0.0804921	0.0410069
Consistency	0.75657	0.860561	0.840603
Solution coverage	0.598782
Solution consistency	0.753042

Note: ⬤ Core conditions presence; ⊗ core conditions are absent; ● peripheral conditions presence; ⮾ peripheral conditions are absent.

. In this study, three configurations achieved high supply chain resilience. Additionally, according to the process of group naming [45], we named the first path as the digital-transformation-driven group, the second path as one driven by supply chain diversification, and the third path as one driven by supplier centralization and customer base diversification. In what follows, a detailed explanation of these three configurations is provided.

In Table 3, a total of three paths of first-order configuration schemes are shown, which are adequate for achieving high supply chain resilience because they had high consistency and coverage (0.75, 0.60). From the above table, it is clear that there were three paths to achieving high supply chain resilience.

The first path is digital-transformation-driven. In this category, firm size and digital transformation depth are the core conditions, and digital transformation breadth is the peripheral condition, resulting in the achievement of high supply chain resilience. This path shows that, for large firms, high supply chain resilience can be achieved through the deep application of digital technologies and with the application of multiple digital technologies as support, which means that, for large firms, the deep application of digital technologies is the key to achieving high supply chain resilience. In large firms, in particular, supply networks tend to be more complex; therefore, in order to better manage complex supply networks, they will prefer to implement digital transformation. Additionally, the implementation of digital transformation often requires more financial support, and large enterprises tend to have more capital and financial power, thus having sufficient funds to support digital transformation. Therefore, large firms can enhance the ability to cope with risks through the implementation of digital transformation, thus improving supply chain resilience. The second path is driven by supply chain diversification. Firms can achieve high supply chain resilience when firm size, digital transformation breadth, supplier concentration, and customer concentration are absent as core conditions, as well as when digital transformation depth is absent as a peripheral condition. The absence of customer concentration and supplier concentration as core conditions indicates that firms need to have diversified supply chains, and this path also indicates that, although the degree of digital transformation is not high enough in small farms, they can also achieve high supply chain resilience because they have a diversified supply base and a diversified customer base. This path suggests that for small firms not having sufficient capital to support digital transformation, their ability to respond to supply chain disruptions can be improved by building a diverse supply chain and customer bases, thereby increasing supply chain resilience.

The third path is driven by supplier concentration and customer base diversification. Firms in his group can achieve high supply chain resilience when the firm size and supplier concentration are core conditions, while digital transformation depth and breadth are absent as peripheral conditions, and customer concentration is absent as a core condition. This path shows that even large firms with a low degree of digital transformation can achieve high supply chain resilience with a diverse customer base and high supplier concentration. This also shows that some large manufacturing firms with a more concentrated supply base and a more diversified customer base can also cope well with supply chain risks. These types of firms are mainly technology-oriented manufacturing firms and mainly customer-oriented, with a more concentrated supplier and a wide customer base; thus, although the degree of their digital transformation is not high, they can also achieve high supply chain resilience, since, when faced with the risk of supply chain disruption, a diversified customer base can help firms better cope with the risk of demand disruption. Additionally, and in the same vein, a more concentrated supplier base can help firms better organize production and proactively respond to changes brought about by the market and environment. For example, due to the impact of COVID-19, many firms are using local procurement to ensure the continuity of production sections, as well as broadening their sales channels to ensure normal operation.

4.2.2. Configurations That Lead to Low Supply Chain Resilience

In this study, we also examined the configurations that generated low supply chain resilience. The configurations that generated low supply chain resilience are shown in

Table 4. Configuration of low supply chain resilience in fsQCA.

		Low Supply Chain Resilience
	S1	S2	S3	S4	S5
Firm size		⊗	●	⊗	⬤
DT breadth	⮾	●		⮾	⬤
DT depth	⊗	⬤	⮾		⊗
Customer concentrate	⬤		●	⮾
Supplier concentrate				⬤	⮾
Raw coverage	0.414542	0.363781	0.306976	0.2719	0.233889
Unique coverage	0.0921795	0.116997	0.008593	0.0439774	0.0218636
Consistency	0.78112	0.829614	0.822759	0.861959	0.842227
Solution coverage	0.704533
Solution consistency	0.785463

Note: ⬤ Core conditions presence; ⊗core conditions are absent; ● peripheral conditions presence; ⮾ peripheral conditions are absent.

, which indicates that five configurations can achieve low supply chain resilience. Configuration S1 shows that the presence of customer concentration as a core condition, the absence of digital transformation depth as a core condition, and the absence of digital transformation breadth as a peripheral condition leads to low supply chain resilience. Configuration S2 shows that the presence of digital transformation depth as a core condition, the absence of firm size as a core condition, and the presence of digital transformation breadth as a peripheral condition leads to low supply chain resilience. Configuration S3 shows the results of achieving low supply chain resilience when the firm size and customer concentrations are peripheral conditions, and digital transformation depth is absent as a peripheral condition. Configuration S4 shows that, in the case where supplier centralization is a core condition, firm size is an absent core condition, and digital transformation breadth and customer concentration are absent as peripheral conditions, low supply chain resilience is achieved. Configuration S5 shows that the presence of firm size and digital transformation breadth as core conditions and the absence of digital transformation depth as core conditions lead to low supply chain resilience. From these configurations leading to low supply chain resilience, it can be seen that firm size as a core condition is absent in both S2 and S4 configurations. These two paths also validate that, for SMEs, single implementation of digital technologies and focusing only on customer base diversification and supply base centrality lead to low supply chain resilience. In contrast, S1, S3, and S5 configurations show that a low depth of digital transformation can easily lead to low supply chain resilience.

4.3. Robustness Test

To ensure the robustness of our findings, we adjusted the frequency thresholds of the cases from three to four and five and re-examined the grouping of supply chain diversification and digital transformation with high supply chain resilience, and the results showed no significant change in our results. According to the study of Greckhamer et al. [46], the adjustment of the parameters did not result in substantial changes in the number, composition, consistency, and coverage of the configuration, and the results can be considered robust.

5. Discussion

In this study, we applied the fsQCA method based on configuration theory to verify the relationship between supply chain diversification, digital transformation, and firm size and supply chain resilience. The results show that three paths can achieve high supply chain resilience. Path 1 is digital-transformation-driven, path 2 is driven by supply chain diversification, and path 3 is driven by supplier concentration and customer base diversification. Meanwhile, our analysis of the configurations that achieve high supply chain resilience and low supply chain resilience shows that the configurations that achieve high supply chain resilience and low supply chain resilience are not exactly symmetrical.

First, our results confirm the important role of digital transformation in achieving high supply chain resilience. This is consistent with previous research findings, i.e., firms can achieve high supply chain resilience by implementing digital transformation [32]. Our results also show that, for large firms, the depth of digital transformation is more important with the breadth of digital transformation as a peripheral condition; that is, for large firms, not only the layout of digital technology is needed, but the application of digital technology is even more important. The in-depth application of digital technology can help firms predict the possible risks in advance and take countermeasures in advance. It can also promote information sharing in the supply chain and reduce the risks caused by untimely information transmission and data sharing in the supply chain. Therefore, for large firms, it is not only necessary to adopt digital technology but also to strengthen the application of digital technology, to improve supply chain resilience.

Second, our study indicates the important role of supply chain diversification in achieving supply chain resilience [11]. According to our findings, for small firms, supply chain resilience can be improved by implementing supply chain diversification even when there is not enough capital to adopt digital technologies and when the degree of digital transformation is not high. This also shows that, for SMEs, there is not enough capital to support the implementation of digital transformation; in such cases, increasing the number of suppliers and expanding the customer base, i.e., a diversified customer base and supply base, can help firms cope with the supply chain disruption risks and improve the supply chain resilience of SMEs.

Finally, our results also show that, except for digital transformation and supply chain diversification that can achieve high supply chain resilience, there is another path that can achieve high supply chain resilience—namely, a path driven by supplier concentration and customer diversification. The grouping of the third path shows that, for some large firms with low digital transformation, a diverse customer base can help firms to achieve high supply chain resilience with high supplier concentration. For some supplier-concentrated firms, a diversified customer base can improve the firm’s ability to cope with risks; the supplier-concentrated firms are mostly related to technology-based manufacturing industries, which are mostly represented by more concentrated suppliers and a large customer base.

In conclusion, our findings suggest that (1) digital transformation of manufacturing and supply chain diversification are important components for achieving high supply chain resilience; (2) there is no complementary relationship between digital transformation of supply chain and supply diversification. This may also explain why previous studies rarely combine supply chain diversification and digital transformation; and (3) there is an asymmetric causal relationship between the paths to achieving high supply chain resilience and low supply chain resilience.

6. Implications

6.1. Theoretical Implications

First, this study classified digital transformation into digital transformation breadth and digital transformation depth from the perspective of resource orchestration, while few studies have examined the extent of digital transformation from the perspective of resource orchestration. Based on the resource orchestration theory, it was proposed that digital transformation requires firms to not only have digital technology resources themselves but to orchestrate digital technology and fully utilize and deploy digital technology resources. Therefore, this study extends the investigations on the degree of digital transformation by studying it from a new perspective.

Second, in this study, the relationship between digital transformation, supply chain diversification, and supply chain resilience was confirmed; our findings revealed that there are three configurations to achieve high supply chain resilience: The first one is digital-transformation-driven, the second one is driven by supply chain diversification, and the third one is jointly driven by supplier concentration and customer diversification. Based on our findings, we confirmed the relationship between digital transformation and supply chain resilience and the relationship between supply chain diversification and supply chain resilience, which, in turn, validated previous research on supply chain diversification and supply chain resilience and between digital transformation and supply chain resilience.

Third, besides the relationship between digital transformation and supply chain diversification and supply chain resilience, our research also shows that supply chain diversification is not the only way to achieve high supply chain resilience. In addition to diversification, supplier concentration can also achieve high supply chain resilience under certain conditions. For some large manufacturing firms with a low degree of digital transformation, customer diversification can help firms improve supply chain resilience if the firm adopts a high degree of supplier concentration. For these technology-based manufacturing firms, their suppliers are often concentrated, and the strategy of these firms is customer-oriented; thus, by sufficiently extending the customer base, high supply chain resilience can be achieved in this case.

6.2. Practical Implications

First, our research confirms that implementing digital transformation can achieve high supply chain resilience. Therefore, large firms that want to improve their supply chain resilience can deploy diverse digital technologies by actively implementing digital transformation, and the deeper use of digital technologies can help these types of firms improve the level of data and information sharing, better manage various business processes, and improve their ability to predict potential future risks, thus improving the ability of firms to cope with risks and improving supply chain resilience.

Second, supply chain diversification is also a way to improve supply chain resilience. Most of the firms that have implemented supply chain diversification are concentrated in small firms, with a low degree of digital transformation. Therefore, SMEs that want to improve supply chain resilience can improve their ability to cope with the risk of supply chain disruption by diversifying both their customer base and supply base.

Third, for customer-oriented large firms with a low degree of digital transformation, when suppliers are relatively concentrated, the firms can improve their ability to cope with supply chain risks by expanding their customer base; such firms are mainly concentrated in technology-based manufacturing firms. Therefore, firms can choose a suitable path to improve supply chain resilience by combining their size and the degree of digitalization.

6.3. Limitations and Future Research Directions

Similar to other studies, our study also has several limitations. First, the data source of this study mainly involved listed manufacturing firms; therefore, it cannot fully represent all manufacturing firms, and future studies can be conducted for unlisted manufacturing firms. Second, this study examined the relationship between supply chain diversification and supply chain resilience from the perspective of the diversification of supply chain structure; thus, as a future perspective, responsive diversification of supply chains can be used to analyze the relationship between supply chain diversification and supply chain resilience, providing a more in-depth understanding of this relationship. Third, we mainly used secondary data to support the conclusions of this study; therefore, future studies can explore the impact of primary data on these results by focusing on primary data collection.