Yearly Distribution of the Literature
Scopus indicates that the specified publication date ranges from 1995 to 2003. However, themes associated with disruptive digital technology and disruptive digital innovation were primarily published after the 2010s, particularly after 2018, and reached their peak in 2021, which can show in Fig. 1 and also indicating a delayed emphasis on this topic. It suggests that researchers and academics only recently recognized the significance of digital technology and its potential impact on disruption, resulting in an increase in publications in recent years.
Block Chain is the most published disruptive technology, with 26 publications, and has attracted significant attention in digital disruption. The decentralized and transparent nature of block chain has the potential to disrupt numerous industries, thereby increasing research interest and publications on the subject. In addition, the 3D printing and AI papers are the top two and top three disruptive technologies. AI revolutionizes multiple industries through automation and intelligent decision-making, whereas 3D printing facilitates decentralized production and customization. Their disruptive potential has attracted researchers, resulting in numerous publications. In addition, big data and cloud computing are the least prevalent, which may reflect a research gap or a delayed recognition of their disruptive potential during the study period. However, it is essential to consider that the selection of Scopus papers may also influence this result.
Geographical Distribution of the Literature
China, the United Kingdom, and the United States publish the most papers on the impact of digital technologies on digital disruption. Additionally, India, France, and Italy all actively contribute to this field's research.67% of published papers originate from developed nations, including Australia, Canada, France, Germany, Ireland, Italy, Netherlands, Portugal, South Korea, Singapore, Sweden, Spain, the United Kingdom, and the United States, which is an intriguing fact. This could be attributed to factors such as the availability of research funding, technologically sophisticated infrastructure, and a robust academic ecosystem in these nations.
However, 33% of the papers come from developing nations, including China, Egypt, Hungary, India, Romania, Malaysia, and South Africa. This indicates that researchers in these countries are also investigating the impact of digital technologies on digital disruption, despite potentially facing different challenges and contexts than their counterparts in developed nations. The details show in Fig. 2.
Digital Technology on Disruption
Existing articles demonstrate that digital technology on digital disruption adoption and integration have transformed traditional industries, thereby creating new opportunities for growth, innovation, and increased productivity. AI, Block chain, IoT, Cloud Computing, big data, and 3D printing are continuously reshaping industries, resulting in new business models, increased productivity, and improved consumer experiences. Block chain research on digital disruption is the most prevalent among these disruptive technologies, followed by 3D printing technology and artificial intelligence. Figure 3 depicts the number of digital technologies on digital disruptions for each.
Artificial Intelligence (AI)
AI's impact on digital disruption is transformative across multiple industries. the first of which is automation and efficiency. In this area, AI-powered automation can streamline processes, reduce costs, and increase operational efficiency, thereby disrupting traditional industries that rely heavily on human labor. For instance, artificial intelligence disrupts traditional logistics practices by facilitating automation, optimization, and intelligent decision-making in logistics operations, resulting in increased efficiency, accuracy, and cost savings (Jia et al., 2022).. The second is to focus more on predictive analytics, in which AI algorithms can analyses large datasets to make accurate predictions, thereby transforming the decision-making processes in finance, marketing, and supply chain management (Hussain et al., 2023). The final section addresses customization and consumer experience. In industries such as e-commerce, entertainment, healthcare, education and robotics. AI-driven personalization techniques can tailor products, services, and experiences to individual consumer preferences, posing a challenge to one-size-fits-all approaches. AI, for instance, disrupts traditional consumer preferences and behaviors by providing personalized experiences, virtual assistants, and AI-driven recommendations, thereby altering how consumers make purchasing decisions and interact with products and services (Wamba, 2022). Table 1 provides a summary of AI that can disrupt traditional industries.
Table 1
Summary of AI Disrupt Traditional Industries.
Digital Technology
|
Disrupt Traditional Industry
|
Segment
Industry
|
Authors
|
Country
|
Artificial Intelligence (AI)
|
Automation and Efficiency
|
Adoption of Autonomous Vehicles (AV)
|
(Plantec et al., 2023)
|
France
|
(Silva et al., 2023)
|
China
|
(Casas & Torres, 2023)
|
Spain
|
(Park et al., 2021)
|
Korea
|
Disruptive Technologies in Intelligent Logistics Robots
|
(Jia et al., 2022)
|
China
|
AI Documentation and Integration into Business Processes
|
(Königstorfer & Thalmann, 2021)
|
Austria
|
Supply Chain Management
|
(Rodríguez-Espíndola et al., 2020)
|
UK
|
Predictive Analytics
|
Decision-making, assist in diagnosis in healthcare
|
(Dwivedi et al., 2023)
|
UK
|
AI for Decision-making in Arbitration
|
(Hussain et al., 2023)
|
Malaysia
|
Personalization and Customer Experience
|
Adoption of AI by Consumers
|
(Wamba, 2022)
|
France
|
Multi-objective Optimization and Algorithm Design
|
(Yue et al., 2021)
|
China
|
Intelligent Transport System
|
(Rao, 2021)
|
India
|
Automated frequency trading
|
(Ma & McGroarty, 2017)
|
UK
|
A knowledge management
|
(Menkhoff et al., 2022)
|
Singapore
|
criterion of AI ethics
|
(Kriebitz & Lütge, 2020)
|
Germany
|
Source: author’s own elaboration |
Moreover, AI also plays an important role in other industries. Autonomous vehicles (AV) have arisen as a disruptive technology in the conventional sector, revolutionizing the transportation and logistics industries (Dwivedi et al., 2023). Intelligent logistics robots powered by artificial intelligence (AI) have played a crucial role in the optimization of supply chain management processes. By automating duties such as inventory management, sorting, and packaging, these robots have dramatically increased productivity and decreased expenses. In addition, the incorporation of AI into business processes has transformed documentation procedures, resulting in streamlined workflows and enhanced precision. AI has become indispensable in decision-making and diagnosis, enabling medical professionals to provide precise and timely treatments (Wamba, 2022). In addition to embracing AI, consumers have adopted smart devices and virtual assistants that enhance their daily lives. In conclusion, the development of multi-objective optimization algorithms has revolutionized algorithm design, allowing for effective resource allocation and optimal results. These results illustrate the disruptive impact of AI across multiple industries, which is spurring innovation and reshaping traditional industry practices.
Artificial Intelligence has emerged as a disruptive force, transforming traditional industries differently. Through the review of the AI articles, the study found that not all sectors are affected by this disruptive technology, mainly accepted by healthcare, education, logistics and supply chain and automation, as well as the financial industry and robotics. Even though by harnessing the transformative power of AI, traditional industries can unlock new opportunities, drive digital disruption, and surpass the leaders in an increasingly competitive landscape. There is a concern that AI could replace human workers in specific tasks and roles. This disruption may lead to job displacement, unemployment, and a need for upskilling or reskilling the workforce to adapt to the changing demands of AI-driven industries. AI relies on vast amounts of data, and its practical implementation requires access to sensitive information. This reliance raises concerns about data privacy and security breaches, potentially exposing businesses and individuals to cyber threats and ethical dilemmas. Therefore, practitioners and policymakers should use proactive measures, proper regulations, and ethical considerations. Traditional industries can harness the potential of AI while minimizing potential risks and ensuring a sustainable and inclusive future.
Block Chain
According to this Scopus assessment, block chain disrupts enterprises. Responses from stakeholders and decision-making in block chain adoption demonstrate the need to comprehend their needs and concerns. (Ferri et al., 2021; Guo et al., 2021; Zhang et al., 2023). In addition to enhancing supply chain transparency, collaboration, and traceability, block chain combats fraud and lack of transparency (Choi et al., 2021; Choi & Siqin, 2022; Zhu et al., 2021; Zkik et al., 2022). Additionally, the study demonstrates how regulatory frameworks and auditor collaborations enhance block chain compliance and auditing (Gan et al., 2021; Sheldon, 2019; Ziolkowski et al., 2020). It may disrupt multiple industries and business models (Frizzo-Barker et al., 2020). The distributed ledger technology of it increases both transparency and trust. The immutability and auditability of block chain can aid industries involving counterfeit goods, supply chain fraud, and opaque financial transactions. Thus, trust and accountability increase, ensuring the security and dependability of the organization. Encryption is utilized by this technology to safeguard sensitive data in healthcare, finance, and identity verification. Customer confidence is increased by Block chain, which reduces data intrusions, tampering, and fraud. Additionally, block chain alters business paradigms. Peer-to-peer transactions facilitated by block chain technology, decentralized applications, and asset tokenization create new revenue streams, business models, and ecosystems. Thus, sectors dependent on intermediaries may undergo significant shifts. The summarize of the contributed to the emergence of digital disruptions in various industries is shown in Table 2.
Table 2
Summary of Block Chain Disrupt Traditional Industries.
Digital Technology
|
Disrupt Traditional Industry
|
Explanation
|
Authors
|
Country
|
Block chain
|
Stakeholder Responses and Decision Making
|
Key stakeholders' best blockchain implementation responses
|
(Zhang et al., 2023)
|
China
|
Decision issues and determinants of blockchain adoption
|
(Ferri et al., 2021)
|
UK
|
Managers and policymakers affect blockchain adoption.
|
(Guo et al., 2021)
|
US
|
Robust facility location decisions
|
(Sundarakani et al., 2021)
|
France
|
Traceability and Supply Chain Management
|
Blockchain traceability system design effectiveness and robustness
|
(Choi et al., 2021)
|
China
|
Blockchain-enabled supply chain management non-functional requirements and system design
|
(Zhu et al., 2021)
|
China
|
Production and logistics blockchain success factors
|
(Choi & Siqin, 2022)
|
China
|
E-agriculture supply chain blockchain strategies and recommendations
|
(Zkik et al., 2022)
|
France
|
Supply Chain Management
|
(Kafeel et al., 2023)
|
UK
|
Supply Chain Management
|
(Zhu et al., 2022)
|
US
|
Retail Food Supply Chain
|
(Kumar et al., 2022)
|
India
|
Supply Chain Adaptability
|
(Sheel & Nath, 2019)
|
India
|
Block chain-based cloud services
|
(Prasad et al., 2018)
|
India
|
Block chain enabled medical supply chain
|
(Khatter & DevanjaliRelan, 2022)
|
India
|
Sustainable Supply chain
|
(Saberi et al., 2019)
|
US
|
Supply chain digitization benefits
|
(Haddud & Khare, 2020)
|
Canada
|
Supply chain management
|
(Ziegler & Uli, 2021)
|
Germany
|
Transform Supply Chain
|
(Laforet & Bilek, 2021)
|
France
|
Fashion Supply Chains
|
(Chan et al., 2020)
|
China
|
Banking, Finance, and Governance
|
Block chain banking and finance study analysis
|
(Gan et al., 2021)
|
China
|
Block chain decision issues and cooperative principles.
|
(Ziolkowski et al., 2020)
|
Ireland
|
Distributed ledgers and decentralized
|
(Centobelli et al., 2021)
|
Italy
|
Distributed ledger technology
|
(Firica, 2017)
|
Romania
|
Block chain ITGC audits.
|
(Sheldon, 2019)
|
US
|
SCM and block chain
|
(Karamchandani et al., 2021)
|
US
|
Electronic marketplace block chain
|
(Kollmann et al., 2020)
|
Germany
|
Source: author’s own elaboration |
Block chain has the potential to destabilize centralized systems by enabling peer-to-peer transactions and bestowing individual’s ownership over their data and assets, thereby enabling stakeholders to verify and trace transactions and data in real time (Ferri et al., 2021; Guo et al., 2021; Sundarakani et al., 2021; Zhang et al., 2023). In addition, intelligent contracts can do away with middlemen, reduce bureaucracy, and automate trust mechanisms. This not only increases productivity but also significantly reduces costs. Consequently, data integrity improves and participant confidence increases (Centobelli et al., 2021; Firica, 2017; Gan et al., 2021; Ziolkowski et al., 2020). Block chain has made significant contributions to numerous industries, but it also faces a number of economic and market challenges. Regulatory and legal issues, as well as governance concerns and the need for industry-wide acceptance, are all obstacles to wider adoption (Karamchandani et al., 2021; Kollmann et al., 2020; Sheldon, 2019). Despite its advancements, block chain technology is still in its early phases of development and refinement, with a great deal of room for future growth and development.
Durability, transparency, immutability, and process integrity are characteristics of block chain (Abeyratne & Monfared, 2016). This digital technology can potentially disrupt traditional industries such as the financial sector, supply chain management, healthcare, intellectual property and copyright, logistics and transportation, the energy sector, and government services such as voting systems, identity management, and public records (Kafeel et al., 2023; Kumar et al., 2022; Prasad et al., 2018; Saberi et al., 2019; Zhu et al., 2021). However, regulatory barriers and legal complexities may impede the adoption of block chain technology, even though it can increase trust in business transactions and boost security, thereby protecting against deception, manipulation, and unauthorized access. In addition, the study suggests a cautious approach to implementation, considering the industry's context and requirements. This digital technology has not yet disrupted the entire business world and all industries (Kafeel et al., 2023); it is still in its infancy. It still faces numerous obstacles and difficulties. Moreover, organizations with low integrating intensity, greater IT integration, and small size are more likely to implement this disruptive technology, according to the study (Karamchandani et al., 2021). Therefore, not all organizations or businesses can immediately adopt block chain technology to challenge or disrupt their traditional business model. Increasing and promoting the proportion of the industry that employs this disruptive technology becomes necessary.
3D Printing
The research findings can be summarized into three primary perspectives that encompass the diverse industries related to the digital disruptions of 3D printing technology. The first area is that operational transformation focuses on achieving economies of scale. This category includes adopting innovative operational management practices, such as volume and material flow optimization design, leading to economies of scale and improved operational efficiency. It also consists of the potential disruption of traditional logistics practices and the diversification of service portfolios in the logistics industry (Colosimo et al., 2018; Hecker, 2021; Huang et al., 2021). The second is a societal Impact and adoption, which highlights the significance of social sustainability and consumer acceptance, which highlights the social sustainability implications of 3D printing technology, including the interest and acceptance of technology among young people and the intention to incorporate it into their lives. It also acknowledges the need for improvements in user-friendliness and technological capabilities to drive broader adoption (Berman, 2012; Ponzoa et al., 2021; Steenhuis & Pretorius, 2016). The last one is supply chain Integration and sustainability, which emphasizes the integration of disruptive technologies like Artificial Intelligence, Block chain, and 3D Printing to improve the flow of information, products, and financial resources in supply chains. It also explores the potential of 3D printing to enable a circular economy at the local level and promote resource efficiency (Garmulewicz et al., 2018; Rodríguez-Espíndola et al., 2020). These themes collectively demonstrate the broad impact of 3D printing technology across operational practices, societal dynamics, and supply chain management, offering insights into the transformative potential of this technology. Table 3 summary the 3D Printing technology disrupt traditional industries.
Table 3
Summary of 3D Printing Disrupt Traditional Industries
Digital Technology
|
Disrupt Traditional Industry
|
Explanation
|
Authors
|
Country
|
3D printing
|
Operational Transformation
|
Scalability and Efficiency
|
(Huang et al., 2021)
|
China
|
Logistics Disruption and Diversification
|
(Hecker, 2021)
|
Germany
|
Quality Concerns
|
(Colosimo et al., 2018)
|
Italy
|
Optimization strategy
|
(Griffiths et al., 2016)
|
UK
|
Societal Impact and Adoption
|
Consumer Acceptance
|
(Ponzoa et al., 2021)
|
Spain
|
Consumer 3D printing could be disruptive.
|
(Steenhuis & Pretorius, 2016)
|
South Africa
|
Comparing Disruptive Technologies
|
(Berman, 2012)
|
US
|
AM technology's societal sustainability
|
(Naghshineh et al., 2021)
|
Portugal
|
3D printing business models
|
(Roth, 2018)
|
France
|
spotting disruptive trends
|
(Dotsika & Watkins, 2017)
|
UK
|
3D printing democratisation
|
(Birtchnell et al., 2020)
|
Australia
|
Sustainable Supply Chain Integration
|
Disruptive Tech Integration
|
(Rodríguez-Espíndola et al., 2020)
|
UK
|
Circular Economy 3D Printing
|
(Garmulewicz et al., 2018)
|
UK
|
Supply chain positions
|
(Öberg & Shams, 2019)
|
US
|
Zero-waste fashion designs
|
(Pasricha & Greeninger, 2018)
|
US
|
Modify manufacturing and construction methods
|
(Majumdar et al., 2018)
|
India
|
Influence supply chain eco-performance
|
(Kothman & Faber, 2016)
|
Netherlands
|
Source: author’s own elaboration |
The convergence of 3D printing technology with digital disruption has the potential to significantly disrupt industries, supply networks, and consumer experiences. Customization, decentralized production, rapid prototyping, sustainability, and material progress are all possible. At the same time, the study discovers that this type of technology also provides some digital disruption in social transformation; it opens options for self-sufficiency, such as democratic manufacturing, also known as manufactured in India (Birtchnell et al., 2020). However, because 3D printing technology can only produce a few bespoke goods, such as replacement components, dental crowns, artificial limbs, and bridge fabrication, it has not achieved mass popularization (Berman, 2012). Even if existing research can find some benefits and disrupt old industries and businesses, it also has some drawbacks. It will, for example, lessen the demand for factory labor while raising complicated legal (Berman, 2012), ethical and regulatory challenges that must be addressed. Large-scale 3D printing can be more expensive than traditional production methods, despite substantial technological breakthroughs. Printers, materials, and post-processing equipment might be too expensive for some applications. Obtaining cost-effective scalability remains difficult, particularly in high-volume production. Furthermore, 3D printing procedures are often slower than traditional production methods. Improving printing speeds and overall efficiency while maintaining quality is critical for wider adoption in time-sensitive sectors. Furthermore, while the range of printable materials has grown, there are still constraints in terms of material qualities, strength, and durability. To overcome these constraints, it will be necessary to develop new materials with superior qualities and broaden the material possibilities accessible for various printing processes (Colosimo et al., 2018). As a result, 3D printing is an incremental digital disruption as a disruptive technology.
Internet of Things (IoT),
The results show the IoT technology disruptive traditional industry demonstrates two distinct perspectives. The first perspective focuses on IoT in industry and innovation, highlighting its implementation and influence. This perspective examines the phased implementation of Automated Guided Vehicles (AGVs), emphasizing design, integration, and continuous improvement(Vlachos et al., 2022; Vlachos et al., 2023). It also explores the integration of IoT with manufacturing processes, showcasing disruptive technologies such as two-dimensional codes, sensing technology, and artificial intelligence that drives digital disruption in intelligent logistics robots (Jia et al., 2022). The second perspective emphasizes stakeholders, generational perspectives, and infrastructure considerations. It underscores the significance of involving various stakeholders and recognizing the importance of generational perspectives in adopting IoT (Marinakis et al., 2021). Additionally, this perspective stresses the role of infrastructure in supporting IoT implementation and emphasizes the need for road mapping techniques to ensure successful integration (Islam et al., 2020; Santoro et al., 2018).These kinds of disruptive technological skills change how technology management in an organization. Collectively, these two perspectives shed light on the practical application of IoT in industry, disrupting the traditional method in the manufacturing industry while underscoring the importance of combining AI and Lot for its successful digital disruption in intelligent logistic robots. Table 4 summary the Internet of Things technology disrupts traditional industries.
Table 4
Summary of Internet of Things Disrupt Traditional Industries.
Digital Technology
|
Disrupt Traditional Industry
|
Explanation
|
Authors
|
Country
|
Internet of Things (LoT)
|
IoT in Industry and Manufacturing
|
AGVs implementation phases
|
(Vlachos et al., 2023)
|
UK
|
IoT in manufacturing
|
(Vlachos et al., 2022)
|
UK
|
digital disruptions advancing intelligent logistics robots.
|
(Jia et al., 2022)
|
China
|
Food security system
|
(Kaur, 2021)
|
India
|
Information and communication technology
|
(Jia et al., 2021)
|
China
|
Knowledge management system
|
(Santoro et al., 2018)
|
Italy
|
Stakeholders, Generational Perspectives, and Infrastructure
|
Generational stakeholders for IoT and SCOT
|
(Marinakis et al., 2021)
|
US
|
Development of a precursor road mapping construct
|
(Islam et al., 2020)
|
UK
|
Knowledge management system for collaborative ecosystems
|
(Santoro et al., 2018)
|
Italy
|
Stakeholders, information list
|
(Giovanardi et al., 2023)
|
Italy
|
Main critical skills
|
(Sousa & Wilks, 2018)
|
Portugal
|
Source: author’s own elaboration |
The intersection of the Internet of Things (IoT) and digital disruption in the foreseeable future contains tremendous potential for revolutionary progress. Anticipated trends include power and water grids, industry transformation, smart cities, advances in healthcare, education, food production and personalized medicine. Nonetheless, the path to actualizing this potential faces numerous obstacles and challenges. Security and privacy issues arise as the number of interconnected devices and the volume of data continue to grow. Some firms are hesitant to decide to develop this technology. Persistent interoperability and standardization issues hinder the integration of disparate IoT systems. As deploying numerous connected devices requires a robust network infrastructure and sufficient bandwidth, scalability and infrastructure requirements pose obstacles. Therefore, managing and deriving actionable insights from the massive data generated by IoT devices presents additional data management and analytics challenges. The other challenges must be addressed are energy efficiency, regulatory and legal frameworks, and the demand for a skilled labor force. By proactively addressing these challenges, industry stakeholders and policymakers can navigate the future landscape of IoT-driven digital disruption, realizing its maximum potential for societal and economic transformation.
Big Data and Cloud Computing
The findings are classified into two groups. The first category is concerned with mathematical models and optimization approaches, such as using evolutionary algorithms for multi-objective optimization and developing contrast flows to speed up the search for optimal solutions. These models and algorithms have real-world applications in a variety of industries (Yue et al., 2021). The second category emphasizes the impact of upcoming technology, such as big data and self-driving cars. The research examines the current level of knowledge and highlights potential prospects related to these technologies (Dong et al., 2021). It focuses on early adopters' use of IoT and the development of big data, which leads to significant operational gains. The benefits of IoT and big data applications in several industries are highlighted, with examples from industry leaders (Roy & Roy, 2019). Overall, this study provides important insights for governments on implementing technologies to limit the consequences of unprecedented outbreaks such as COVID-19 and shines a light on the transformational potential of digital technology in fostering digital disruption.
Furthermore, the findings demonstrate how cloud computing technology has aided in introducing disruptive technologies in various industries. The findings highlight three significant types. To begin, it is proposed that cloud technology may mature sooner than expected, providing a chance for businesses to obtain a competitive edge in the face of technological breakthroughs and uncertainties (Srivastava et al., 2021). Second, testing results show that cloud computing is effective and efficient, including its capacity to prevent SLA violations, optimize QoS, and manage service components across numerous cloud providers (Fuzes, 2020; Sfondrini & Motta, 2021). Furthermore, the study emphasizes the revolutionary impact of cloud computing on the industry, particularly in emerging markets, and the ramifications for companies such as Oracle (Bruque Camara et al., 2015). Finally, incorporating cloud computing with other cutting-edge technologies, such as Cyber-Physical Systems (CPS), heralds the arrival of Industry 4.0 in the manufacturing sector (Ramzi et al., 2019). The paper also emphasizes the significance of supply chain integration in enabling successful cloud computing implementation (Adamuthe & Thampi, 2019). Overall, these findings highlight the importance of cloud technology in enabling disruptive ideas and provide insights for businesses looking to capitalize on its potential benefits. Table 5 summary the big data and cloud computing technology disrupts traditional industries.
Table 5
Summary of Big Data and Cloud Computing Disrupt Traditional Industries
Digital Technology
|
Disrupt Traditional Industry
|
Explanation
|
Authors
|
Country
|
Big Data
|
Mathematical Models and Optimization Techniques
|
Mathematical modelling and multi-objective optimisation with genetic algorithms
|
(Yue et al., 2021)
|
China
|
These models and algorithms in numerous sectors
|
(Roy & Roy, 2019)
|
US
|
Impact of Emerging Technologies on digital disruption in industries
|
Identification and analysis of emerging technologies
|
(Dong et al., 2021)
|
Sweden
|
Mobile payment
|
(Schmidthuber et al., 2020)
|
Austria
|
Disruptive technologies for COVID-19 analysis
|
(Abdel-Basset et al., 2021)
|
Egypt
|
Digital technologies in hospitality
|
(Lee et al., 2023)
|
US
|
Development of the IoT and big data industry
|
(He et al., 2020)
|
US
|
Cloud Computing
|
Competitive Advantage and Early Adoption
|
Cloud technology maturing early and unpredictable technological age.
|
(Srivastava et al., 2021)
|
India
|
Investing in cloud technology and remain digital disruption.
|
(Fuzes, 2020)
|
Hungary
|
Effectiveness and Efficiency of Cloud Computing
|
Cloud technology prevents SLA violations
|
(Sfondrini & Motta, 2021)
|
Italy
|
Cloud computing prevents service performance degradations.
|
(Bruque Camara et al., 2015)
|
Spain
|
Cloud Computing and Industry Transformation
|
The integration of cloud computing with other technologies
|
(Ramzi et al., 2019)
|
Malaysia
|
Cloud computing requires supply chain integration.
|
(Adamuthe & Thampi, 2019)
|
India
|
Transformative skills of business leaders
|
(Gaffley & Pelser, 2021)
|
South Africa
|
Source: author’s own elaboration |
According to the existing research, big data applications and cloud technologies may evolve quicker than expected and disrupt numerous industries, resulting in considerable operational gains than other digital disruptive technologies. However, the fast development speed of this disruptive technology may pose a potential threat to conventional businesses that may be slow to adopt these technologies. Furthermore, it may provide some complications. The first is increasing data volume and complexity, which indicates that data volume will continue to expand due to IoT devices, social media, and connected technology. In addition, data will become more diverse and unstructured, necessitating the use of advanced analytics techniques. Automation will be possible by combining big data analytics with AI and machine learning algorithms, advanced data-driven insights, predictive modelling, and decision-making process. The current organization and firms lack this digital disruption capability; some even want to hesitate to embrace and somehow resist the transformation of disruptive technology. At the same time, the shortage of skilled personnel in big data analytics and cloud computing on related technologies is a big problem that cannot be denied. Therefore, it still needs industry, academia, and technology providers to work together on continual innovation, strategic planning, and collaboration to attain their full potential and then disrupt the existing business world and industry to drive the industrial revolution.