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Article

Digital Transformation: Moderating Supply Chain Concentration and Competitive Advantage in the Service-Oriented Manufacturing Industry

1
School of Economics and Management, University of Electronic Science and Technology of China, No. 2006 Xiyuan Avenue, Gaoxin District (West Zone), Chengdu 611731, China
2
School of Economics and Management, Inner Mongolia Normal University, No. 81 Zhaowuda Road, Saihan District, Hohhot 010022, China
*
Author to whom correspondence should be addressed.
Systems 2023, 11(10), 486; https://doi.org/10.3390/systems11100486
Submission received: 13 August 2023 / Revised: 12 September 2023 / Accepted: 13 September 2023 / Published: 22 September 2023

Abstract

:
One of the service-based manufacturing concepts emphasizes relationship orientation and building strong customer relationships, while Industry 4.0 enables companies to be proactive in the supply chain. However, to achieve digitally driven growth, service-based manufacturing requires a shift away from the traditional upstream and downstream hierarchy toward a collaborative model. In this study, service-oriented manufacturing companies in the packaging and printing industries are selected as case studies to examine the relationship between supply chain concentration, digital transformation, and corporate competitive advantage from the perspectives of power control and equilibrium. The results show that a high supply chain concentration harms firms’ competitive advantage, especially when power is unevenly distributed. Moreover, digital transformation plays a moderating role in this relationship, suggesting that it is possible to improve firms’ competitiveness and further equalize the power balance by applying digital technologies to supply chain processes. The study revealed significant heterogeneity within the group of companies in terms of ownership type, dual management roles, and company size. In summary, this study makes a unique contribution to the growing research field of supply chain digital transformation. It provides valuable insights from a power balance perspective for service-oriented manufacturing companies seeking to enhance their competitive advantage in a rapidly changing market environment.

1. Introduction

As we transition from the industrial age to the digital age, the essence of production and industry remains unchanged [1]. However, with advances in our understanding of industry and breakthroughs in technology and business, an important trend is emerging: the convergence and overlap of industries. This trend, epitomized by the merging of manufacturing and services, has spawned new production methods and industrial models [2]. Service-oriented manufacturing is an excellent example of the development and integration of the manufacturing and service sectors. Service-oriented manufacturing represents an innovative production paradigm that combines advanced manufacturing with contemporary service delivery. This approach is distinguished by its emphasis on personalized design, extended service lifecycles, a heavy reliance on information technology, and the creation of high-value-added products [3]. Within this industry, service provision is recognized as a fundamental component for enhancing the competitiveness and profitability of enterprises [4]. In addition to providing one-time product transactions, companies engaged in service-based manufacturing possess the potential to offer comprehensive solutions to their clients, transitioning from basic, product-centric services to tailored, process-oriented solutions [5]. The service-oriented manufacturing landscape, spanning both upstream and downstream activities, typically encompasses a diverse array of industries and fields. These encompass design, processes, component production, repair and maintenance, logistics, marketing, post-sales support, software development, intelligent manufacturing, R&D innovation, human resources, and intelligent testing [6]. Furthermore, it is important to note that these entities may not always operate independently, as they can concurrently engage in both upstream and downstream activities within the service-oriented manufacturing sector.
The source of a company’s competitiveness has become inextricably linked to the ecosystem in which it operates. A company’s ecosystem consists of consumers, suppliers, key producers, competitors, and other risk-takers [7]. The competitive advantage of the service-based manufacturing industry is influenced by a multitude of factors, including technology, supply chain efficiency, service quality, talent management, and brand establishment. In particular, the effectiveness and synergy of supply chain management play a pivotal role in impacting a company’s production capabilities and customer experience [8,9]. Compared to traditional manufacturing, the supply chain in service-based manufacturing is often more intricate and requires the realization of synergies across various links. While the impact of supply chain relationships on a company’s competitive advantage has been empirically examined in existing studies, achieving a sustainable competitive advantage in manufacturing necessitates the establishment of enduring business relationships with major customers and key suppliers, ensuring stable production and mitigating the risk of supply chain disruptions [10,11]. Nonetheless, it is essential to acknowledge that close partnerships may also entail inherent risks [12]. Furthermore, powerful upstream and downstream enterprises may prioritize their interests by negotiating favorable contract terms [13]. While most research efforts have concentrated on mitigating risks and minimizing the impact of supply chain concentration on the competitive advantage of midstream manufacturers in the context of supply chain transformation and the upgrade of traditional manufacturing industries [14,15,16], a notable scarcity of empirical evidence from the upstream and downstream industries within the service-oriented manufacturing sector remains.
The core of service-oriented manufacturing is to overcome the differences between the manufacturing and service industries based on their different performance characteristics and to change traditional industrial relationships [17]. Supply chain complexity is the driving force behind digital transformation for core companies [18]. It is also a key driver of digital modernization when companies face bottlenecks in the marketplace or when they are in an industry in transition. With the promotion of research on and application of the service-oriented manufacturing industry, the use of information technology to promote R&D, production, management, and other aspects of change in the service-oriented manufacturing industry seems to have become a solution to the supply chain problems at the breakthrough point, meaning that the digital transformation of service-oriented manufacturing enterprises has become a hot topic of discussion in the industry. Industry 4.0 enables companies to be proactive rather than reactive throughout the value chain [19]. The concept of Industry 4.0 encompasses both the process-oriented aspect of digital transformation and the outcome-focused approach of a novel manufacturing paradigm [20]. Those who do not embrace new technologies will be affected by the digital transformation [21], therefore, companies need to integrate rapid digital transformation into their processes [22]. Digital transformation is the adoption of advanced tools such as big data [23], the Internet of Things, cloud computing, and artificial intelligence to transform technological innovation into digital productivity, i.e., to digitize operational capabilities [24,25]. Digital transformation is considerably more extensive and all-encompassing than prior IT technological advancements [26]. It concentrates not exclusively on enhancing technological tools and systems, but also on including crucial modifications to the culture, processes, and strategies of the entire organization, which is altering long-standing production methods and giving rise to innovative business models and forms of contingent employment [27]. Digital technologies have been shown to improve supply chain efficiency, transparency, collaboration, and adaptability, giving companies a competitive advantage [28,29]. In addition, previous research has shown that it is critical in digital transformation to consider critical aspects such as the linkages between different entities [30]. However, whether the service-oriented manufacturing industry is suitable for digital transformation at this stage, what problems will be encountered in the transformation, and other “black box” issues have yet to be discussed [31].
For an understanding of some factors relating to the study of service-oriented manufacturing, the packaging and printing sector was selected as a paradigmatic case in this study. The packaging and printing industry can be divided into publishing printing, packaging printing, and other printing segments. Packaging and printing involve the application of decorative patterns, designs, or text to various packaging materials to enhance the appeal or information content of products. This serves the purpose of conveying information and increasing sales. Looking at the industry’s supply chain, the upstream sectors include the production companies for packaging raw materials such as packaging paper and energy supply companies, while the downstream sectors consist of industrial and consumer goods production companies and transport companies. From an industry chain perspective, the printing and packaging industry is a typical midstream industry. Both the lack of control over the cost of upstream raw materials, and the downstream demand side of the drive, pose major challenges to industrial development. Specifically, with the rapid growth of the consumer electronics packaging industry, the packaging printing business model has also changed dramatically. It has evolved from simple sourcing relationships to “comprehensive packaging printing solution providers”. In this new model, packaging companies not only provide their customers with packaging products but also offer a wide range of services, such as packaging design, third-party sourcing, logistical distribution, inventory management, and more [32]. Secondly, the packaging sector is one of the parts of the world economy that is growing the fastest. Digital technology has emerged as a revolutionary force in this constantly changing environment, ushering in a new era for packaging printers that must contend with short print runs and tight deadlines [26,27]. Additionally, the Sustainable Development Goals are pursued by packaging and printing businesses using digital technologies that are largely focused on advancing important fields like cloud computing, big data, and the Internet of Things (IoT) [33]. Thirdly, the supply chain of the packaging and printing industry exhibits mutual dependencies from the point of view of power dynamics in the supply chain [34,35,36]. Most importantly, the issue of excessive concentration in the supply chain in the packaging and printing industry is prevalent not only in the service sector but also in the manufacturing sector in Europe and North America [37,38].
Therefore, this study focuses primarily on the following questions, which distinguish it from previous research:
RQ1. To what extent does supplier concentration affect the competitiveness of manufacturers within the supply chain of the service-based manufacturing industry?
RQ2. Can the transition from a hierarchical to a collaborative structure in manufacturers’ upstream and downstream supply chains be mitigated by digital transformation?
RQ3. Does the impact of supply chain concentration on a firm’s competitive advantage remain consistent across different ownership structures, board role combinations, and firm sizes?
The findings from this study make several contributions to the current literature: Firstly, the existing literature mainly emphasizes the potential of integrating digital technologies to increase competitiveness [39,40,41,42]. In contrast, this study, which starts from the premise that digital transformation promotes a firm’s competitive advantage, examines the potential impact of digital transformation on power dynamics within supply chain relationships. Secondly, previous studies have mainly concentrated on the macro level, such as countries, provinces, and cities [43]. There has been a lack of research, particularly on service-based manufacturing, examining the disparities between industry sectors in emerging and rapidly evolving areas like Industry 4.0 [44,45]. Given the widespread use of qualitative methods in empirical research on service-oriented manufacturing [46], this study provides new empirical insights into how supply chain relationships affect the competitive advantage of industrial firms. Third, the research findings reveal remarkable differences in the effects of supply chain concentration on a firm’s competitiveness.
The article is organized as follows: The Section 1 provides an “Introduction to the Background”. The Section 2 provides a “Literature Review” from the last five years on “Servitization in the Manufacturing” and “Packaging and Printing Industries”. The Section 3 deals with “Background and Hypothesis Development”. The Section 4 outlines the “Research Methodology”. The Section 5 presents the “Empirical Analysis and Results”. The Section 6 deals with the “Heterogeneity Analysis”. The Section 7 deals with “Robustness Testing”. Finally, the Section 8 concludes with “Conclusions and Implications”.

2. Literature Review

2.1. Servitization in the Manufacturing Context

In defining servitization, it was originally described as “the service elements offered by manufacturing firms” [47]. In recent years, servitization has been defined as a method of increasing manufacturers’ competitive edge by adding services to their product offerings [48]. In this study, we focus on the services offered by manufacturing firms. Therefore, we emphasize the transition “from product manufacturer to service provider” [49], where manufacturers gradually integrate services into their core product offering to customers [50]. Table 1 organizes the literature in this evolving field into three related areas over the last five years (excluding the definition section): The first area concerns the definition of service-oriented manufacturing. The second area discusses the benefits of servitization for manufacturing. The third area of literature focuses on the growth trajectories of manufacturers with a service-centric approach. Our study fills a gap regarding micro-foundational analysis [46] by examining digital transformation, and the findings highlight the significant role of digital transformation in balancing power among service-oriented manufacturing organizations.

2.2. Packaging and Printing Industries

Based on an extensive literature search using the search terms “printing”, “packaging”, and “printing and packaging” in both Google Scholar and the Web of Science, it appears that the majority of existing studies focus primarily on industrial production, materials, environmental impact, and marketing, which are listed in Table 2. Few studies address supply chain management and strategic management in the context of the printing and packaging industries. This observation highlights a significant research gap that we aim to fill with our study and thereby contribute to the existing body of knowledge.

3. Background and Hypothesis Development

3.1. Supply Chain Relationships and Corporate Competitive Advantage

As opposed to the primary and tertiary sectors, manufacturing enterprises are more relevant to the supply chain interaction [90]. One of the concepts of service-based manufacturing is that companies should be relationship-oriented, thus building long-term and strong ties with their customers [91]. This long-term strategic relationship based on services requires manufacturers to cooperate with their customers more broadly and strategically at multiple structures and levels [92]. According to the social expectedness theory perspective, the cooperative relationships established between manufacturing firms and upstream and downstream firms in the supply chain can reduce production costs and increase production stability; therefore, such relationships can be understood as the relationship-network-based social capital that manufacturing firms actively acquire [12]. In this paper, the supply chain relationship is defined as a profit-sharing-based business relationship established between the producing enterprise and its suppliers and customers in their daily business activities. The so-called competitive advantage, which is achieved by the enterprise through its characteristics and resources, shows an advantage over other enterprises in the same industry or market, and the competitive advantage of the enterprise is a guarantee for the enterprise to obtain excessive profits [93].
In the production and operation process, high production costs, lack of information sources, and lack of advantages of speed can lead to a company’s disadvantage in competition. A good supply chain relationship can create external governance pressure and reduce corporate transaction costs [94]; it also becomes a heterogeneous intangible resource that firms can accumulate, helping them to form core competencies [94]; and it can also contribute to the development of innovation capabilities and improve their innovation performance to some extent [95]. On the other hand, supply chain relationships can also affect the flexibility of firms’ strategic adjustments, making them tend to choose more conservative, stable, or defensive strategies to avoid uncertain risks [96]; they can also lead to excessive spending on dedicated asset investments to maintain supply chain relationships [97], especially in highly competitive industries, exposing firms to more risks of financial predation and reducing investment opportunities. In the relationships and exchanges between the entities, the impact of the power imbalance is clear. Suppliers with more clout can disadvantage their supply chain partners when it comes to decision making and resource allocation [36]. It is clear that the number and make-up of suppliers may vary as a result of this change in supply chain collaboration [98]. It can be concluded that supply chain relationships can affect a firm’s competitive advantage in the industry.
As a capital-intensive industry with high energy consumption and pollution rates, the packaging and printing industry maintains a strong cooperative stickiness with the upstream and downstream of the supply chain in terms of technology sharing, collaborative production, and industrial upgrading to adapt to the developmental requirements of a low-carbon economy. Due to the low industry concentration of packaging and printing enterprises, the cooperative stickiness of the supply chain may reduce the autonomy of enterprises, create dependence on the dominant upstream and downstream enterprises in the supply chain, and put them in a passive position in cooperative competition. In summary, Hypothesis 1 of this paper is proposed:
Hypothesis 1.
High supply chain concentration negatively affects the competitive advantage of enterprises.

3.2. Supply Chain Relationships, Digital Transformation, and Competitive Advantage

Companies strive to balance purchasing, production, and sales. Due to the complexity of supply channels, supply–demand relationships, and other factors, the information gap between purchasing and sales is large, and the synergy effects are small, exacerbating supply chain power imbalances even further. To improve the efficiency of resource and factor allocation within the industry chain and the enterprise, it is not enough to rely solely on basic supply chain controls which cannot ensure the efficient and smooth operation of the entire process. Instead, we need to use more advanced technologies and methods to maximize the benefits of supply chain relationship management and effectively reduce potential risks [99]. Here, we hypothesize the role of digital transformation in solving the supply chain relationship paradox, particularly in the adoption of innovative production methods. In service-based manufacturing, IoT technologies enable traditional manufacturing companies to shift from a product-centric to a service-centric business model. This shift facilitates the delivery of advanced customer services, increases market responsiveness in complicated scenarios, and promotes collaboration in extended smart applications and production processes [100]. Moreover, digital transformation not only revolutionizes production techniques, but also strengthens a company’s holistic capabilities in areas such as environmental protection, product innovation, and sustainable growth. As a result, this leads to smarter operating strategies and decision-making for manufacturing companies, strengthening their competitive advantage [101].
This study shows that digital transformation can mitigate the loss of competitive advantage associated with more concentrated supply chains. We hypothesize that the interaction between supply chain relationships and digital transformation has a linear effect on firms’ competitive advantage. To have a significant positive impact on competitive advantage, service-based manufacturing firms must invest sufficiently in supply chain relationships and digital transformation, enhance communication between departments and integration capabilities at all levels, flatten the hierarchical structure of the enterprise, and create collaborative networks within the enterprise and among corporate partners [102]. Digital transformation encompasses the entire ecosystem in which a company operates and will extend to all entities in the ecosystem as a company’s digital technology matures and its real business needs evolve. Significant investments in digital supply chain management bring these innovations to the forefront. They add value to all aspects of a company’s production operations and serve as a foundation for developing strategic resources and core competencies. Similar findings have already been made in digital transformation research, where researchers found that digital transformation plays an important role in impacting competitive advantage [101,102,103,104]. This means that companies should pay sufficient attention to digital transformation to make a difference and make continuous strategic changes, enabling them to continuously restructure and adapt their competitive capabilities in response to environmental changes [105].
Finally, the combination of supply chain relationship and digital transformation can create an efficient synergy mechanism with all parties in the supply chain through the digital platform to improve the efficiency and synergy of the whole supply chain and reduce the transaction risks and cost pressures in the traditional industry, and more accurately understand the operation of the whole supply chain and capture the information of downstream enterprises, such as suppliers and distributors, to better control transaction costs and reduce the pressure on prices due to a high degree of centralization. In the current context, digital transformation provides solid support for companies to unlock the potential value of supply chain relationships. It serves not only as a core resource within a company but also as a powerful tool that enables companies to respond more flexibly to changes in the external environment and cover all aspects of production and operations more comprehensively. Digital transformation enables a company’s upstream and downstream activities to be accurately recorded and shared in the form of data. This dramatically improves real-time information, supplier management efficiency, and sales forecast accuracy, and achieves a better balance between purchasing and sales. Compared to traditional manufacturing companies, service-oriented manufacturing companies are more flexible in applying and adapting to new digital technologies [106]. Thus, digital transformation opens up new opportunities for the service-oriented manufacturing industry to innovate supply chain business models, such as building industrial ecosystems based on service-oriented manufacturing in order to improve supply chain innovation and competitiveness and avoid profit loss due to the paradox of supply chain relationships.
According to the National Bureau of Statistics of China, the online retail sales of physical goods in China reached CNY 119,642 billion in 2022. This figure reflects the impact of epidemic prevention and control policies and lifestyle adjustments, such as home offices, on consumer behavior, which have also included the promotion of the rapid development of take-out and express delivery industries. The increased demand for packaging and printing products in these industries has brought market opportunities for the packaging and printing industry. However, the packaging and printing industry is also facing many challenges, such as rising raw material prices, labor shortages, obstructed logistics, etc. These external environmental factors have compressed the profit margins of enterprises. To meet these challenges, packaging and printing companies need to undergo digital transformation, improve operational efficiency, perfect business models, reduce production costs and environmental risks, and gain competitive advantages in the era of the smart internet. The packaging and printing industry is a typical vertical industry, providing products and services for various industrial sectors. The industry has the distinctive features of “many product varieties, varying order and production frequencies, and difficult to control production batches”. Therefore, digital transformation can reduce the negative impact of supply chain concentration on the competitive advantage of enterprises and enhance their competitiveness by improving the visibility and transparency of the supply chain, improving the efficiency of supply chain collaboration, and innovating the business model of the supply chain in the packaging and printing industry. Based on the above analysis:
Hypothesis 2.
Digital transformation has a moderating effect on the relationship between supply chain concentration and firms’ competitive advantage. The higher the degree of digital transformation, the smaller the negative effect of supply chain concentration on firms’ competitive advantage will be; the lower the degree of digitalization, the greater the negative effect of supply chain concentration on firms’ competitive advantage will be.
The research framework is shown in Figure 1.

4. Research Methodology Design

4.1. Sample Selection and Data Sources

The packaging and printing industry used to be a part of the traditional manufacturing industry, whose main business model for a long time was selling packaging products. However, with the rapid development of the consumer electronics packaging industry, the business model of the packaging and printing industry has gradually changed from a simple procurement relationship to a “total solution provider for packaging and printing”. In addition to manufacturing packaging products for customers, packaging companies also provide a range of services, such as packaging design, third-party sourcing, logistics distribution, and inventory management. Excellent packaging companies such as Tetra Pak, Tralin Pak, WestRock, etc., have also modernized their business models accordingly. As a typical representative of the service-oriented manufacturing industry, the packaging and printing industry has the following characteristics: its products have a high degree of added value, including technical services, innovation capabilities, intelligent manufacturing, and other elements related to customer needs; its products involve multiple fields and application scenarios, such as food, cosmetics, electronics, labeling, etc., requiring customized production and delivery according to a customer’s individual needs; its product production process adopts digital technologies, such as the internet, Internet of Things, and big data, to improve production efficiency and quality, reduce costs and resource consumption, and enhance market competitiveness.
Based on these characteristics, this study selects the packaging and printing industry as a representative research sample of the service-oriented manufacturing industry, and a total of 550 valid observations were collected. We obtained information on 55 businesses involved in the packaging and printing industries from the Flush Finance industry classification for 2021. The data related to the competitive advantage of enterprises were collected from the Sina Finance and Finance and Wind databases and manually collected and calculated, the data on supply chain relationships were collected from the Guotaian database, the data on keyword text relating to digital transformation of enterprises were collected manually from the Guotaian database, Rex database, Sina Finance and Finance, and Sky Eye Search, and the data on control variables were collected from the Wind database. The data is treated as follows: first, we exclude financial firms; second, we exclude samples with ST and periodic delistings; third, this paper retains only those samples that do not have at least five consecutive years of missing data; and fourth, this paper reduces all micro-level continuous variables by 1 percent and 99 percent to reduce the impact of outliers. This paper uses Excel 2010 to collect and organize the data and uses stata17.0 to conduct empirical statistical analysis.

4.2. Variable Definition

4.2.1. Supply Chain Relationship

This paper utilizes supply chain relationships as the explanatory variable, and competitive position to analyze the impact of supply chain concentration on corporate profits. The five competitive forces theory [107] states that the five forces of the industry determine the competitive advantage of firms and vary with the stage of development of the industry, leading to differences in the level of earnings in different industries. Among the five forces, the bargaining power of suppliers and customers is an important factor affecting the profitability of production companies, and these two forces are closely related to supply chain concentration. Higher supply chain concentration implies a greater number and integration of suppliers and customers, which results in greater pressure on producers. We calculated supply chain concentration in line with previous studies by dividing the sum of sales to the top five customers by the sum of purchases from the top five suppliers [13,94], which should accurately represent the company’s position and capabilities in the supply chain. On the one hand, a higher supply chain concentration ratio indicates that suppliers and customers have stronger bargaining power and market influence in the supply chain, and thus can obtain more profit share; on the other hand, a higher supply chain concentration ratio also indicates that producers bear more market risks and inventory costs in the supply chain, which will reduce profit share.

4.2.2. Digital Transformation

To determine the level of digital transformation in companies, this study employs the method proposed by Wu Fei et al. [108]. Information that characterizes a company’s digital transformation is more likely to be found in a summary and thorough annual report. The vocabulary used in the annual report is highly reflective of the company’s philosophy and the development path guided by that philosophy. It is therefore feasible and scientifically sound to depict the degree of digital transformation of listed companies using statistics on the frequency of words related to the “digital transformation of companies” in their annual reports [109,110]. This method is based on Python’s crawler text recognition function and analysis of the annual reports of listed companies. Specifically, the “search matching summation” approach is utilized, whereby data is collected on the occurrence of key terms including artificial intelligence technology, blockchain technology, cloud computing technology, big data technology, and digital technology applications in the annual reports of businesses. By evaluating the frequency of these key terms, the extent of digital transformation of businesses can be established [111,112].

4.2.3. Competitive Advantage

Using competitive advantage as an explanatory variable, this paper refers to the study of Newbert et al. [113] and selects the average return on assets of the packaging and printing industry to calculate the average performance of the industry [114], which is one of the indicators to assess the profitability of the company [115], and then compares the calculation results with the performance of each sample company to obtain the competitive advantage of the company. The calculation methodology is as follows [113,116,117]:
ROA   =   N e t   I n c o m e A v e r a g e   T o t a l   A s s e t s
where: the term “net income” refers to the company’s net profit, which is the money remaining after paying taxes and a variety of expenses. The average value of a company’s total assets during a given period, typically on an annual or quarterly basis, is known as average total assets.

4.2.4. Control Variables

Several variables that could affect the competitive advantage of a corporation were controlled for in this study. Following the existing literature [118,119,120,121,122,123,124,125], we designed a series of control variables and added them to the model design which is shown in Table 3.

4.3. Empirical Model

In this paper, the following regression models are constructed separately to test the hypotheses:
C A = α 0 + α 1 S C C + α 2 G R O W T H + α 3 E I + α 4 L E V + α 5 R O A + α 6 P R O D U C T + α 7 R T A + Σ I D + Σ Y E A R + ε
Model (1) examines the impact of supply chain concentration on competitive advantage. Among them, α0, α1, α2, … are the regression coefficients to be estimated. CA was the explanatory variable that represented the level of firms’ entrepreneurial competitive advantage. SCC was an explanatory variable representing the level of a firm’s supply chain relationships. ID and YEAR were the dummy variables for firm and year, respectively, indicating that the research model controlled for year and firm. GROWTH, EI, LEV, ROA, PRODUCT, and RTA served as control variables. ε represents the residual term.
C A = α 0 + α 1 S C C + α 2 D I G + α 3 S C C D I G + α 4 G R O W T H + α 5 E I + α 6 L E V + α 7 R O A + α 8 P R O D U C T + α 9 R T A + Σ I D + Σ Y E A R + ε
Model (2) verifies the impact of the cross-product term of supply chain concentration and the degree of digital transformation on the competitive advantage of the firm. The study investigated the moderating impact of digital transformation (DIG) on the connection between SCC and CA. Interaction terms of SCC and DIG were added to evaluate moderation. α 3 represents the moderating effect of digital transformation on SCC and competitive advantage.

5. Empirical Analysis and Results

5.1. Descriptive Statistics

Table 4 shows the results of descriptive statistics of the main variables. The mean value of enterprise competitive advantage (CA) is 0.380, the maximum value is 36.32, and the minimum value is −34.20, which indicates that there is a large gap in competitive ability between packaging and printing enterprises in China, that most of them have no obvious competitive advantage, and that there is serious polarization. Supply chain relationship (SCC) has a maximum value of 97.58, a minimum value of 3.020, and a mean value of 36.40.

5.2. Correlation Analysis

Table 5 shows that the correlation coefficient value between supply chain concentration (SCC) and firm competitive advantage (CA) is 0.076 and is significantly correlated at the 1% level, indicating that supply chain concentration is correlated with firm competitive advantage, but the significance is not significant due to the small sample size. The specific effects of supply chain concentration on competitive advantage will be shown in the main effects analysis section.

5.3. Regression Analysis

5.3.1. Supply Chain Relationships and Corporate Competitive Advantage

By looking at Table 6 and comparing the results of the regression analysis of Model 1 without two-way fixation y and with the addition of two-way fixation, respectively, the regression coefficients of supply chain relationship (SCC) and competitive advantage (CA) are −0.0255 and −0.0293, which are significant at the 1% level. This result indicates that a high supply chain concentration negatively affects the competitive advantage of enterprises. The upstream companies in the packaging and printing industry are mainly in the paper, equipment manufacturing, and paper packaging printing industries, and the downstream are the end brand owners such as cigarette, IT electronics, and food and beverage companies. In terms of supplier relations, as a strong synergistic industry, producers and suppliers share the risk in procurement, logistics, and technology. However, due to the continuous increase in raw material prices, suppliers’ production costs have increased, and suppliers occupying a large market share are prone to transferring the raw material price risk of plant fiber, pulp raw materials, and chemical raw materials to midstream enterprises due to their strong bargaining position. In terms of brand user relations, in beauty products, electronic products, tobacco and wine, and other downstream consumer areas, the paper packaging process, quality, technical content, and other aspects of the increasingly high demand for packaging and printing enterprises in the production of orders cannot be ignored. Digital era consumption trends towards personalization and customization and consumers focusing on the experience of consumption and emotional connection, as well as the difference between online and offline packaging customization requirements, are forcing brands to focus on packaging design, causing significant pressure on midstream production enterprises. As a service-oriented processing industry, packaging and printing enterprises focus on the adjustment of machines, printing plates, environmental standards, and other production processes to manage the influence of upstream and downstream enterprises; the higher the concentration of the supply chain and the higher the degree of fixed assets is in packaging and printing enterprises, the more difficult it is to achieve economies of scale. All of the above factors will affect the profitability level and competitiveness of production enterprises to some extent, which is consistent with the theoretical prediction of Hypothesis 1.

5.3.2. Supply Chain Relationships and Corporate Competitive Advantage: A Moderating Mechanism for Digital Transformation

Table 7 reports the regression results of Model 2 when testing the effect of digital transformation (DIG) on the relationship between supply chain relationship (SCC) and firms’ competitive advantage (CA). The interaction term of digital transformation (DIG) and supply chain relationship (SCC) shows significance at the 1% level with a regression coefficient of 0.0138, indicating that the deepening of digital transformation of production enterprises can mitigate the constraining of the competitive ability of production enterprises by upstream and downstream enterprises. The findings of this study’s Hypothesis 2 were confirmed. From the perspective of the current development in the packaging and printing industry, digital transformation can improve the negative effects of supply chain relationships on competitive advantage in three aspects, raw material profit management, personalized order management, and business model transformation. The first is raw material profit management. By introducing a digital visual system, manufacturers can monitor the whole process of subsequent processing of raw materials, clearly identify the key nodes of process improvement, improve the phenomenon of large losses in the procurement of raw materials, save procurement volume, and then cope with the risk of compressed production profit after the increase of raw material supply prices. Second, for personalized order management, digital printing technology improves the production efficiency of small-lot customized orders, reduces inventory, develops consumer-driven production and customer resources, and improves the bargaining power of production enterprises. Third, for the aspect of business model transformation, packaging and printing enterprises can use the supply chain digital layout and transform their business model from simple “production and processing” to “product + service” intelligent manufacturing, including consulting, technology, equipment, environmental protection synergies, and other comprehensive packaging and printing services. In addition, the company can also connect upstream and downstream enterprises in the supply chain to create a closed-loop ecological model. In the digital transformation of the application of innovation to reduce the supply chain relationship’s impact on high business risks, enterprises can improve their competitive advantage.

6. Heterogeneity Analysis

Given the characteristics of the packaging and printing industry, including dispersed concentration, relatively small overall size, and the fact that different firm sizes can lead to different resource integration advantages, there may be differences in the effects of supply chain concentration on competitive advantage. To investigate whether there is heterogeneity in the effects of these three factors on the competitive advantage of supply chain concentration on enterprises, this study adopts a classification method based on the type of ownership, dual function of management, and enterprise size to group enterprises in the packaging and printing industry and conduct a corresponding test for heterogeneity.

6.1. Property Rights Heterogeneity Test

Specifically, we first divide enterprises into state-owned enterprises (SOE) and non-state-owned enterprises (Non-SOE) according to their governmental nature [126]. Columns (1) and (2) of Table 8 examine the effects of supply chain concentration on the competitive advantages of packaging and printing firms with different ownership. From the regression results, it can be seen that supply chain concentration (SCC) harms the competitive advantage of both state-owned and non-state-owned enterprises, but the absolute value of the marginal effect of SCC in state-owned enterprises, which is 0.0679, is smaller than the absolute value of the marginal effect of SCC in non-state-owned enterprises, which is 0.0336. Therefore, the negative effect of supply chain concentration on the competitive advantage of enterprises in non-state-owned enterprises is more obvious. The possible reason for this is that non-state-owned enterprises typically operate in competitive markets and compete with multiple suppliers and customers. When key links in the supply chain are concentrated in the hands of a small number of suppliers or customers, it is easier for these key players to exert pressure on an NSOE to obtain more favorable prices, contract terms, or other negotiating conditions [127,128].

6.2. CEO Duality and Compensation Heterogeneity Test

Board independence and CEO duality may have an impact on business performance [129]. Therefore, based on the management characteristics of the sample firms, the study classified whether the chairman of the board of directors is also the general manager into the categories of “CEO Duality” and “Board Independence”. An analysis of the regression results is presented in Table 9. The results indicate that with higher levels of concentration in the supply chain, companies that maintain separate leadership positions may face increased challenges in maintaining their competitive advantages. This greater challenge stems from the fact that the separation of positions can lead to slower decision-making processes [130]. In contrast, rapid response is a critical factor in supply chain management. It is worth noting that supply chain management brings several benefits, including achieving a sustainable competitive advantage and managing suppliers more effectively [131].

6.3. Company Scale Heterogeneity Test

The size of a company can lead to differences in its supply chain relationships and competitive advantages [132]. In this study, based on the average firm size of the sample firms, which was 21.71, firms that exceeded this value were classified as large firms, while the remaining were classified as small firms. The findings demonstrate that supply chain concentration (SCC) has a negative effect on the competitive advantage of enterprises of different sizes. From Table 10, it is evident that the absolute value of the marginal effect of SCC for large firms is 0.0287, which is larger than the absolute value of the marginal effect of SCC in small firms, which is 0.0572. This indicates that larger firms tend to have greater investment capacity in technology and innovation. They can use advanced supply chain management technologies and tools to better monitor and optimize supply chain operations to increase efficiency and mitigate risks.

7. Robustness Checks

7.1. Variable Lag Method

Table 11 represents the effect of supply chain concentration on the lagged period competitive advantage of the sample firms. The regression results show that the regression coefficient of supply chain concentration (L.SCC) is 0.0318, and that supply chain concentration (SCC) is negatively related to competitive advantage (CA) at a 1% significance level, which is consistent with the empirical results of Hypothesis 1.

7.2. Change of Variable Measurement Method

The Lerner index reflects the level of monopoly power in the market by measuring the degree of deviation of the firm’s price from its marginal cost, which is commonly used to reflect the market competitiveness of individual firms [133]. Accordingly, we choose the Lerner index as a changeable indicator of the competitive ability of packaging and printing companies. As Table 12 Column 1 shows, the empirical test results of the baseline regression finds a coefficient of 0.0667 for supply chain concentration (SCC), which is negatively significant at the 10% level, and Column 2 shows the results of the regression controlling for firm and year effects with a coefficient of −0.0805 for supply chain concentration (SCC), which is negatively significant at the 5% level, consistent with the previous findings.

8. Conclusions and Implications

8.1. Discussion

In his book The World is Flat, Friedman mentions that “global supply chains are one of the ten forces that have leveled the world” [134]. The service industry is also affected by this force. In the packaging and printing industries, for example, the paper supply chain is highly globalized, making it difficult for many companies to control the supply chain and pricing. In response to the diversification of customer orders, increasing variety, smaller batch sizes, and shorter lead times, companies must look for innovative solutions to improve efficiency. The key to success is building agile, responsive supply chains, not only within companies but also with partners. The true value of a digital supply chain lies in integrating all of a company’s business processes, from demand forecasting and procurement to production and transportation transactions, to form a complete value chain. At the heart of this management approach is the use of information technology to reduce costs.
The impact of supply chain characteristics on the degree of servitization of companies is a complex issue that still needs to be studied in depth [135]. The interplay between a manufacturer and their supply chain significantly influences several critical aspects, including cost control [65], operational efficiency [66], innovative potential [67], risk exposure [68], and collaborative endeavors [69]. To enhance customer satisfaction, elevate product value, and reinforce the competitive edge within service-oriented manufacturing, manufacturers strategically integrate their product and service resources, extending seamlessly through the value chain to the core product. Consequently, establishing effective collaborative relationships both upstream and downstream in the value chain becomes pivotal [135]. A thorough comprehension of the equilibrium characterizing the affiliations connecting manufacturers and their counterparts within the supply chain assumes pivotal significance in the attainment of enduring competitive advantages for the enterprise.
Industry 4.0 is concerned with the general transformation of the manufacturing industry from traditional mechanized production methods to digital and intelligent production methods [136]. The purpose of this study is to examine the mutual impact of digital transformation and supply chain relationships on the competitive advantage of manufacturers in the service-based manufacturing sector. Digital transformation is viewed as a moderating variable that encompasses the process by which companies leverage digital technologies to transform supply chain collaboration, increase operational efficiency, and explore new business models. In contrast, supply chain relationships are considered an independent variable, encompassing the close collaboration and interaction between manufacturers and their supply chain partners.
The effect of digital transformation mitigates the negative impact of supply chain concentration on manufacturers’ competitive advantage. This study selects the packaging and printing industry as the object of study primarily because of the widespread adoption of Industry 4.0 components such as cloud computing, Big Data, and the Internet of Things (IoT) [137,138], which have facilitated the establishment of a service-oriented manufacturing paradigm. These technologies play a regulatory role in key partnerships [33], critical activities, and customer relationships within the supply chain, improving business performance and advancing sustainable development goals [139,140].

8.2. Conclusions

The unique characteristics of supply chain partnerships shape the trajectory of firms by having a dual impact on their performance and risk. With the rise of digital transformation, this impact is likely to become even more pronounced, as restructuring of supply chains in digital environments may trigger drastic changes in the balance of power. Therefore, more empirical studies are especially urgent to reveal the potential impacts of digital transformation on supply chain partnerships.
Using a two-way fixed effects model, this study examines the impact of supply chain concentration on the competitive advantage of Chinese A-share listed packaging and printing companies from 2012 to 2021. The study also examines the role of digital transformation in adjusting the negative impact of supply chain relationships on firms’ competitive advantage from the perspective of power checks and balances.
Firstly, this research reveals that in the traditional supply chain profit-sharing model, the rising costs of procurement and consumption depress corporate profits. Over-concentration of the supply chain can lead to economic disadvantages in today’s service-oriented markets [128]. This can lead to manufacturers abusing their power in the supply chain, exacerbating the potential economic consequences. In addition, manufacturers may be asked by suppliers and customers to lower their prices or improve their services, which could impact profit margins and long-term competitive advantage.
Secondly, this research shows that the push towards of digital transformation mitigates the negative impact of supply chain concentration on manufacturers’ competitive advantage.
For industry development dilemmas, companies can use digital transformation as an entry point to develop effective business processes and realize the potential benefits of data. First, for the pain point of supply chain disruption, by centralizing digital technology into the process, packaging and printing enterprises can establish a collaborative supply chain management system with upstream and downstream enterprises, help suppliers learn inventory management through shared orders, provide customers with total packaging solutions through multi-level tracking, realize revenue sharing, and play a core enterprise role in terms of business flow, information flow, and capital flow. Second, in response to the pain point of low industrial concentration, small packaging and printing enterprises can implement a merger and acquisition strategy on the premise of complementary advantages to increase efficiency and competitiveness while expanding the scale of the enterprise and promoting intensive development of the industry. Service manufacturing companies can achieve smart and low-energy development, stay away from homogeneous competition, and improve their competitive advantage by adopting digital transformation technology tools such as smart manufacturing, flexible production, and collaborative planning with entities upstream and downstream in the supply chain to develop information, capital, and commodity flows.
Thirdly, the results of the heterogeneity test are as follows: 1. The adverse effects of supply chain concentration on the competitive advantage of non-state-owned firms are more pronounced. 2. Firms that hold separate leadership positions may face greater challenges in maintaining competitive advantage. 3. Larger companies tend to have a greater capacity to invest in technology and innovation. The heterogeneity analyses extend and discuss these findings, enriching the original contribution.
In conclusion, the results of this study underscore that companies in the service industry should recognize the opportunities presented by digital transformation and, on this basis, actively strengthen their collaborative relationships with supply chain partners. By effectively using digital technologies and optimizing supply chain management, companies are likely to further enhance their competitive advantages, consolidate their market position, and achieve sustainable development goals. In addition, our research revealed significant heterogeneity among groups of companies in terms of ownership type, dual management roles, and company size. This highlights the importance of considering these factors when developing strategies to leverage digital transformation and improve supply chain collaboration.
This study contributes to a better understanding of supply chain management issues in the service-oriented industry, especially in emerging economies. China is one of the largest economies in the world, and the future development of China’s manufacturing industry will focus on efforts to promote a shift from “production-based manufacturing” to “service-oriented manufacturing”. From a global perspective, the combination of digitalization and supply chain management offers a new path for supply chain power balance, synergistic development between enterprises, and cost reduction. As the global market continues to change, this shift will have long-term implications for the future business landscape. Only those companies that can flexibly adjust their supply chains and adapt to the changes will prevail in this new era.

8.3. Limitations and Future Research Directions

To achieve service-oriented business development, the company and its upstream and downstream affiliates need to make an identity adjustment from a hierarchical relationship to a partnership, i.e., from a profit-shifting system with checks and balances based on power and bargaining power to a multi-actor partnership based on the premise of trust and responsibility. A stakeholder network with a broader base of cooperation in the supply chain is established to replace the original narrow ties with only key actors in upstream and downstream firms. Significant theoretical advancements in the area of corporate competitive advantage have been made through the transition from a hierarchical relationship to a partnership and the creation of a stakeholder network with a wider base of collaboration in the supply chain. This supports the notion that an organization’s success is influenced not only by its internal resources but also by the resources and competencies of its external stakeholders, including suppliers and consumers. The resource dependence theory, which emphasizes the significance of outside resources in determining a company’s competitive advantage, is consistent with this strategy. Additionally, this partnership-based strategy is consistent with the stakeholder theory, which emphasizes the significance of taking all stakeholders’ interests into account when making company decisions.
First, this study focuses on the manufacturing service industry as the main object of research, but our vision is to ensure that the theoretical insights and management knowledge gained are generalizable and can provide targeted guidance and lessons for other industries. Secondly, it is worth noting that the sample used is from the packaging and printing industry, and although to some extent this represents a typical case, there are unavoidable limitations. We should acknowledge this and be cautious in interpreting the results. Third, the measurement of digital change in this study relies on the keyword thesaurus created by researchers. While this provides an objective basis for the study to some extent, it also means that the perspective of the study is limited by the time frame and coverage of this keyword thesaurus. Future research needs to further expand the measurement of digital transformation to more comprehensively and accurately capture the essence of the digital transformation of enterprises. At the same time, in-depth studies should be conducted in different industry contexts to verify whether the impact of digital transformation on companies’ competitive strategy holds up in different environments.
In summary, despite some limitations of this study, these limitations do not diminish its contribution to theory and practice. By fully acknowledging and judiciously dealing with the limitations of the study, future research can arrive at richer and deeper insights by expanding the sample size and measurement methodology and by expanding the research in different industry contexts.

Author Contributions

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

Funding

National Natural Science Foundation of China: 71872028; University-Industry Collaborative Education Program: 202102477004.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors without undue reservation.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Fang, H.; Jiang, C.; Hussain, T.; Zhang, X.; Huo, Q. Input Digitization of the Manufacturing Industry and Carbon Emission Intensity Based on Testing the World and Developing Countries. Int. J. Environ. Res. Public. Health 2022, 19, 12855. [Google Scholar] [CrossRef]
  2. Chen, P.; Kim, S. The Impact of Digital Transformation on Innovation Performance—The Mediating Role of Innovation Factors. Heliyon 2023, 9, e13916. [Google Scholar] [CrossRef] [PubMed]
  3. Li, L.; Mao, C. Big Data Supported PSS Evaluation Decision in Service-Oriented Manufacturing. IEEE Access 2020, 8, 154663–154670. [Google Scholar] [CrossRef]
  4. Wang, S.; Su, H.; Hou, Q. Evolutionary Game Study on Multi-Agent Value Co-Creation of Service-Oriented Digital Transformation in the Construction Industry. PLoS ONE 2023, 18, e0285697. [Google Scholar] [CrossRef] [PubMed]
  5. Gao, J.; Yao, Y.; Zhu, V.C.Y.; Sun, L.; Lin, L. Service-Oriented Manufacturing: A New Product Pattern and Manufacturing Paradigm. J. Intell. Manuf. 2011, 22, 435–446. [Google Scholar] [CrossRef]
  6. Choudhury, T.T.; Paul, S.K.; Rahman, H.F.; Jia, Z.; Shukla, N. A Systematic Literature Review on the Service Supply Chain: Research Agenda and Future Research Directions. Prod. Plan. Control 2020, 31, 1363–1384. [Google Scholar] [CrossRef]
  7. Espina-Romero, L.C.; Guerrero-Alcedo, J.M.; Ossio, C. 7 Topics That Business Ecosystems Navigate: Assessment of Scientific Activity and Future Research Agenda. Heliyon 2023, 9, e16667. [Google Scholar] [CrossRef]
  8. Awan, F.H.; Dunnan, L.; Jamil, K.; Mustafa, S.; Atif, M.; Gul, R.F.; Guangyu, Q. Mediating Role of Green Supply Chain Management Between Lean Manufacturing Practices and Sustainable Performance. Front. Psychol. 2022, 12, 810504. [Google Scholar] [CrossRef]
  9. Min, S.; Zacharia, Z.G.; Smith, C.D. Defining Supply Chain Management: In the Past, Present, and Future. J. Bus. Logist. 2019, 40, 44–55. [Google Scholar] [CrossRef]
  10. Eksoz, C.; Mansouri, S.A.; Bourlakis, M.; Önkal, D. Judgmental Adjustments through Supply Integration for Strategic Partnerships in Food Chains. Omega 2019, 87, 20–33. [Google Scholar] [CrossRef]
  11. Huy, Q.T.; Hara, Y. Supply Chain Risk Management: Manufacturing- and Service-Oriented Firms. J. Manuf. Technol. Manag. 2018, 29, 218–239. [Google Scholar] [CrossRef]
  12. Shin, N.; Park, S.; Park, S. Partnership-Based Supply Chain Collaboration: Impact on Commitment, Innovation, and Firm Performance. Sustainability 2019, 11, 449. [Google Scholar] [CrossRef]
  13. Huang, Y.; Han, W.; Macbeth, D.K. The Complexity of Collaboration in Supply Chain Networks An Exploratory Study of the Chinese Automotive Sector. SCM 2020, 25, 393–410. [Google Scholar] [CrossRef]
  14. Kwak, D.-W.; Seo, Y.-J.; Mason, R. Investigating the Relationship between Supply Chain Innovation, Risk Management Capabilities and Competitive Advantage in Global Supply Chains. Int. J. Oper. Prod. Manag. 2018, 38, 2–21. [Google Scholar] [CrossRef]
  15. Hui, K.W.; Liang, C.; Yeung, P.E. The Effect of Major Customer Concentration on Firm Profitability: Competitive or Collaborative? Rev. Acc. Stud. 2019, 24, 189–229. [Google Scholar] [CrossRef]
  16. Afraz, M.F.; Bhatti, S.H.; Ferraris, A.; Couturier, J. The Impact of Supply Chain Innovation on Competitive Advantage in the Construction Industry: Evidence from a Moderated Multi-Mediation Model. Technol. Forecast. Soc. Chang. 2021, 162, 120370. [Google Scholar] [CrossRef]
  17. Li, Y.; Ding, H.; Li, T. Path Research on the Value Chain Reconfiguration of Manufacturing Enterprises Under Digital Transformation—A Case Study of B Company. Front. Psychol. 2022, 13, 887391. [Google Scholar] [CrossRef]
  18. Yin, W. Identifying the Pathways through Digital Transformation to Achieve Supply Chain Resilience: An fsQCA Approach. Environ. Sci. Pollut. Res. Int. 2023, 30, 10867–10879. [Google Scholar] [CrossRef]
  19. The Transformation of Supply Chain Collaboration and Design through Industry 4.0. International Journal of Logistics Research and Applications. Available online: https://www.tandfonline.com/doi/abs/10.1080/13675567.2022.2148638 (accessed on 1 August 2023).
  20. Huber, R.; Oberländer, A.M.; Faisst, U.; Röglinger, M. Disentangling Capabilities for Industry 4.0—An Information Systems Capability Perspective. Inf. Syst. Front. 2022, 1–29. [Google Scholar] [CrossRef]
  21. Hole, G.; Hole, A.S.; McFalone-Shaw, I. Digitalization in Pharmaceutical Industry: What to Focus on under the Digital Implementation Process? Int. J. Pharm. X 2021, 3, 100095. [Google Scholar] [CrossRef]
  22. Cruz-Cárdenas, J.; Zabelina, E.; Guadalupe-Lanas, J.; Palacio-Fierro, A.; Ramos-Galarza, C. COVID-19, Consumer Behavior, Technology, and Society: A Literature Review and Bibliometric Analysis. Technol. Forecast. Soc. Chang. 2021, 173, 121179. [Google Scholar] [CrossRef]
  23. Yin, S.; Zhang, N.; Ullah, K.; Gao, S. Enhancing Digital Innovation for the Sustainable Transformation of Manufacturing Industry: A Pressure-State-Response System Framework to Perceptions of Digital Green Innovation and Its Performance for Green and Intelligent Manufacturing. Systems 2022, 10, 72. [Google Scholar] [CrossRef]
  24. Ivanov, D.; Dolgui, A.; Sokolov, B. The Impact of Digital Technology and Industry 4.0 on the Ripple Effect and Supply Chain Risk Analytics. Int. J. Prod. Res. 2019, 57, 829–846. [Google Scholar] [CrossRef]
  25. Binsaeed, R.H.; Grigorescu, A.; Yousaf, Z.; Condrea, E.; Nassani, A.A. Leading Role of Big Data Analytic Capability in Innovation Performance: Role of Organizational Readiness and Digital Orientation. Systems 2023, 11, 284. [Google Scholar] [CrossRef]
  26. Mahmood, T.; Mubarik, M.S. Balancing Innovation and Exploitation in the Fourth Industrial Revolution: Role of Intellectual Capital and Technology Absorptive Capacity. Technol. Forecast. Soc. Chang. 2020, 160, 120248. Available online: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7439089/ (accessed on 3 September 2023). [CrossRef]
  27. Hiba, J.C.; Jentsch, M.; Zink, K.J. Globalization and Working Conditions in International Supply Chains. Z. Arbeitswiss. 2021, 75, 146–154. [Google Scholar] [CrossRef]
  28. Akbari, M.; Kok, S.K.; Hopkins, J.; Frederico, G.F.; Nguyen, H.; Alonso, A.D. The Changing Landscape of Digital Transformation in Supply Chains: Impacts of Industry 4.0 in Vietnam. Int. J. Logist. Manag. 2023. [Google Scholar] [CrossRef]
  29. 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]
  30. Shi, Y.; Venkatesh, V.G.; Venkatesh, M.; Fosso Wamba, S.; Wang, B. Guest Editorial: Digital Transformation in Supply Chains: Challenges, Strategies and Implementations. Int. J. Phys. Distrib. Logist. Manag. 2023, 53, 381–386. [Google Scholar] [CrossRef]
  31. Zhang, K.; Feng, L.; Wang, J.; Qin, G.; Li, H. Start-Up’s Road to Disruptive Innovation in the Digital Era: The Interplay Between Dynamic Capabilities and Business Model Innovation. Front. Psychol. 2022, 13, 925277. [Google Scholar] [CrossRef]
  32. Salwin, M.; Kraslawski, A.; Lipiak, J.; Gołębiewski, D.; Andrzejewski, M. Product-Service System Business Model for Printing Houses. J. Clean. Prod. 2020, 274, 122939. [Google Scholar] [CrossRef]
  33. Kluczek, A.; Gladysz, B.; Buczacki, A.; Krystosiak, K.; Ejsmont, K.; Palmer, E. Aligning Sustainable Development Goals with Industry 4.0 for the Design of Business Model for Printing and Packaging Companies. Packag. Technol. Sci. 2023, 36, 307–325. [Google Scholar] [CrossRef]
  34. Vendrell-Herrero, F.; Bustinza, O.F.; Parry, G.; Georgantzis, N. Servitization, Digitization and Supply Chain Interdependency. Ind. Mark. Manag. 2017, 60, 69–81. [Google Scholar] [CrossRef]
  35. Hofmann, E.; Locker, A. Value-Based Performance Measurement in Supply Chains: A Case Study from the Packaging Industry. Prod. Plan. Control 2009, 20, 68–81. [Google Scholar] [CrossRef]
  36. Collier, Z.A.; Sarkis, J. The Zero Trust Supply Chain: Managing Supply Chain Risk in the Absence of Trust. Int. J. Prod. Res. 2021, 59, 3430–3445. [Google Scholar] [CrossRef]
  37. Bui, T.-D.; Tsai, F.M.; Tseng, M.-L.; Tan, R.R.; Yu, K.D.S.; Lim, M.K. Sustainable Supply Chain Management towards Disruption and Organizational Ambidexterity: A Data Driven Analysis. Sustain. Prod. Consum. 2021, 26, 373–410. [Google Scholar] [CrossRef]
  38. Zhang, G.; Yang, Y.; Yang, G. Smart Supply Chain Management in Industry 4.0: The Review, Research Agenda and Strategies in North America. Ann. Oper. Res. 2023, 322, 1075–1117. [Google Scholar] [CrossRef]
  39. Department of Industrial Engineering, Tomas Bata University, Czech Republic; Nwaiwu, F. Analysis of Emerging Business Models of Companies in the Era of the Digital Economy. In Proceedings of the How to Cope With Disrupted Times; Association of Economists and Managers of the Balkans: Belgrade, Serbia; Faculty of Management Koper: Capodistria, Slovenia; Doba Business School: Maribor, Slovenia; Integrated Business Faculty: Skopje, Macedonia; Faculty of Management: Zajecar, Serbia, 2018; p. 988. [Google Scholar]
  40. Zhang, Q.; Yang, M.; Lv, S. Corporate Digital Transformation and Green Innovation: A Quasi-Nature Experiment from Integration of Informatization and Industrialization in China. Int. J. Environ. Res. Public. Health 2022, 19, 13606. [Google Scholar] [CrossRef]
  41. Cuthbertson, R.W.; Furseth, P.I. Digital Services and Competitive Advantage: Strengthening the Links between RBV, KBV, and Innovation. J. Bus. Res. 2022, 152, 168–176. [Google Scholar] [CrossRef]
  42. Leão, P.; da Silva, M.M. Impacts of Digital Transformation on Firms’ Competitive Advantages: A Systematic Literature Review. Strateg. Chang. 2021, 30, 421–441. [Google Scholar] [CrossRef]
  43. Sun, S.; Guo, L. Digital Transformation, Green Innovation and the Solow Productivity Paradox. PLoS ONE 2022, 17, e0270928. [Google Scholar] [CrossRef] [PubMed]
  44. Ding, B. Pharma Industry 4.0: Literature Review and Research Opportunities in Sustainable Pharmaceutical Supply Chains. Process Saf. Environ. Prot. 2018, 119, 115–130. [Google Scholar] [CrossRef]
  45. De Vass, T.; Shee, H.; Miah, S.J. The Effect of “Internet of Things” on Supply Chain Integration and Performance: An Organisational Capability Perspective. Australas. J. Inf. Syst. 2018, 22, 1–29. [Google Scholar] [CrossRef]
  46. Xin, Y.; Ojanen, V.; Huiskonen, J. Empirical Studies on Product-Service Systems—A Systematic Literature Review. Procedia CIRP 2017, 64, 399–404. [Google Scholar] [CrossRef]
  47. Vandermerwe, S.; Rada, J. Servitization of Business: Adding Value by Adding Services. Eur. Manag. J. 1988, 6, 314–324. [Google Scholar] [CrossRef]
  48. Baines, T.; Ziaee Bigdeli, A.; Bustinza, O.F.; Shi, V.G.; Baldwin, J.; Ridgway, K. Servitization: Revisiting the State-of-the-Art and Research Priorities. Int. J. Oper. Prod. Manag. 2017, 37, 256–278. [Google Scholar] [CrossRef]
  49. Oliva, R.; Kallenberg, R. Managing the Transition from Products to Services. Int. J. Serv. Ind. Manag. 2003, 14, 160–172. [Google Scholar] [CrossRef]
  50. Kastalli, I.V.; Van Looy, B. Servitization: Disentangling the Impact of Service Business Model Innovation on Manufacturing Firm Performance. J. Oper. Manag. 2013, 31, 169–180. [Google Scholar] [CrossRef]
  51. Kowalkowski, C.; Gebauer, H.; Kamp, B.; Parry, G. Servitization and Deservitization: Overview, Concepts, and Definitions. Ind. Mark. Manag. 2017, 60, 4–10. [Google Scholar] [CrossRef]
  52. Reim, W.; Sjödin, D.R.; Parida, V. Servitization of Global Service Network Actors: A Contingency Framework for Matching Challenges and Strategies in Service Transition. J. Bus. Res. 2019, 104, 461–471. [Google Scholar] [CrossRef]
  53. Hou, J.; Neely, A. Investigating Risks of Outcome-Based Service Contracts from a Provider’s Perspective. Int. J. Prod. Res. 2018, 56, 2103–2115. [Google Scholar] [CrossRef]
  54. Niu, Y.; Jiang, Z. Servitization in Cross-Border Relationships: Investigating the Effects of Global Supply Chain Dependence on the Servitization Level of the Manufacturers. Int. J. Oper. Prod. Manag. 2023. [Google Scholar] [CrossRef]
  55. Shah, S.A.; Jajja, M.S.; Chatha, K.A.; Farooq, S. Servitization and Supply Chain Integration: An Empirical Analysis. Int. J. Prod. Econ. 2020, 229, 107765. [Google Scholar] [CrossRef]
  56. Lafuente, E.; Vaillant, Y.; Vendrell-Herrero, F. Editorial: Product-Service Innovation Systems—Opening-up Servitization-Based Innovation to Manufacturing Industry. Technovation 2023, 120, 102665. [Google Scholar] [CrossRef]
  57. Li, H.; Yang, Y.; Singh, P.; Sun, H.; Tian, Y. Servitization and Performance: The Moderating Effect of Supply Chain Integration. Prod. Plan. Control 2023, 34, 242–259. [Google Scholar] [CrossRef]
  58. Zhou, D.; Yan, T.; Zhao, L.; Guo, J. Performance Implications of Servitization: Does a Manufacturer’s Service Supply Network Matter? Int. J. Prod. Econ. 2020, 219, 31–42. [Google Scholar] [CrossRef]
  59. Morgan, T.; Anokhin, S.A.; Wincent, J. New Service Development by Manufacturing Firms: Effects of Customer Participation under Environmental Contingencies. J. Bus. Res. 2019, 104, 497–505. [Google Scholar] [CrossRef]
  60. Doni, F.; Corvino, A.; Bianchi Martini, S. Servitization and Sustainability Actions. Evidence from European Manufacturing Companies. J. Environ. Manag. 2019, 234, 367–378. [Google Scholar] [CrossRef]
  61. Zhang, J.; Sun, X.; Dong, Y.; Fu, L.; Zhang, Y. The Impact of Servitization on Manufacturing Firms’ Market Power: Empirical Evidence from China. J. Bus. Ind. Mark. 2022, 38, 609–621. [Google Scholar] [CrossRef]
  62. Eloranta, V.; Ardolino, M.; Saccani, N. A Complexity Management Approach to Servitization: The Role of Digital Platforms. Emerald Insight. Available online: https://www.emerald.com/insight/content/doi/10.1108/IJOPM-08-2020-0582/full/html (accessed on 4 September 2023).
  63. Ezzat, O.; Medini, K.; Boucher, X.; Delorme, X. A Clustering Approach for Modularizing Service-Oriented Systems. J. Intell. Manuf. 2022, 33, 719. [Google Scholar] [CrossRef]
  64. Huang, W.; Yang, J.; Wei, Z. How Does Servitization Affect Firm Performance? IEEE Trans. Eng. Manag. 2022, 69, 2871–2881. [Google Scholar] [CrossRef]
  65. Bustinza, O.F.; Opazo-Basaez, M.; Tarba, S. Exploring the Interplay between Smart Manufacturing and KIBS Firms in Configuring Product-Service Innovation Performance. Technovation 2022, 118, 102258. [Google Scholar] [CrossRef]
  66. Culot, G.; Orzes, G.; Sartor, M.; Nassimbeni, G. The Future of Manufacturing: A Delphi-Based Scenario Analysis on Industry 4.0. Available online: https://www.citexs.com/Detail?pmid=32351256 (accessed on 5 September 2023).
  67. Sklyar, A.; Kowalkowski, C.; Tronvoll, B.; Sörhammar, D. Organizing for Digital Servitization: A Service Ecosystem Perspective. J. Bus. Res. 2019, 104, 450–460. [Google Scholar] [CrossRef]
  68. Kamalaldin, A.; Linde, L.; Sjödin, D.; Parida, V. Transforming Provider-Customer Relationships in Digital Servitization: A Relational View on Digitalization. Ind. Mark. Manag. 2020, 89, 306–325. [Google Scholar] [CrossRef]
  69. Simonsson, J.; Agarwal, G. Perception of Value Delivered in Digital Servitization. Ind. Mark. Manag. 2021, 99, 167–174. [Google Scholar] [CrossRef]
  70. Kohtamäki, M.; Parida, V.; Patel, P.C.; Gebauer, H. The Relationship between Digitalization and Servitization: The Role of Servitization in Capturing the Financial Potential of Digitalization. Technol. Forecast. Soc. Chang. 2020, 151, 119804. [Google Scholar] [CrossRef]
  71. Zhou, D.; Yan, T.; Dai, W.; Feng, J. Disentangling the Interactions within and between Servitization and Digitalization Strategies: A Service-Dominant Logic. Int. J. Prod. Econ. 2021, 238, 108175. [Google Scholar] [CrossRef]
  72. Abou-foul, M.; Ruiz-Alba, J.L.; Soares, A. The Impact of Digitalization and Servitization on the Financial Performance of a Firm: An Empirical Analysis. Prod. Plan. Control 2021, 32, 975–989. [Google Scholar] [CrossRef]
  73. Gomes, E.; Lehman, D.W.; Vendrell-Herrero, F.; Bustinza, O.F. A History-Based Framework of Servitization and Deservitization. Int. J. Oper. Prod. Manag. 2021, 41, 723–745. [Google Scholar] [CrossRef]
  74. Naik, P.; Schroeder, A.; Kapoor, K.K.; Ziaee Bigdeli, A.; Baines, T. Behind the Scenes of Digital Servitization: Actualising IoT-Enabled Affordances. Ind. Mark. Manag. 2020, 89, 232–244. [Google Scholar] [CrossRef]
  75. Chen, Y.; Visnjic, I.; Parida, V.; Zhang, Z. On the Road to Digital Servitization—The (Dis)Continuous Interplay between Business Model and Digital Technology. Int. J. Oper. Prod. Manag. 2021, 41, 694–722. [Google Scholar] [CrossRef]
  76. Arifin, N.A.M.; Saman, M.Z.M.; Sharif, S.; Ngadiman, N.H.A. Sustainability Implications of Additive Manufacturing. In Human-Centered Technology for a Better Tomorrow; Hassan, M.H.A., Ahmad Manap, Z., Baharom, M.Z., Johari, N.H., Jamaludin, U.K., Jalil, M.H., Mat Sahat, I., Omar, M.N., Eds.; Lecture Notes in Mechanical Engineering; Springer: Singapore, 2022; pp. 441–452. ISBN 9789811641145. [Google Scholar]
  77. Gladysz, B.; Krystosiak, K.; Ejsmont, K.; Kluczek, A.; Buczacki, A. Sustainable Printing 4.0—Insights from a Polish Survey. Sustainability 2021, 13, 10916. [Google Scholar] [CrossRef]
  78. Ukobitz, D. Organizational Adoption of 3D Printing Technology: A Semisystematic Literature Review. J. Manuf. Technol. Manag. 2020, 32, 48–74. [Google Scholar] [CrossRef]
  79. Salwin, M.; Santarek, K.; Kraslawski, A.; Lipiak, J. Product-Service System: A New Opportunity for the Printing Industry. In Proceedings of the Advanced Manufacturing Processes II; Tonkonogyi, V., Ivanov, V., Trojanowska, J., Oborskyi, G., Grabchenko, A., Pavlenko, I., Edl, M., Kuric, I., Dasic, P., Eds.; Springer International Publishing: Cham, Switzerland, 2021; pp. 83–95. [Google Scholar]
  80. Woodson, T.S.; Alcantara, J.T.; do Nascimento, M.S. Is 3D Printing an Inclusive Innovation?: An Examination of 3D Printing in Brazil. Technovation 2019, 80, 54–62. [Google Scholar] [CrossRef]
  81. Huang, Z.; Shen, Y.; Li, J.; Fey, M.; Brecher, C. A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics. Sensors 2021, 21, 6340. [Google Scholar] [CrossRef]
  82. Marić, J. Exploring 3D Printing Technology in the Context of Product-Service Innovation: Case Study of a Business Venture in South of France. IJBE 2020, 11, 222. [Google Scholar] [CrossRef]
  83. Villalba-Diez, J.; Schmidt, D.; Gevers, R.; Ordieres-Meré, J.; Buchwitz, M.; Wellbrock, W. Deep Learning for Industrial Computer Vision Quality Control in the Printing Industry 4.0. Sensors 2019, 19, 3987. [Google Scholar] [CrossRef]
  84. Shabbir, M.; Sulaiman, M.A.B.A.; Al-Kumaim, N.H.; Mahmood, A.; Abbas, M. Green Marketing Approaches and Their Impact on Consumer Behavior towards the Environment—A Study from the UAE. Sustainability 2020, 12, 8977. [Google Scholar] [CrossRef]
  85. Wandosell, G.; Parra-Meroño, M.C.; Alcayde, A.; Baños, R. Green Packaging from Consumer and Business Perspectives. Sustainability 2021, 13, 1356. [Google Scholar] [CrossRef]
  86. Spruit, D.; Almenar, E. First Market Study in E-Commerce Food Packaging: Resources, Performance, and Trends. Food Packag. Shelf Life 2021, 29, 100698. [Google Scholar] [CrossRef]
  87. Su, Y.; Duan, H.; Wang, Z.; Song, G.; Kang, P.; Chen, D. Characterizing the Environmental Impact of Packaging Materials for Express Delivery via Life Cycle Assessment. J. Clean. Prod. 2020, 274, 122961. [Google Scholar] [CrossRef]
  88. Zeng, T.; Deschênes, J.; Durif, F. Eco-Design Packaging: An Epistemological Analysis and Transformative Research Agenda. J. Clean. Prod. 2020, 276, 123361. [Google Scholar] [CrossRef]
  89. Baykina, R.N.; Lisovsky, A.L.; Yussuf, A.A. Assessment of a Sustainable Development Potential of Printing Companies in the Digital Economy Environment. In Inclusive Development of Society; CRC Press: Boca Raton, FL, USA, 2020; Available online: https://sc.panda321.com/scholar?hl=zh-CN&as_sdt=0%2C5&q=+Assessment+of+a+sustainable+development+potential+of+printing+companies+in+the+digital+economy+environment.+In%3A+Inclusive+development+of+society.+CRC+Press%3B+2020.+&btnG= (accessed on 9 August 2023).
  90. Cheng, L.T.W.; Poon, J.S.C.; Tang, S.; Wang, J.W. Does Supplier Concentration Matter to Investors during the COVID-19 Crisis: Evidence from China? Financ. Innov. 2022, 8, 85. [Google Scholar] [CrossRef] [PubMed]
  91. Kreye, M.E. When Servitized Manufacturers Globalise: Becoming a Provider of Global Services. Int. J. Oper. Prod. Manag. 2022, 42, 1521–1543. [Google Scholar] [CrossRef]
  92. Vargas, J.; Calvo, R. Joint Optimization of Process Flow and Scheduling in Service-Oriented Manufacturing Systems. Materials 2018, 11, 1559. [Google Scholar] [CrossRef]
  93. Jamaludin, M. The influence of supply chain management on competitive advantage and company performance. Uncertain. Supply Chain. Manag. 2021, 9, 696–704. [Google Scholar] [CrossRef]
  94. Adebanjo, D.; Teh, P.-L.; Ahmed, P.K. The Impact of Supply Chain Relationships and Integration on Innovative Capabilities and Manufacturing Performance: The Perspective of Rapidly Developing Countries. Int. J. Prod. Res. 2018, 56, 1708–1721. [Google Scholar] [CrossRef]
  95. Du, C.; Zhang, Q. Supply Network Position, Digital Transformation and Innovation Performance: Evidence from Listed Chinese Manufacturing Firms. PLoS ONE 2022, 17, e0279133. [Google Scholar] [CrossRef]
  96. Jiang, S.; Yeung, A.C.L.; Han, Z.; Huo, B. The Effect of Customer and Supplier Concentrations on Firm Resilience during the COVID-19 Pandemic: Resource Dependence and Power Balancing. J. Oper. Manag. 2023, 69, 497–518. [Google Scholar] [CrossRef]
  97. Frank, A.G.; Dalenogare, L.S.; Ayala, N.F. Industry 4.0 Technologies: Implementation Patterns in Manufacturing Companies. Int. J. Prod. Econ. 2019, 210, 15–26. [Google Scholar] [CrossRef]
  98. Adamik, A.; Nowicki, M. Preparedness of Companies for Digital Transformation and Creating a Competitive Advantage in the Age of Industry 4.0. Proc. Int. Conf. Bus. Excell. 2018, 12, 10–24. [Google Scholar] [CrossRef]
  99. He, X.; Hu, W.; Li, W.; Hu, R. Digital Transformation, Technological Innovation, and Operational Resilience of Port Firms in Case of Supply Chain Disruption. Mar. Pollut. Bull. 2023, 190, 114811. [Google Scholar] [CrossRef] [PubMed]
  100. Libai, B.; Bart, Y.; Gensler, S.; Hofacker, C.F.; Kaplan, A.; Kötterheinrich, K.; Kroll, E.B. Brave New World? On AI and the Management of Customer Relationships. J. Interact. Mark. 2020, 51, 44–56. [Google Scholar] [CrossRef]
  101. Rêgo, B.S.; Jayantilal, S.; Ferreira, J.J.; Carayannis, E.G. Digital Transformation and Strategic Management: A Systematic Review of the Literature. J. Knowl. Econ. 2022, 13, 3195–3222. [Google Scholar] [CrossRef]
  102. Ardolino, M.; Rapaccini, M.; Saccani, N.; Gaiardelli, P.; Crespi, G.; Ruggeri, C. The Role of Digital Technologies for the Service Transformation of Industrial Companies. Int. J. Prod. Res. 2018, 56, 2116–2132. [Google Scholar] [CrossRef]
  103. Tao, F.; Qi, Q. New IT Driven Service-Oriented Smart Manufacturing: Framework and Characteristics. IEEE Trans. Syst. Man Cybern Syst. 2019, 49, 81–91. [Google Scholar] [CrossRef]
  104. 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]
  105. Dyduch, W.; Chudziński, P.; Cyfert, S.; Zastempowski, M. Dynamic Capabilities, Value Creation and Value Capture: Evidence from SMEs under Covid-19 Lockdown in Poland. PLoS ONE 2021, 16, e0252423. [Google Scholar] [CrossRef]
  106. Su, X.; Mou, C.; Zhou, S. Institutional Environment, Technological Innovation Capability and Service-Oriented Transformation. PLoS ONE 2023, 18, e0281403. [Google Scholar] [CrossRef]
  107. Porter, M. The Five Competitive Forces That Shape Strategy. Harv. Bus. Rev. 2008, 86, 78. [Google Scholar]
  108. Wu, F.; Hu, H.; Lin, H.; Ren, X. Enterprise Digital Transformation and Capital Market Performance:Empirical Evidence from Stock Liquidity. Manag. World 2021, 37, 130–144. [Google Scholar] [CrossRef]
  109. Su, J.; Wei, Y.; Wang, S.; Liu, Q. The Impact of Digital Transformation on the Total Factor Productivity of Heavily Polluting Enterprises. Sci. Rep. 2023, 13, 6386. [Google Scholar] [CrossRef] [PubMed]
  110. Zhu, Z.; Ning, S. Corporate Digital Transformation and Strategic Investments of Construction Industry in China. Heliyon 2023, 9, e17879. [Google Scholar] [CrossRef] [PubMed]
  111. Wu, K.; Fu, Y.; Kong, D. Does the Digital Transformation of Enterprises Affect Stock Price Crash Risk? Financ. Res. Lett. 2022, 48, 102888. [Google Scholar] [CrossRef]
  112. Tian, G.; Li, B.; Cheng, Y. Does Digital Transformation Matter for Corporate Risk-Taking? Financ. Res. Lett. 2022, 49, 103107. [Google Scholar] [CrossRef]
  113. Newbert, S.L. Value, Rareness, Competitive Advantage, and Performance: A Conceptual-Level Empirical Investigation of the Resource-Based View of the Firm. Strat. Mgmt. J. 2008, 29, 745–768. [Google Scholar] [CrossRef]
  114. Du, L.; Wang, X.; Peng, J.; Jiang, G.; Deng, S. The Impact of Environmental Information Disclosure Quality on Green Innovation of High-Polluting Enterprises. Front. Psychol. 2022, 13, 1069354. [Google Scholar] [CrossRef]
  115. Subramaniam, V.; Wasiuzzaman, S. Geographical Diversification, Firm Size and Profitability in Malaysia: A Quantile Regression Approach. Heliyon 2019, 5, e02664. [Google Scholar] [CrossRef]
  116. Beracha, E.; Feng, Z.; Hardin, W.G. REIT Operational Efficiency: Performance, Risk, and Return. J. Real Estate Financ. Econ. 2019, 58, 408–437. [Google Scholar] [CrossRef]
  117. Eluyela, D.F.; Akintimehin, O.O.; Okere, W.; Ozordi, E.; Osuma, G.O.; Ilogho, S.O.; Oladipo, O.A. Datasets for Board Meeting Frequency and Financial Performance of Nigerian Deposit Money Banks. Data Brief 2018, 19, 1852–1855. [Google Scholar] [CrossRef]
  118. Gao, K.; Wang, L.; Liu, T.; Zhao, H. Management Executive Power and Corporate Green Innovation—Empirical Evidence from China’s State-Owned Manufacturing Sector. Technol. Soc. 2022, 70, 102043. [Google Scholar] [CrossRef]
  119. Wu, J.; Xia, Q.; Li, Z. Green Innovation and Enterprise Green Total Factor Productivity at a Micro Level: A Perspective of Technical Distance. J. Clean. Prod. 2022, 344, 131070. [Google Scholar] [CrossRef]
  120. Wu, L.; Zhang, Z. Impact and Threshold Effect of Internet Technology Upgrade on Forestry Green Total Factor Productivity: Evidence from China. J. Clean. Prod. 2020, 271, 122657. [Google Scholar] [CrossRef]
  121. Serafeim, G. Public Sentiment and the Price of Corporate Sustainability. Financ. Anal. J. 2020, 76, 26–46. [Google Scholar] [CrossRef]
  122. Arayssi, M.; Jizi, M.I. Does Corporate Governance Spillover Firm Performance? A Study of Valuation of MENA Companies. Soc. Responsib. J. 2019, 15, 597–620. [Google Scholar] [CrossRef]
  123. Wan Mohammad, W.M.; Wasiuzzaman, S. Effect of Audit Committee Independence, Board Ethnicity and Family Ownership on Earnings Management in Malaysia. J. Account. Emerg. Econ. 2019, 10, 74–99. [Google Scholar] [CrossRef]
  124. Nguyen Trong, N.; Nguyen, C.T. Firm Performance: The Moderation Impact of Debt and Dividend Policies on Overinvestment. J. Asian Bus. Econ. Stud. 2020, 28, 47–63. [Google Scholar] [CrossRef]
  125. Will Environmental Information Disclosure Affect Bank Credit Decisions and Corporate Debt Financing Costs? Evidence from China’s Heavily Polluting Industries. Available online: https://www.researchsquare.com (accessed on 11 August 2023).
  126. Qiang, O.; Tian-tian, W.; Ying, D.; Zhu-ping, L.; Jahanger, A. The Impact of Environmental Regulations on Export Trade at Provincial Level in China: Evidence from Panel Quantile Regression. Environ. Sci. Pollut. Res. Int. 2022, 29, 24098–24111. [Google Scholar] [CrossRef]
  127. Zhu, Q.; Yuan, F.; Wang, C.; Luan, D.; Wang, H. The Impact of Corporate Violations on Charitable Donation Behavior. Front. Psychol. 2023, 14, 1121381. [Google Scholar] [CrossRef]
  128. He, H.; Zuo, Z. Supply Chain Concentration and Enterprise Financialization: Evidence from Listed Companies in China’s Manufacturing Industry. PLoS ONE 2023, 18, e0285308. [Google Scholar] [CrossRef]
  129. Siddiqui, F.; YuSheng, K.; Tajeddini, K. The Role of Corporate Governance and Reputation in the Disclosure of Corporate Social Responsibility and Firm Performance. Heliyon 2023, 9, e16055. [Google Scholar] [CrossRef] [PubMed]
  130. Hassan, M.K.; Houston, R.; Karim, M.S.; Sabit, A. CEO Duality and Firm Performance during the 2020 Coronavirus Outbreak. J. Econ. Asymmetries 2023, 27, e00278. [Google Scholar] [CrossRef] [PubMed]
  131. Das, G.; Li, S.; Tunio, R.A.; Jamali, R.H.; Ullah, I.; Fernando, K.W.T.M. The Implementation of Green Supply Chain Management (GSCM) and Environmental Management System (EMS) Practices and Its Impact on Market Competitiveness during COVID-19. Environ. Sci. Pollut. Res. Int. 2023, 30, 68387–68402. [Google Scholar] [CrossRef] [PubMed]
  132. Li, Z.; Zhang, Y. CEO Overconfidence and Corporate Innovation Outcomes: Evidence From China. Front. Psychol. 2022, 13, 760102. [Google Scholar] [CrossRef]
  133. Noman, A.H.M.; Gee, C.S.; Isa, C.R. Does Competition Improve Financial Stability of the Banking Sector in ASEAN Countries? An Empirical Analysis. PLoS ONE 2017, 12, e0176546. [Google Scholar] [CrossRef]
  134. Masi, A.; Pero, M.; Abdelkafi, N. Supply Chain Antecedents of Servitization: A Study in ETO Machinery Companies. Int. J. Prod. Econ. 2023, 258, 108808. [Google Scholar] [CrossRef]
  135. Zhong, W.; Ma, Z.; Tong, T.W.; Zhang, Y.; Xie, L. Customer Concentration, Executive Attention, and Firm Search Behavior. Acad. Manag. J. 2021, 64, 1625–1647. [Google Scholar] [CrossRef]
  136. Qader, G.; Junaid, M.; Abbas, Q.; Mubarik, M.S. Industry 4.0 Enables Supply Chain Resilience and Supply Chain Performance. Technol. Forecast. Soc. Chang. 2022, 185, 122026. [Google Scholar] [CrossRef]
  137. Cui, J.; Ren, L.; Mai, J.; Zheng, P.; Zhang, L. 3D Printing in the Context of Cloud Manufacturing. Robot. Comput.-Integr. Manuf. 2022, 74, 102256. [Google Scholar] [CrossRef]
  138. Gandolfo, A.; Lupi, L. Circular Economy, the Transition of an Incumbent Focal Firm: How to Successfully Reconcile Environmental and Economic Sustainability? Bus. Strategy Environ. 2021, 30, 3297–3308. [Google Scholar] [CrossRef]
  139. Sachs, J.D.; Schmidt-Traub, G.; Mazzucato, M.; Messner, D.; Nakicenovic, N.; Rockström, J. Six Transformations to Achieve the Sustainable Development Goals. Nat. Sustain. 2019, 2, 805–814. [Google Scholar] [CrossRef]
  140. Hák, T.; Janoušková, S.; Moldan, B. Sustainable Development Goals: A Need for Relevant Indicators. Ecol. Indic. 2016, 60, 565–573. [Google Scholar] [CrossRef]
Figure 1. Research model.
Figure 1. Research model.
Systems 11 00486 g001
Table 1. Existing research on servitization of the manufacturing industry.
Table 1. Existing research on servitization of the manufacturing industry.
Research AreaKey ConceptsRepresentative Literature
DefinitionThe service elements, increasing manufacturers’ competitive edge, moving from a product-centric to a service-centric business model and logic, shifting from traditional products and basic services to offering advanced services.(Vandermerwe and Rada, 1988 [47]; Baines et al., 2017 [48]; Kowalkowski et al., 2017 [51]; Reim et al., 2019 [52])
Servitization and manufacturing benefitsMore attractive revenue models, a new way to revitalize businesses, enhanced supply chain integration, promote service co-creation, advanced services improving profitability, increase the financial return.(Hou and Neely, 2018 [53]; Yimeng Niu and Zhibin Jiang, 2023 [54]; Shah et al., 2020 [55]; Lafuente et al., 2023 [56]; Li et al., 2021 [57]; Zhou et al., 2020 [58])
Service-led growth trajectoriesProduct–service systems, lifecycle services, power shifting, complexity management, modularity, platform-based innovation, innovation management.(Morgan et al., 2019 [59]; Federica et al., 2019 [60]; Zhang et al., 2022 [61]; Eloranta et al., 2021 [62]; Ezzat et al., 2022 [63]; Huang et al., 2022 [64]; Bustinza et al.,2021 [65])
Digital technologies and servitization strategiesEvolutionary trajectories, service ecosystem, relational components (complementary digital capability), value delivered, digital servitization, resource liquefaction and resource integration, integration of digital and service-specific capabilities, divergence of digitization and servitization as an alternative pathway, Internet of Things-enabled opportunities, evolution.(Culot et al., 2020 [66]; Sklyar et al., 2019 [67]; Kamalaldin et al., 2020 [68]; Simonsson and Agarwal, 2021 [69]; Kohtamäki et al., 2020 [70]; Zhou et al., 2021 [71]; Abou-Foul et al., 2021 [72]; Gomes et al., 2021 [73]; Naik et al., 2020 [74]; Chen et al., 2021 [75])
Table 2. Existing research on packaging and printing industries.
Table 2. Existing research on packaging and printing industries.
Research AreaKey ConceptsRepresentative Literature
Industry 4.0Additive manufacturing, increasing boosting of sustainability performance through digitalization, organizational adoption, product–service system business model, inclusive innovation, robotics and smart manufacturing, servitization, deep learning.(Arifin et al. [76]; Gladysz et al., 2021 [77]; Ukobitz, 2020 [78]; Salwin et al., 2020 [79]; Woodson, T.S., Alcantara, J.T., & Nascimento, M.S., 2019 [80]; Salwin et al. [32]; Huang et al. [81]; Marić, J, 2020 [82]; Villalba-Diez et al., 2019 [83])
MarketingBusiness strategy, green packaging alternatives, improved packaging for online groceries.(Shabbir et al., 2020 [84]; Wandosell et al., 2021 [85]; Spruit et al., 2021 [86])
Environmental impactLife cycle assessment, positivism, interpretivism, transformative consumer research, sustainability.(Su et al., 2020 [87]; Zeng et al., 2020 [88]; Baykina (Fedosova) et al., 2020 [89])
Table 3. Summary of variables.
Table 3. Summary of variables.
SortVariable NameVariable CodeDefinition and Measurement
Explained variableCompetitive AdvantagesCAReturn on total assets of sample companies calculated through industry average return on total assets
Explanatory variableSupply Chain RelationshipsSCC(Proportion of purchases from top five suppliers + proportion of sales to top five customers)/2
Moderator variableDigital TransformationDIGNumber of disclosures of keywords: artificial intelligence technology, cloud computing technology, blockchain technology, big data technology, digital technology applications
Control variablesCompany GrowthGROWTHThe growth rate of main business revenue
Executive Shareholding RatioEIShares held by executives/total share capital
Balance Sheet RatioLEVTotal liabilities/total assets
Operating CapacityROAProfit before tax/total assets
Profit before Tax/Total AssetsPRODUCT(Operating expenses + administrative expenses)/main operating revenues
Proportion of Tangible AssetsRTATangible assets/total assets
Company Dummy VariablesIDCompany stock code
Year Dummy VariablesYEAR2012–2021
Table 4. Descriptive statistics of the main variables.
Table 4. Descriptive statistics of the main variables.
VariablesNMeanSdMinMax
CA5500.3806.383−34.2036.32
SCC55036.4018.803.02097.58
EI15505.33313.59069.75
LEV55041.8319.580111.2
ROA15505.7326.029−32.6335.20
PRODUCT155011.9114.440219.6
RTA155048.0518.81−24.1490.02
Number of ids5555555555
Table 5. Correlation analysis of the main variables.
Table 5. Correlation analysis of the main variables.
VariablesCASCCGROWTHEILEVROAPRODUCTRTA
CA1
SCC0.076 *1
GROWTH0.110 ***0.0261
EI−0.0480.0490.195 ***1
LEV−0.349 ***−0.064−0.022−0.122 ***1
ROA0.804 ***0.238 ***0.171 ***0.065−0.388 ***1
PRODUCT−0.110 ***0.084 *0.0420.02−0.004−0.0551
RTA0.357 ***0.062−0.0210.159 ***−0.875 ***0.453 ***−0.0621
*, **, and *** indicate significance at the 10%, 5%, and 1% levels.
Table 6. Group regression results of the supply chain relationship and corporate competitive advantage.
Table 6. Group regression results of the supply chain relationship and corporate competitive advantage.
(1)(2)
VariablesCACA
SCC−0.0225 **−0.0293 ***
(−2.1317)(−2.8213)
GROWTH−0.00080.0002
(−0.1064)(0.0308)
EI−0.0435 ***−0.0490 ***
(−3.1742)(−3.6541)
LEV−0.0397 **−0.0427 **
(−2.1960)(−2.4224)
ROA0.8510 ***0.8350 ***
(27.5788)(27.2798)
PRODUCT−0.0098−0.0117
(−0.9178)(−1.1228)
RTA−0.0451 **−0.0404 **
(−2.4528)(−2.2487)
_cons0.5022−1.1124
(0.3091)(−0.6829)
Year
ID
No
No
Yes
Yes
N550550
adj. R20.67570.6970
*, **, and *** indicate significance at the 10%, 5%, and 1% levels.
Table 7. The impact of digital transformation on the relationship between supply chain relationships and firms’ competitive advantage.
Table 7. The impact of digital transformation on the relationship between supply chain relationships and firms’ competitive advantage.
VariablesCA
SCC−0.0301 ***
(−2.9542)
DIG−0.0465 **
(−2.1743)
SCC×DIG0.0138 ***
(4.8195)
GROWTH−0.0009
(−0.1214)
EI−0.0481 ***
(−3.6382)
LEV−0.0467 ***
(−2.6925)
ROA0.7983 ***
(25.8453)
PRODUCT−0.0109
(−1.0689)
RTA−0.0398 **
(−2.2566)
_cons−0.6576
(−0.4096)
Year
ID
Yes
Yes
N550
adj. R20.7113
*, **, and *** indicate significance at the 10%, 5%, and 1% levels.
Table 8. Heterogeneous effects from the perspective of property ownership.
Table 8. Heterogeneous effects from the perspective of property ownership.
(1)(2)
VariablesCA
State-Owned EnterprisesNon-State-Owned Enterprises
SCC−0.0679 ***−0.0336 ***
(−7.1379)(−2.6448)
GROWTH−0.00960.0065
(−0.9332)(0.7400)
EI0.0467−0.0535 ***
(1.0619)(−3.6806)
LEV−0.0458−0.0594 ***
(−1.5917)(−2.9171)
ROA0.8994 ***0.8427 ***
(21.4710)(22.3231)
PRODUCT−0.0256 ***−0.0163
(−3.0649)(−0.9737)
RTA−0.0752 **−0.0372 *
(−2.5473)(−1.7831)
_cons−0.68010.0914
(−0.2408)(0.0484)
Year
ID
Yes
Yes
Yes
Yes
N128422
adj. R20.87080.6792
*, **, and *** indicate significance at the 10%, 5%, and 1% levels.
Table 9. Heterogeneous effects from the perspective of dual executive roles.
Table 9. Heterogeneous effects from the perspective of dual executive roles.
(1)(2)
VariablesCA
CEO DualityBoard Independence
SCC−0.0567 ***−0.0342 ***
(−3.2084)(−3.0189)
GROWTH0.0093−0.0087
(0.7232)(−0.9776)
EI−0.0518 **−0.0416 **
(−2.5178)(−2.5012)
LEV0.0464−0.0995 ***
(1.5653)(−4.2351)
ROA0.9063 ***0.8752 ***
(17.6648)(21.2370)
PRODUCT−0.1020−0.0160
(−1.4120)(−1.6135)
RTA0.0770 **−0.1065 ***
(2.4497)(−4.3955)
_cons−8.7663 ***4.2642 *
(−3.0827)(1.9323)
Year
ID
Yes
Yes
Yes
Yes
N210340
adj. R20.71270.7086
*, **, and *** indicate significance at the 10%, 5%, and 1% levels.
Table 10. Heterogeneous effects from the perspective of company scale.
Table 10. Heterogeneous effects from the perspective of company scale.
(1)(2)
VariablesCA
Small-Scale EnterprisesLarge-Scale Enterprises
SCC−0.0572 ***−0.0287 **
(−4.2958)(−2.3719)
GROWTH−0.0142−0.0027
(−1.1208)(−0.2906)
EI−0.0300−0.0513 ***
(−0.3342)(−3.8502)
LEV0.0554 **−0.1543 ***
(2.1669)(−6.9098)
ROA0.8462 ***0.8862 ***
(16.9913)(23.3105)
PRODUCT−0.1402 **−0.0309 ***
(−2.3751)(−2.6855)
RTA0.0492 *−0.1263 ***
(1.7231)(−5.5746)
_cons−9.9001 ***8.7750 ***
(−3.8601)(4.3042)
Year
ID
Yes
Yes
Yes
Yes
N267283
adj. R20.70080.7639
*, **, and *** indicate significance at the 10%, 5%, and 1% levels.
Table 11. Lagged one-period regression results.
Table 11. Lagged one-period regression results.
VariablesCA
L.SCC−0.0318 ***
(−3.0333)
GROWTH0.0012
(0.1656)
LEV−0.0477 **
(−2.5136)
EI−0.0439 ***
(−3.1419)
ROA0.8126 ***
(25.5686)
PRODUCT−0.0194
(−1.5818)
RTA−0.0520 ***
(−2.7234)
_cons2.3639
(1.3606)
Year
ID
Yes
Yes
N495
adj. R20.6848
*, **, and *** indicate significance at the 10%, 5%, and 1% levels.
Table 12. Regression results when replacing the measurement of the explanatory variables.
Table 12. Regression results when replacing the measurement of the explanatory variables.
(1)(2)
VariablesLILI
SCC−0.0667 *−0.0805 **
(−1.6538)(−1.9994)
GROWTH−0.0338−0.0357
(−1.2013)(−1.2636)
LEV−0.0291−0.0264
(−0.4186)(−0.3826)
EI0.0097−0.0109
(0.1843)(−0.2083)
ROA0.9243 ***0.9239 ***
(7.7475)(7.6728)
PRODUCT−1.2051 ***−1.2036 ***
(−29.1469)(−29.1829)
RTA0.06890.0581
(0.9689)(0.8222)
_cons19.6847 ***13.9105 **
(3.1430)(2.1766)
Year
ID
No
No
Yes
Yes
N550550
adj. R20.63280.6426
*, **, and *** indicate significance at the 10%, 5%, and 1% levels.
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Tana, G.; Chai, J. Digital Transformation: Moderating Supply Chain Concentration and Competitive Advantage in the Service-Oriented Manufacturing Industry. Systems 2023, 11, 486. https://doi.org/10.3390/systems11100486

AMA Style

Tana G, Chai J. Digital Transformation: Moderating Supply Chain Concentration and Competitive Advantage in the Service-Oriented Manufacturing Industry. Systems. 2023; 11(10):486. https://doi.org/10.3390/systems11100486

Chicago/Turabian Style

Tana, Gegen, and Junwu Chai. 2023. "Digital Transformation: Moderating Supply Chain Concentration and Competitive Advantage in the Service-Oriented Manufacturing Industry" Systems 11, no. 10: 486. https://doi.org/10.3390/systems11100486

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