Enterprise digitalisation and financial performance: the moderating role of dynamic capability

Yu, Feifei; Jiang, Dong; Zhang, Yu; Du, Hongyan

doi:10.1080/09537325.2021.1980211

Cited by 34 publications

(35 citation statements)

References 48 publications

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“…Artificial intelligence has gained much attention as a potential to increase the competitive advantage of firms ( Hughes et al, 2020 ; Obschonka and Audretsch, 2020 ; Shareef et al, 2021 ). Firm capabilities of applied AI also appear to be particularly valuable ( Yu et al, 2021 ). Combined with RBV, we define AIC of e-commerce firms as the ability of firms to build, integrate, and utilize AI-based related resources ( Łapińska et al, 2021 ; Mikalef and Gupta, 2021 ).…”

Section: Literature Review and Conceptual Modelmentioning

confidence: 99%

“…The majority of the businesses across E-commerce companies are throughout the Internet, and thus they have a natural advantage in acquiring data resources ( Wang and Fan, 2021 ). While the firm sets down the basic tangible resources, it is significant to efficiently employ the proclivity of using AI (intangible resources; Ashaari et al, 2021 ; Yu et al, 2021 ). If firms are not inclined to implement AI in planning, coordination, control, and implementation ( Belhadi et al, 2021 ; Chen and Lin, 2021 ), even if they have access to very superior AI base resources will not help ( Denicolai et al, 2021 ).…”

Section: Literature Review and Conceptual Modelmentioning

confidence: 99%

“…In this scenario, IC is an enterprise culture that encourages innovation ( Khattak et al, 2021 ), encouraging motivation and adopting technologies like artificial intelligence within firms ( Zhang et al, 2021 ), and it helps firms reach higher business goals ( Chaudhuri et al, 2021 ). In the face of intense market competition, encouragement of firm innovation is more likely to transform processes and decisions with digital technologies represented by artificial intelligence to gain new business opportunities and improve performance ( Yu et al, 2021 ). Innovation culture plays an essential role in organizations adopting new decision-making approaches and transforming organizations ( Chen and Lin, 2021 ), and AI-based driven decision-making implies opportunities to enhance business performance ( Ashaari et al, 2021 ).…”

Section: Literature Review and Conceptual Modelmentioning

confidence: 99%

“…Enterprise capabilities are critical for identifying business opportunities ( Yao et al, 2021 ). While there is excellent potential for artificial intelligence capability (AIC) to improve a company’s performance ( Mikalef and Gupta, 2021 ), there are also significant challenges to these companies applying AI ( Yu et al, 2021 ). Businesses can utilize AI to improve the customer service experience by offering more appropriate recommendations and less costly options ( Payne et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

2022

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The application of artificial intelligence (AI) technology has evolved into an influential endeavor to improve firm performance, but little research considers the relationship among artificial intelligence capability (AIC), management (AIM), driven decision making (AIDDM), and firm performance. Based on the resource-based view (RBV) and existing findings, this paper constructs a higher-order model of AIC and suggests a research model of e-commerce firm AIC and firm performance. We collected 394 valid questionnaires and conducted data analysis using partial least squares structural equation modeling (PLS-SEM). As a second-order variable, AIC was formed by three first-order variables: basic, proclivity, and skills. AIC indirectly affects firm performance through creativity, AIM, and AI-driven decision making. Firm creativity, AIM, and AIDDM are essential variables between AIC and firm performance. Innovation culture (IC) positive moderates the relationship between firm creativity and AIDDM as well as the relationship between AIDDM and firm performance. Environmental dynamism (ED) positive mediates the connection between AIM and AIDDM. Among the control variables, firm age negatively affects firm performance, and employee size does not. This study helps enterprises leverage AI to improve firm performance, achieve a competitive advantage, and contribute to theory and management practice.

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Section: Literature Review and Conceptual Modelmentioning

confidence: 99%

Section: Literature Review and Conceptual Modelmentioning

confidence: 99%

Section: Literature Review and Conceptual Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

2022

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“…When businesses that use business model design introduce innovative and efficient business models, the creation, transfer, and acquisition of business value are made easier for everyone involved in the value chain. Designing a company's business model is now recognized as a critical instrument for enhancing efficiency within the organization [6,7].…”

Section: Introductionmentioning

confidence: 99%

Evaluation Method for Diversifying Dynamic Capabilities of Small- and Medium-Sized Enterprises Using a Hybrid Genetic Algorithm

Zhao

2022

Mobile Information Systems

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Focusing on the topic of dynamic capability development and digital transformation of traditional enterprises in the digital economy era, and using traditional manufacturing as an example, this paper examines how small- and medium-sized (SMS) businesses should transform and develop in the digital economy era. Furthermore, in light of the problem that existing models cannot evaluate dynamic nonlinear optimization, a diversified dynamic capability evaluation model of SMS enterprises is developed, and the model is solved using the accelerated genetic value method based on real number coding, while the parameters of the BP network are evaluated using the genetic algorithm. In this study, 100 SMS companies are chosen from a pool of 1000 companies to perform an empirical study. In the empirical study, three different scenarios were employed. The selected dataset is utilized to test BP and GA in the first scenario. In the second scenario, the BP and GA are combined to create a more robust model, which is then evaluated on the specified dataset. This research provides a novel approach that combines the PCA with the acceleration method in the third case. According to the findings of this study, the methodology suggested in this work has an overall evaluation accuracy of 95.6 percent, which is pretty good when compared to other approaches. The model training error and test error, on the other hand, are both lower than those of traditional assessment procedures, according to the data.

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What digital‐enabled dynamic capabilities support the circular economy? A multiple case study approach

et al. 2023

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Circular economy and digital technologies are crucial topics in the current academic and managerial debates. It is largely recognised that—although related to different paradigms—digital technologies could support the industrial circular transition, fostering the adoption of circular economy practices. So far, the relationship has been studied by directly linking the adoption of digital technologies to the implementation of circular economy practices; however, indications for practitioners are unclear. There is thus the need to investigate the relationship at a deeper level. This paper aims at contributing to the debate by adopting a dynamic capabilities theory perspective. By employing an explorative multiple case study methodology and based on an abductive logic, this study investigates 11 Northern‐Italy industrial firms in order to understand the transformations that occurred following the adoption of digital technologies and how these transformations supported the adoption of circular economy practices. The results shed preliminary light on which dynamic capabilities—sensing, seizing and transforming, and their related microfoundations—can be enabled by the different digital technologies and how these capabilities and microfoundations support the circular transition. The study thus provides a first‐of‐a‐kind investigation and suggests propositions for further research to better deepen the knowledge of digital‐enabled dynamic capabilities supporting industrial circular economy.

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Enterprise digitalisation and financial performance: the moderating role of dynamic capability

Cited by 34 publications

References 48 publications

The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

Evaluation Method for Diversifying Dynamic Capabilities of Small- and Medium-Sized Enterprises Using a Hybrid Genetic Algorithm

What digital‐enabled dynamic capabilities support the circular economy? A multiple case study approach

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