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Managing in the face of disruption: how do companies manage business model innovation along the process of disruptive innovation?

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• archetypes, business model, business model innovation, disruptor's dilemma, disruptive innovation,
• dynamic capabilities, platform, strategic alliances, topic modeling, value proposition innovation

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• Process Social Sciences 100%
• Company Social Sciences 100%
• Business Model Social Sciences 100%
• Disruptive Innovation Social Sciences 100%
• Innovation Social Sciences 100%
• Research Psychology 100%
• Longitudinal Study Psychology 33%
• Mixed Methods Psychology 33%

T1 - Managing in the face of disruption: how do companies manage business model innovation along the process of disruptive innovation?

AU - Schmidt, Alexander Lennart

PY - 2021/3/8

Y1 - 2021/3/8

N2 - In a world of continuous change, companies’ conventional modes of doing business are being disturbed at an ever-increasing pace. Hence, scholars from the innovation and management domains are discussing innovation-induced market changes. The concept of disruptive innovation captures a portion of these changes. Disruptive innovation describes how new entrants gain a foothold in a niche market before moving upmarket and challenging powerful incumbents. From its emergence in the mid-1990s, the concept of disruptive innovation was first theorised with a focus on technology. Since 2006, the debate has shifted focus, and the business model is acknowledged as the decisive vehicle that spurs related market dynamics. Given the complexity of disruptive innovation, this thesis builds on multiple theoretical streams to further extend our understanding of companies’ strategic management choices in the face of disruptive innovation. An integration of elements from business model innovation, strategic alliances, platform development and growth, and dynamic capabilities enables a complementary picture of the levels of disruptive innovation. This research is guided by the following question: ‘how do companies manage business model innovation along the process of disruptive innovation?’ Following a sequential mixed methods approach, this research uses publications, interview data, archival data, and survey data. Chapter 2 presents a consolidation of lessons learned from previous waves of disruption. It furthers understanding of disruptive innovation by reviewing disruptive business models that have been discussed in the academic literature. Based on a qualitative content analysis, a classification framework proposes five archetypes: 1) matchmakers, 2) standardisers, 3) service providers, 4) open collaborators, and 5) performance reducers. Chapter 3 adds to discussions on theorising the entrant as a proactive strategic actor. Drawing on the strategic alliance literature, the chapter explores how entrants strategically configure an alliance portfolio to pursue a disruptive path despite an interplay with incumbents. Based on longitudinal research, the development trajectories of two disruptive entrants in the German fashion retail and insurance industries are studied. The findings demonstrate how entrants engage in early network building by configuring an alliance portfolio with partners unaffected by the disruption. Furthermore, how entrants have used the power of their alliance portfolios to combine social and timing defence mechanisms to manage the interplay with incumbents and guard against dissuading influences is discussed. In Chapter 4, the discussion of the entrant as a strategic actor is extended. Specifically, dynamics involved in developing and growing a multi-sided disruptive platform are investigated. The longitudinal study proposes three mechanisms through which the entrant leverages relationships with its multiple platform sides. 1) ‘Guarded inception’ involves collaboration with a knowledgeable partner unaffected by disruption to overcome the chicken-and-egg problem quickly. 2) ‘Activating force multipliers’ entails the strategic orchestration of complementors contractually tied to the entrant and working to extend the entrant’s value network. Enabled by these two mechanisms, the entrant is 3) ‘building on others’ to develop the platform along a disruptive path while circumventing internal limitations and external resistance. Chapter 5 presents a general model in which relationships are integrated, as has been called for in disruptive innovation debates. According to survey data on German companies, it can be suggested that value proposition innovation activities regarding new offerings and channels fully mediate the relationship between dynamic capabilities and disruptive innovation. This thesis explores under-theorised facets of the disruptive innovation phenomenon while supporting attempts to generalise more established theoretical statements further. In addition to contributing to the construction of a theory of disruptive innovation, the thesis delivers prescriptive guidelines for corporate managers and entrepreneurs on how to manage business model innovation. This work thus paves the way for further studies on disruptive innovation, ultimately fostering this emerging intellectual field.

AB - In a world of continuous change, companies’ conventional modes of doing business are being disturbed at an ever-increasing pace. Hence, scholars from the innovation and management domains are discussing innovation-induced market changes. The concept of disruptive innovation captures a portion of these changes. Disruptive innovation describes how new entrants gain a foothold in a niche market before moving upmarket and challenging powerful incumbents. From its emergence in the mid-1990s, the concept of disruptive innovation was first theorised with a focus on technology. Since 2006, the debate has shifted focus, and the business model is acknowledged as the decisive vehicle that spurs related market dynamics. Given the complexity of disruptive innovation, this thesis builds on multiple theoretical streams to further extend our understanding of companies’ strategic management choices in the face of disruptive innovation. An integration of elements from business model innovation, strategic alliances, platform development and growth, and dynamic capabilities enables a complementary picture of the levels of disruptive innovation. This research is guided by the following question: ‘how do companies manage business model innovation along the process of disruptive innovation?’ Following a sequential mixed methods approach, this research uses publications, interview data, archival data, and survey data. Chapter 2 presents a consolidation of lessons learned from previous waves of disruption. It furthers understanding of disruptive innovation by reviewing disruptive business models that have been discussed in the academic literature. Based on a qualitative content analysis, a classification framework proposes five archetypes: 1) matchmakers, 2) standardisers, 3) service providers, 4) open collaborators, and 5) performance reducers. Chapter 3 adds to discussions on theorising the entrant as a proactive strategic actor. Drawing on the strategic alliance literature, the chapter explores how entrants strategically configure an alliance portfolio to pursue a disruptive path despite an interplay with incumbents. Based on longitudinal research, the development trajectories of two disruptive entrants in the German fashion retail and insurance industries are studied. The findings demonstrate how entrants engage in early network building by configuring an alliance portfolio with partners unaffected by the disruption. Furthermore, how entrants have used the power of their alliance portfolios to combine social and timing defence mechanisms to manage the interplay with incumbents and guard against dissuading influences is discussed. In Chapter 4, the discussion of the entrant as a strategic actor is extended. Specifically, dynamics involved in developing and growing a multi-sided disruptive platform are investigated. The longitudinal study proposes three mechanisms through which the entrant leverages relationships with its multiple platform sides. 1) ‘Guarded inception’ involves collaboration with a knowledgeable partner unaffected by disruption to overcome the chicken-and-egg problem quickly. 2) ‘Activating force multipliers’ entails the strategic orchestration of complementors contractually tied to the entrant and working to extend the entrant’s value network. Enabled by these two mechanisms, the entrant is 3) ‘building on others’ to develop the platform along a disruptive path while circumventing internal limitations and external resistance. Chapter 5 presents a general model in which relationships are integrated, as has been called for in disruptive innovation debates. According to survey data on German companies, it can be suggested that value proposition innovation activities regarding new offerings and channels fully mediate the relationship between dynamic capabilities and disruptive innovation. This thesis explores under-theorised facets of the disruptive innovation phenomenon while supporting attempts to generalise more established theoretical statements further. In addition to contributing to the construction of a theory of disruptive innovation, the thesis delivers prescriptive guidelines for corporate managers and entrepreneurs on how to manage business model innovation. This work thus paves the way for further studies on disruptive innovation, ultimately fostering this emerging intellectual field.

KW - archetypes, business model, business model innovation, disruptor's dilemma, disruptive innovation,

KW - dynamic capabilities, platform, strategic alliances, topic modeling, value proposition innovation

M3 - PhD-Thesis - Research and graduation internal

SN - 9789464191356

PB - Gildeprint

CY - Enschede

ITNG 2021 18th International Conference on Information Technology-New Generations pp 427–434 Cite as

Disruptive Technologies for Disruptive Innovations: Challenges and Opportunities

• Amjad Gawanmeh 15 &
• Jamal N. Al-Karaki 16  
• Conference paper
• First Online: 17 February 2021

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1346))

Disruptive technologies continuously and significantly alter the way people communicate and collaborate as well as the way industries operate today and in the future. To create new business models and opportunities, several combinations of disruptive technologies are being introduced nowadays. Among these technologies, cloud computing, IoT, Blockchain, artificial intelligence, social networks and media, big data, and 5G are mostly used. For instance, Blockchain technology made distributed solutions feasible and popular. On the other hand, big data and the social media are two contemporary technologies which lament significant impact on business and society. This paper presents a holistic approach to integration perspectives of these technologies considering many challenges like security and privacy. This paper also surveys the most relevant work in order to analyze how some of these technologies could potentially improve each other.

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Gawanmeh, A., Al-Karaki, J.N. (2021). Disruptive Technologies for Disruptive Innovations: Challenges and Opportunities. In: Latifi, S. (eds) ITNG 2021 18th International Conference on Information Technology-New Generations. Advances in Intelligent Systems and Computing, vol 1346. Springer, Cham. https://doi.org/10.1007/978-3-030-70416-2_55

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ORIGINAL RESEARCH article

The role and meaning of the digital transformation as a disruptive innovation on small and medium manufacturing enterprises.

• 1 Faculty of Organisation Studies in Novo Mesto, Novo Mesto, Slovenia
• 2 Faculty of Management, University of Primorska, Koper, Slovenia
• 3 Faculty of Organizational Sciences, University of Maribor, Maribor, Slovenia
• 4 Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, Slovenia

The research reported in this paper explores the impact of digital transformation as a disruptive innovation on manufacturing SMEs. The research is based on a qualitative Delphi study encompassing 49 experts from eleven EU countries. The paper aims to demonstrate how disruptive innovations affect organizational changes and determine critical factors in organizations that impact the initiating and promoting R&D of disruptive innovation. We discovered that disruptive innovations impact product/process development methods, new production concepts, new materials for products, and new organization plans. Additionally, we identified organizational changes related to the development and use of disruptive innovations in the future. We also indicate how disruptive innovations influence social and technological changes in the organizational environment. The analysis also disclosed three main groups of disruptive innovations and their impact on future smart factory development, namely the following: technological changes, the emergence of innovative products, business models and solutions and organizational culture as one of the crucial key success factors. The analysis also examined the enablers of the successful development/introduction of disruptive innovations, wherein internal and external factors were determined. Additionally, we presented obstacles and the approaches necessary to mitigate them. We can conclude from the findings that in the timeframe of 5–10 years, only the SME that uses/develops disruptive innovations will survive in the market. However, the companies do not always have a clear idea of the meaning of disruptive innovations. Therefore, it is important to set clear goals regarding the achievement of disruptive innovations in companies. It is also necessary to creatively apply presented instruments enabling improvement of organizational changes and apply some additional concepts, which we have suggested.

Introduction

The emergence of disruptive innovation theories dates to 1995, when Bower and Christensen (1995) published the article entitled Disruptive Technologies: Catching the Wave, which outlined the thesis that innovation drives corporate growth. Over the past 25 years, this thesis has become a guide for entrepreneurs and managers. Scholars usually ask why industry leaders do not remain leaders when technological or market changes occur. The answer can be found in the fundamental idea of disturbances theory as a tool that predicts behavior ( Dillon, 2020 ). Its core value lies in the ability to evaluate and predict within the organization. The ability required by the organization is then one of choosing the right strategy and avoiding the wrong one ( Shang et al., 2019 ). Such an instance is presented by the sale of the laptop IBM program to Lenovo, which is probably one of the most essential business decisions contributing to the continued growth and survival of IBM.

Disruptive innovations are defined as those based on which a product or service has been developed that incorporates a technology initially introduced in simple applications at a lower market price range ( Christensen et al., 2018 ). These products or services are affordable in their original form. Disruptive innovations are not considered breakthrough innovations or ambitious upgrades of existing products or services that would dramatically change business practices and business models. Instead, they consist of straightforward and affordable products and services. Competitors recognize the market potential of such products and services, which are capable of transforming a particular industry. There is a knock-out effect of competition on the incumbent producers. They recognize factors of the primary producer (such as an internal organization) that prevent further product development and market penetration in compliance with predicted customer needs and expectations ( Christensen et al., 2013 ; Dillon, 2020 ).

While work automation and computerisation were the critical paradigms of the Third Industrial Revolution (1960-2010), the Fourth Industrial Revolution (also named Industry 4.0) brought the digitalisation and informatisation of processes. Industry 4.0 can be understood as a broad socio-technical paradigm ( Mariani and Borghi, 2019 ). It presents a policy concept for increasing economic growth, which has fostered the emergence of innovation-based entrepreneurship, and which is based on development and research, deregulation, increased risk capital financing and international protection of intellectual property ( Christensen et al., 2018 ; Herrmann, 2019 ). The networking of the economy as a strategic tool for acquiring knowledge and information and connecting people with expertise in a modern knowledge society is crucial. The networking of businesses (e.g., incubators and technology parks) offers synergies in the joint management of information, knowledge and human resources. Knowledge and information become crucial for success in the Fourth Industrial Revolution ( Kabir, 2019 ). The organization is required to do as much as possible, including optimizing resources, reducing costs per unit produced and enabling greater efficiency. Higher productivity with cost optimisation means a competitive organizational advantage. From the position of value and the value system, it is also vital to understand the current direction: striving for a balance between business and private life, a creative environment and the possibility of self-realization ( Martin-Rojas et al., 2019 ). The new phase of evolution is connected with the development of the social superstructure and occurs only if suitable conditions are created in the broader social environment, namely the development level of information knowledge, individual consciousness, and attitude toward the environment ( Nanterme, 2016 ; Bongomin et al., 2020 ).

During the Third Industrial Revolution, enterprises developed technologies that reduce cost and complexity. The development of technological processes has also enabled enterprises to produce more technologically advanced and higher quality products and services and develop new business models. However, in Industry 4.0, manufacturers are being challenged by the digital transformation, in which niche technologies, together with the Industry 4.0 concept, are understood as disruptive innovations. The most important developmental step within Industry 4.0 is establishing cyber-physical systems (CPS) which connect the physical environment and cyberspace ( Ren et al., 2015 ; Lu and Xu, 2018 ). Within the systems, mechanisms are created that enable interaction at the human-to-human, human-to-machine and machine-to-machine level along the entire value chain ( Kagermann et al., 2013 ). These processes affect changes in organizational culture and become an increasing challenge for companies and society, as the involvement of humans in the processes of direct communication and collaboration with the machine as an equal partner brings new challenges, such as the resistance of employees, the fear of replacing humans with machines and artificial intelligence-based technology, and the question of the adequacy of the skills necessary to manage organizational processes in the context of smart manufacturing ( Hirsch-Kreinsen, 2016 ; Kiel et al., 2017 ; Seeber et al., 2020 ).

In manufacturing companies, the integration of CPSs into production creates cyber-physical production systems (CPPS) ( Schiele and Torn, 2020 ). These systems become increasingly important in smart factories for creating connections along the entire supply chain (connection with suppliers – the company’s external environment) ( Roblek et al., 2020 ). However, in the enterprise’s internal environment, changes in the production processes, wherein smart factory factors such as the industrial internet of things, CPPS and production systems consisting of one or more CPS come to the fore ( Panetto et al., 2019 ). CPS is understood as a physical object with a built-in system in which the control process unit (computer power supply) is located, the industrial cloud, whose goal is to store, analyze and share data, with some form of network connectivity ( Mabkhot et al., 2018 ). Thus, smart factories strive for self-organization based on establishing automatic machine configuration and process optimisation, enabled by the decentralization of production control. Innovative production process control software influences the transformation of shop floor management by introducing advanced technological processes based on lean management philosophy. For example, the Enterprise Resource Planning (ERP) at the planning level (top floor) uses objective performance data that captures all resources of the enterprise (shop floor) in real-time. The Manufacturing Execution System (MES) influences the improvement of production processes. It can connect production data and ERP data, including business planning that includes resources, customer requirements and expectations ( Gruber, 2013 ; Oesterreider and Teuteberg, 2016 ).

In addition to CPPS, another characteristic of Industry 4.0 that influences the emergence of disruptive innovations within smart factories is that Industry 4.0 is based on and driven by technological development, represented by both self-oriented production manufacturing and service-oriented architects ( Xu et al., 2018 ; Müller, 2019 ; Oztemel and Gursev, 2020 ). Technological development has influenced the emergence of smart products and services. It can be concluded that the result of Industry 4.0 is seen in the concept of smart factories, which is based on the intelligent production of smart, personalized products and within this production has a high degree of collaboration in production networks that also include external partners of the company value chain ( Wang et al., 2017 ; Zhong et al., 2017 ; Frank et al., 2019 ).

The main objective of the research study is to identify disruptive innovations and understand their impact on future organizational agility. The paper also aims to present how disruptive innovations affect organizational changes and determine critical factors in organizations that impact the initiation and development of disruptive innovation. We focused on small and medium manufacturing enterprises (SMEs) in the European Union.

Based on these future expectations, the following research question was established:

Research Question: What organizational changes should be expected from SMEs that enable the development and implementation of disruptive innovations and how do disruptive innovations pertaining to organizational changes influence future organizational agility?

The following types of disruptive innovations were analyzed (and it has been estimated that they have an important impact on future smart factory development): (1) technological changes, (2) the emergence of innovative products, business models and solutions, and (3) organizational culture. These concepts enable manufacturing enterprises to reduce costs, improve flexibility and productivity, enhance quality and increase the speed of business processes ( Brunelli et al., 2017 ; Junaid, 2020 ).

The research was conducted in European SMEs because micro, small, and medium-sized enterprises represent 99% of all European Union enterprises ( Müller, 2019 ). The European Union promotes SMEs through various action programs, thus co-financing research programs in SMEs, which enable them a higher level of innovation and competitiveness ( Hessels and Parker, 2013 ). Thus, SMEs have become the most propulsive companies in the EU and represent the European economy’s backbone ( Dabić et al., 2016 ).

The paper consists of the following sections: introduction, followed by conceptual background (theoretical review). The third section includes methodology. The fourth section presents the research results. The paper concludes with a discussion of results and conclusion, including paper limitations, and proposes research in future development trends.

Conceptual Background

The digital transformation in organizations is changing technology and business models. It brings challenges and opportunities for established companies and newcomers in the field of disruptive innovations. One of the most relevant results of the Fourth Industrial Revolution is the smart factory. The transformation of the classical factory into a smart factory begins with the digital transformation, measurements and informatisation of everything related to production systems. However, the development and implementation of Industry 4.0 niche technologies [advanced robots, additive manufacturing, augmented reality, simulation, horizontal and vertical system integration, the Industrial Internet of Things (IIOT), cloud computing cybersecurity, big data and big data analytics] for a manufacturing enterprise represents a disruption to the innovation that is transforming production ( Brunelli et al., 2017 ). For example, Bruer et al. (2018) and Tortorella et al. (2018a) examined the connection between lean manufacturing and Industry 4.0. Ben-Daya et al. (2017) gave attention to the connections between the Internet of Things (IoT) and supply chain management. Liu et al. (2014) , Li et al. (2017) and Oettmeier and Hofmann (2017) pointed out the influence of additive manufacturing on processes and performance in the supply chain. Ivanov et al. (2016) presented a dynamic model and algorithm for short-term supply chain in smart factories. The short-term smart factory supply chain is by their opinion based on “temporal machine structures, different processing speed at parallel machines and dynamic job arrivals.” New research regarding supply chain management research ( Chang et al., 2020 ; Venkatesh et al., 2020 ) focuses on blockchain technology and its disintermediation effects. However, niche technologies as disruptive innovations also influence the organizational culture ( Sultan and van de Bunt-Kokhuis, 2012 ; Tortorella et al., 2018b ). Based on previous research into disruptive forces occurring in the industry, five crucial manufacturing disruptive methodologies that enable smart manufacturing can be highlighted. These five disruptive forces are ( Li, 2016 ; McKinsey & Company, 2018 ):

(1) Connectivity-driven business models: The development and widespread availability of Internet technologies in the 21st century have made connectivity an essential factor in the emergence of new business models, among which the monetisation of data is a significant challenge. It is characteristic of the age of digitisation that software has become much more important than hardware. Interaction with customers is increasingly digital, in many cases managed without intermediaries, and takes place via digital industry platforms such are Amazon Web Services or, in the automotive industry, Mercedes Me Connect or Lexus Enform. Intel enables organizations implementing IoT solutions to connect almost any type of device to the cloud through their system architecture. It does not matter whether the device is connected to the native internet. IBM Watson technology platforms offer companies the opportunity to extend cognitive computing to IoT, and Microsoft Azure IoT platforms help companies to connect devices, prepare an analysis of previously unused data, and integrate business systems ( Ionut Pirvan et al., 2019 ). Gawer and Cusumano (2013 , 417) defined industry platforms as “products, services, or technologies that act as a foundation upon which external innovators, organized as an innovative business ecosystem, can develop their complementary products, technologies, or service.”

(2) Artificial Intelligence and autonomous systems: industrial companies are increasingly investing in robotics and machine learning. These investments enable them to develop technologies that enable the further development of the company’s core activities (for example, the development of an automatic vehicle for transporting materials and products within the company) ( Roblek et al., 2020 ). Thus, learning data and developing intelligent algorithms becomes a competitive advantage for companies. The development of artificial intelligence and autonomous systems, both concerning production and incorporation into products, has already had and will continue to have an even more significant impact on the entire industry ( Oztemel and Gursev, 2020 ).

(3) Internet of Things (IoT): the basis for evaluation, integration and optimal process control is process-related data. The data is obtained from measurements performed by different sensors (IoT). Intelligent sensors with an integrated microprocessor play an essential role in measuring and enabling their rapid digitalisation. Integrated intelligent sensors enable the execution of logical functions, two-way communication and adaptation to environmental changes, decision making, self-calibration and self-testing in start-up situations. The sensors are becoming smaller and more user-friendly. The IoT can be described technically as a combination of sensors such as RFID, other communication devices (i.e., embedded computers), CM applications, Enterprise Resource Planning (ERP) integration and business intelligence technology ( Mabkhot et al., 2018 ). It is essential in manufacturing to expand the role of IIoT, CPPS and production systems consisting of one or more CPS. The CPS represents a physical object with an embedded system containing a control processing unit (computer power), the industrial cloud that can store, analyze and exchange data, and form a network connection. The emergence of CPPS in any production system enables economic, social and even ecological benefits ( Thiede et al., 2016 ). McKinsey Global Institute predicts that the IoT potential is 10–20 percent energy savings and a 10–25 percent improvement in work efficiency ( McKinsey & Company, 2018 ). However, according to casual theory, the question arises as to whether big data eliminates the need to search for causality? Here, it is necessary to first pay attention to the fact that organization data does not represent the phenomenon itself, but it is necessary to understand it as representational of this phenomenon. The purpose of providing continuous research within organizations, communities, and individuals is to reveal new insights by creating new data within new categories. It is necessary to be aware that big data overlaps or neglects irregularities unless we enable this with a search-analytical algorithm. The problem is that big data is much more focused on correlation than on causality and thus ignores average events or conditions ( Song and Taamouti, 2019 ; Wamba et al., 2020 ).

(4) Electrification: the Fourth Industrial Revolution concerns the sustainability aspect of production and the environmental aspect, and the technical aspect of converting fossil energy to renewable energy and resource efficiency. However, environmental legislation and customer demand for sustainable products and services are forcing the industry to manufacture products that use electricity (e.g., electric cars) and other renewable energy sources ( Moldavska and Welo, 2019 ).

(5) Cybersecurity: the increasing connectivity both within companies (man to machine and machine to machine) and between companies (company to company), companies and consumers (company to the customer) and other systems such as defense, transport, and banking reminds us of the importance of cybersecurity. As more and more closed systems open, there is a more significant threat to both work and property processes (such as industrial espionage). It is estimated that the cybersecurity market’s annual growth will be 5–10 percent by 2025 ( McKinsey & Company, 2018 ). Companies have, therefore, begun to introduce the skills required for cybersecurity. Particular views of industry leaders suggest that they see cybersecurity as a battlefield for competitive advantage and diversity ( McKinsey & Company, 2018 ).

Digitisation and informatisation enable the connecting of (smart) factories with other smart infrastructure elements – people, machines, and products. It is about connecting the entire value chain throughout the lifespan. People are involved as customers, constructors, technologists, managers and enhancers, repairers and analysts ( Zhou et al., 2018 ). It can be concluded that connectivity enables organizations to adapt their systems to the needs of their customers in all aspects, specific requirements, quantities, deadlines and delivery points. The main challenges that organizations face in the digital transformation framework are standardization, security, and IT infrastructure. The real establishment of mentioned elements in the broader industrial environment will take several years, which is why some prefer to use the word evolution instead of the term ‘industrial revolution’ ( Alvarez-Pereira, 2019 ).

In the context of research in the field of various manufacturing companies (breweries, automotive, food, textile, footwear industry, etc.), various authors (e.g., Yoo et al., 2012 ; Nosalska et al., 2019 ; Osterrieder et al., 2020 ) note that, in the context of Industry 4.0, digital transformation is coming which will lead to the emergence of smart factories. The digitalisation of production also affects customer requirements and business model change, the emergence of the digital (smart) supply chain ( Garay-Rondero et al., 2020 ; Schniederjans et al., 2020 ), additive manufacturing technologies ( D’Aveni, 2018 ) and increases the competitiveness of companies. The importance of disruptive innovations are noticeable in the context of full automation, robotisation and the development of manufacturing technologies that allow a higher degree of interconnectivity (IIoT), leading to increased communication between machines and local data processing. The research conducted in various German manufacturing industries shows that the machine and plant engineering companies are mainly facing changing workforce qualifications, while the electrical engineering and information and communication technology companies are mainly concerned with the importance of different critical partner networks, and automotive suppliers predominantly exploit IIoT-inherent benefits in terms of increasing cost efficiency ( Arnold et al., 2016 ).

Hamzeh et al. (2018) researched the importance of technology and the Industrial Revolution concept for SMEs. The research was conducted among SME consulting managers who believed that technological development based on Industry 4.0 technology innovation would impact production costs, improve agility, and enhance service offerings. It should be noted that this is only a prospective study carried out among a very heterogeneous group of SME consulting managers. Chan et al. (2019) were attempting to determine how SMEs achieve the agility to respond to disruptive digital innovation. Their findings show “that for SME; mitigating organizational rigidity is enabled by the mechanism of achieving boundary openness while developing innovative capability is enabled by the mechanism of achieving organizational adaptability. At the same time, given the inherent challenges of resource constraints, SMEs also need to balance the tension of organizational ambidexterity”.

The transformation of traditional factories into smart factories will provide new insights into how disruptive innovations technology affects business process transformation, agility, value chain transformation, organizational culture, and human resource policy changes ( Loonam et al., 2018 ). However, management in organizations must be aware that organizational and business issues remain the same in the age of smart organizations. The forces that cause disruptions are constant and affect both the internal and external organizational environment (e.g., supply chains which are transforming in the value chains) ( Akkermans and Van Wassenhove, 2018 ). To ensure the successful operation of organizations and their long-term existence, leaders (often founders or significant shareholders) must provide adequate resources in the form of tangible and intangible assets. Therefore, they must be aware of the importance of acquiring knowledge that will enable the organization to cope with disruptive events and form a foundation on the basis of which management will be able to react to disruptive forces in a timely manner and provide a system for continuous management of disruptive events ( Jaques, 2017 ). In doing so, the management must be aware of the importance of disruptive innovations theory and, on this basis, be able to predict what will happen without the hindrance of personal opinions ( Wördenweber and Weissflog, 2006 ).

Organizations that want to be successful disruptive innovators must embed in their organizational culture the mindset that disruptiveness is not the creation of something new or breakthrough and that disruptive innovations are not events but a process in which resources are allocated within the organization, with a view to continuous technological evolution and meeting the changing needs of existing and potential new consumers ( Rastogi et al., 2019 ). As part of its strategy, management must be aware of the importance of disruptive innovations policies within the Fourth Industrial Revolution. To this end, the organization’s strategy includes the importance of developing and adapting the system, organizational culture, organizational processes and other factors that enable the provision of fluidity even under reduced innovation conditions ( Jaques, 2017 ; Hopp et al., 2018 ).

Szymańska (2016) and Mohelska and Sokolova (2018) explained that for ensuring success in the new work environment created by the Industry 4.0 era, it is crucial that organizational culture must be characterized by openness to various fields of activity. A new type of culture requires a new, open system of values, standards, thinking patterns, and actions perpetuated in the organization’s social environment, and contributing to its goals. The organizational culture in the Industry 4.0 era is primarily open to the environment, supports extensive cooperation therewith, provides freedom of relations, uses the potential of employees and external partners, and is open to new knowledge, changes, and sometimes to the resulting mistakes. Moreover, it focuses on implementing unique visions and strategies while ensuring discipline and successfully integrates participants in the described relationships around new activities ( Al-Haddad and Kotnour, 2015 ).

Methodology

Delphi methodology.

Most Delphi researchers focus on the reliable and original research of ideas or advancing new information, which is useful in making important (strategic) decisions. Delphi studies are often used in deductive research but can be combined with data collected with qualitative methods that ensure a more pragmatic approach to instrumentalisation ( Rowe and Wright, 1999 ). Consequently, this approach also allows for methodological triangulation ( Yin, 2002 ), improves validity ( Yin, 2013 ) and increases contextual understanding of the phenomena ( Fiss, 2009 ).

The Delphi method is used particularly for predictions and forecasts concerning the future development of technology and the impact of new technologies on society and the economy. It is based on the statistical processing of collected opinions obtained from experts in a specific field. The Delphi method is a structured scientific method with clear rules and procedures. The experts are asked to answer some pre-selected questions, each on its own, and then the “average answer” is calculated. It is assumed that there are no “correct” answers, but the approach results in a free estimation of the probability that some events will occur. After collecting, processing and submitting answers to the same questions, definitive predictions are made ( Higgins, 1994 ). The Delphi method’s key features are anonymity among survey participants, structured feedback that experts receive after giving opinions and allowing them to adjust their previous opinions until they reach an agreement ( Hsu and Sandford, 2007 ). Usually, the Delphi method involves two to three rounds of exchange of opinions between experts and the researcher ( Adler and Ziglio, 1996 ). Two are considered adequate ( Boulkedid et al., 2011 ; Gary and Heiko, 2015 ) as the addition of further rounds adds a further administrative burden and places pressure upon participants that results in lower response rates ( Gary and Heiko, 2015 ).

According to Loo (2002) , the Delphi method can be used to forecast the future for strategic management and organizational development, among other potential applications for organizational management. Okoli and Pawlowski (2004) explained that the Delphi method was recognized as a widespread instrument in information systems research to identify and evaluate executive decision-making issues. Hallowell and Gambatese (2010) imply that Delphi technology is used in construction engineering and construction management when conventional methods fail because the latter may not be suitable for research involving disruptive factors and require sensitive data access. The Delphi technique is valued in such cases because it enables researchers to obtain highly reliable data from certified experts through strategically designed surveys. For this reason, we have chosen the Delphi method for our research. It helps us to establish procedures for obtaining and refining expert and professional opinions in the field.

Delphi Study Design

The survey was conducted in two rounds. The Delphi study’s first round includes open-ended questions about expectations pertaining to the introduction of disruptive innovations in an organization, challenges experienced in introducing disruptive innovations, and steps for a successful introduction of disruptive innovations. The survey questionnaire was prepared in accordance with the questionnaire used in the MIT Sloan Management Review and Boston Consulting artificial intelligence survey ( Boston Consulting Group, 2020 ). The questions were modified in accordance with the disruption innovation theme of our research. We tested the questionnaire on a sample of 12 persons that we had previously used in the survey. Following the comments of the participants, some minor mistakes have been addressed and complementary material was added to some questions in accordance with the topic of the research.

The questionnaire with four open questions was prepared in a survey tool named One Click Survey or 1KA ( One Click Survey, 2021 ), and a link to the questionnaire was sent by email. The first question was: What disruptive innovation have you introduced into the organization and your strategy for further development? The second question was: What effect has disruptive innovation had on your organization so far? The third question was: What organizational changes do you think would result from disruptive innovations in the future (5–10 years)? The fourth question was: What are the key factors in the organization’s internal and external environment that enable further development and disruptive innovations?

Participants were given 10 days to provide their opinion and share expertise insights. Answers to open-ended questions were analyzed using qualitative content analysis. We informed the research participants of the results and allowed them to familiarize themselves therewith.

Based on the qualitative analysis of the answers obtained from round one of the Delphi study, seven expectations concerning the introduction of disruptive innovations in the organization were formulated. In the second round, participants were required to choose the appropriate answer in regard to introducing disruptive innovations in their organization. They were required to choose on the Likert scale the results they expected to achieve by introducing disruptive innovations. The third question includes ranking the predominant challenges that their company has experienced in introducing disruptive innovations. In the fourth question, they were required to specify the most important steps necessary to enable disruptive innovations. In the fifth question, they were asked to describe the importance and role of individual cultural values in developing and implementing disruptive innovations in their company. In the sixth question, they were required to list cultural values by their relevance to disruptive innovations in a changing environment.

We sent the questionnaire prepared using the 1KA tool in the second round to the participants who had answered all the open questions. All survey participants were given 14 days to provide answers. After 1 week, a reminder was sent. At the beginning of the third week, we thanked all participants who had answered the questionnaire. So, it can be concluded that all procedures necessary to undertake the standard Delphi method were followed during the study ( Linstone and Turoff, 1975 ).

A comprehensive approach to the concept of the Delphi method was used. The information concerning the system of criteria and their relative importance creates the conditions for improving the quality of the design of a multi-criteria decision-making basis. The official expert prediction of the qualification weighting criteria was achieved through a methodologically defined, organized and systematized harmonization of individual assessments using descriptive statistical processing of these assessments and predictions ( Hsu and Sandford, 2007 ).

Delphi Panel

For this study, an expert was considered to have a broad understanding of smart manufacturing with specific expertise in at least one of four functional areas: human resource management, information systems management, research and innovation, and manufacturing. To be selected, an expert was required to hold either a middle or high-level managerial position in a smart manufacturing company. Moreover, each expert was required to be accessible and interested in the research results.

Participants

The selection of suitable experts is of special importance. For this reason, the systematic approach was applied to select the appropriate participants for the study. In the first step, within various projects regarding innovations, workshops were conducted which were attended by participants and experts in the impact of disruptive innovations on the small and medium manufacturing enterprises. A list of those experts was formed. In order to meet methodological prerequisites for the Delphi study, the sample of appropriate experts was selected by applying various criteria, i.e., both genders were included in the study, from different work position levels (from board members to operation workers), years of work experience, country, and educational level. As a heterogeneous group of experts reflects the positively cognitive biases of the participants ( Winkler and Moser, 2016 ), an emphasis was placed on an adequate heterogeneity of selected experts. Overall, a total number of 92 experts was identified and invited to participate in the study. All of them were contacted. By the end of the study, 49 experts from eleven countries (Slovenia (14), Italy (3), Spain (2), Hungary (5), Croatia (7), Czech Republic (5), Austria (3), Sweden (2), Germany (7), and Malta (1)) had completed both rounds of the Delphi study. Therefore, the participants’ final sample is purposive and consists of two board members, fifteen managing directors, seven technology directors, seven heads of business units or department, eight experts, three consultants, and seven operation workers. Their SMEs are, on average, more than 10 years old, with more than fifty employees, and generate an average of 3.3 million EUR in revenues per year. The SME primary industry is manufacturing, and the primary activity is R&D or product development, project management, strategy management, general management or information technology. They all have experience in using disruptive innovations as disruptive innovations in production, disruptive innovations algorithms and techniques, or disruptive innovations tools as an end-user.

Assumptions and Biases of the Delphi Participants

The expert panel composition was based on identifying, evaluating, selecting, and recruiting relevant research participants. There is no general rule about the size of a Delphi study panel. Thus, the size depends on the purposes of the researcher, the desired heterogeneity, and the availability of the research expert ( Loo, 2002 ). Researchers in past studies have used the Delphi method with 15–35 participants ( McMillan et al., 2016 ) and studies with 40–60 participants ( Kent and Saffer, 2014 ; Roßmann et al., 2018 ). The panel size in this study belongs to the second group and includes experts in digital transformation and smart manufacturing, which has become a complex topic involving different structures and actors, and the number of experts in this field is increasing. In practice, it has been shown that composite panels allow for more accurate estimates, as opposed to more diverse views, thereby reducing the specific polarization of preferences and responses ( Yaniv, 2011 ).

The study involved a large number of stakeholders performing different functions within smart manufacturing. We ensured that the experts came from different countries. Potential experts were identified based on a database search and a network approach. The selection criterion focused on knowledge about smart manufacturing and the practice of a profession in this field. The experts were required to make appropriate statements about the importance of disruptive innovations and their future significance in the context of smart manufacturing. In the next step, we evaluated the experts regarding corporate functions and the importance of disruptive innovations in their smart factory environment.

Research Results

The results of the study are presented in this chapter. Thus, the final rankings are shown, which were obtained based on the data analysis, and we added the explanations obtained through an analysis of the qualitative comments of the participants in the first phase of the study.

We decided to divide the research topic into two parts because a company’s digital transformation affects the emergence of change and the development of a new organizational culture. Thus, digitalisation in conjunction with the increasingly important informatisation represents an important field of research for the future, which includes not only technological changes in the field of final products (e.g., electric cars) and the robotisation of production and logistics processes (both have consequences for the supply and value chain and future employee structures of companies, etc.), but also raises the question of the emergence of a new organizational culture and leadership with increasing cooperation between humans and machines ( Caruso, 2018 ). The first part addresses the impact of disruptive innovations on the organizations, while the second part presents the impact of the disruptive innovations on the organizational culture.

The Impact of Disruptive Innovations on the Organizations

In the second round of the Delphi study, the participants were first asked about adopting disruptive innovations in their organizations. Figure 1 shows that 48% of the participants think that their organization is on the right track with disruptive technologies, while 24% of the participants think that their organization is behind schedule with adoption and 22% of the participants think that their organization is ahead of schedule in adopting disruptive technologies and 6% of the participants think that their organization has not yet begun to adopt disruptive technologies but plans to do so. None of the participants thinks that their organization has not yet begun to adopt disruptive technologies and does not plan to adopt them.

Figure 1. The level of introduction of disruptive technologies in the organizations ( n = 49; source: authors).

The second question analyzed the % of participants expecting an increase in organizational performance by introducing disruptive innovations. Table 1 shows the listed outcome expectations in accordance with their importance for the participants.

Table 1. Results of participants’ SME achievement expectations by introducing disruptive innovation.

According to the results in Table 1 , the study participants indicated that they expect that 29% of the participants think that the introduction of disruptive innovation will increase sales by 10–20%. 35% of the participants think that there will be an increase in market share by 1–10%, and 37% of the participants think that operating costs will decrease by 10–20%. 27% of participants think business speed and agility will increase by 10–20%, 31% of participants think customer satisfaction will increase by 50–100%, 33% of participants think the new product/service development time will decrease by 10–20%, and 35% of participants think the number of more talented personnel hired and retained will increase by 20–50%.

In the third question, participants were asked to identify and name the three most important challenges for their company in introducing disruptive innovations. Figure 2 shows that the most important challenges for companies in adopting disruptive innovations are the following: lack of the right in-house capabilities (11 votes), tendency to think short-term vs. plan long-term (7 votes), internal politics (5 votes), lack of a dedicated budget (5 votes), over-reliance on legacy technology (4 votes), lack of the right technology/tools (4 votes), cultural resistance (3 votes), lack of formal strategy/plan (3 votes), data silos (2 votes), lack of central coordination/ownership (2 votes), lack of senior management support (2 votes), and one participant indicated no challenges.

Figure 2. The average rank of the most important organizational challenges ( n = 49; source: authors).

In the first part of the Delphi study, participants mentioned in their qualitative comments that a lack of the right technology/tools occurs in their organizations. However, participants do not pay much attention to this problem (or do not perceive it) because they lack the right internal skills and budget. They also mentioned that they have a higher-than-average tendency to think short term while planning long term. In the first part of the study, participants also pointed out the lack of a positive attitude among senior management regarding supporting technology implementation and helping employees overcome implementation or development challenges. Participants also believe there is a lack of central coordination in their organizations regarding ownership. In the qualitative comments, participants also pointed to issues related to over-reliance on outdated technology that, if not addressed, could lead to the creation of a dysfunctional organization. A culture of resistance may be associated with the challenge of a dysfunctional organization.

Concerning the challenge referred to as cultural resistance, the first part of the study examined which organizational culture values correspond to the adoption of disruptive innovations. It was found that the interplay between external and internal environments, technology orientation, and appropriate communication is of great importance. In the context of the development and use of Big Data, organizations are faced with the emergence of large volumes of unstructured data. Therefore, organizations must implement tools based on algorithms (e.g., Hidden Markov Model) to extract terms from data silos. Failure to address this challenge can lead to a dysfunctional organization. Within the internal policies, participants pointed out a lack of methods and procedures.

Participants in the Delphi study’s first part pointed out that disruptive innovations in business processes initially involve some resistance due to lack of internal knowledge, but this can be mitigated with the right methods. Some organizations had problems with employee resistance, especially with all methods, and needed more time for organizational change due to information support.

Participants highlighted the importance of digital transformation, enabling the introduction of new smart factory modules, technological improvements, robotisation (e.g., a laser camera system for seam tracking in mig/mag welding) and virtual (CPS) development. The consequences are apparent in the elimination of operators in the work process as such processes become modified by the deployment of robots. They also mentioned the importance of business methods such as Kaizen-5s and the implementation of 6 Sigma. According to them, disruptive innovations also change product/process development methods, bring new production concepts, new materials for products and new organizational plans (flat organizations, organizational flow changes, and more internal communication). For example, they enable greater effectiveness, real-time information for better decision making, fewer bottlenecks, seam tracking systems to enable better penetration and less dispersion of weld quality, and changes in supply chain management (e.g., the supplier can monitor inventory through online access).

The participants also emphasized that the strategic decision to engage in disruptive innovation is critical to success. Innovation does not arise from inspiration but from a clear, ambitious goal, business excellence, hiring the best talent inside or outside the organization, dedicated funding, and a strict timeline. Positive disruptive innovations include making the organization more agile and flexible. Other disruptive innovations, such as electric cars, bring some risks in the future and opportunities for a greater level of sustainability. Generally, if the disruptive program or product generates a significant cash flow, the organization must adapt to that opportunity.

Regarding the position of what organizational changes will occur in 5–10 years due to the development of disruptive innovations, the participants came to the encouraging conclusion that in 5–10 years, only the SMEs that develop disruptive innovations will survive in the market.

The participants’ comments included full digitisation, more virtual development, a different way of working, new offerings, new knowledge, new production concepts and market opportunities, shorter time-to-market, and collaboration between different market players. They also think that companies will have fewer staff, and supervisors with a higher educational level. Smart factories will need highly educated people and continuous updating of knowledge to manage their systems. Some participants also stated that the paradigm is changing dramatically right now due to the coronavirus, and it is difficult to predict what will happen in the future.

Participants expect that artificial intelligence will have an increased presence in business, especially in regard to big data. In the participants’ opinion, fewer people will require administrative or middle management, especially in middle-sized organizations. They asserted that the decision-making process must be quicker; development times for new products will be shorter; and the niches will become more critical because people will expect personalized products or services. The robotic lines will require different methods of guidance and monitoring. Reorganization of information support will be required, as will the increased awareness of line managers. It can be concluded that the business landscape will change drastically in the coming years as companies that are unwilling to adapt lose their market shares to new companies with new visions and monetisation approaches.

Participants ranked the most important organizational factors capable of enabling the further development of disruptive innovations in the internal and external environment as follows: the cosmopolitanism of the team, which can bring courage, openness and open-mindedness, which drives innovation, communication with people and their consultation, competition in the market, competitiveness, the desire for progress, new working methods, and the gathering of ideas. Helping top management to adjust and urge the adoption of high-level, open-source development toolkits allows a high level of abstraction and rapid development.

Among the internal factors that have proven to be the best and most effective in all aspects are openness to change, willingness to adopt new or innovative business models, organizational culture, budgeting, and external subjects’ willingness to participate. Among the external ones: competition (and cooperation, where complementary technologies are available or have the x-industrial application potential) and environmental friendliness (no safe/clean environment, no existential duration).

The organization’s expectations regarding the results achieved with disruptive innovations are based on the participants’ knowledge of the expected results of disruptive innovations in their organizations.

In the fourth question, participants were asked to mark the most important steps from the list that would enable the successful introduction of disruptive innovations. Figure 3 shows that the participants decided that the most important steps for a successful introduction of disruptive innovations are: investment in the appropriate technologies and tools, communicating strategy, investment in staff training, employee goals and innovation culture. Among the least important steps, participants ranked reducing reliance on older technologies and assigning a board-level or c-level sponsor to the project and senior management sponsorship.

Figure 3. The most important steps to enable the successful introduction of disruptive innovations ( n = 49; source: authors).

The next subsection presents the answers regarding organizational culture changes in organizations due to disruptive innovations. We want to stress that the next subchapter is based on the same questionnaire (questions 5–6), which addresses the impact of disruptive innovations on the organizational culture.

The Impact of Disruptive Innovations on the Organizational Culture

Development of the innovation culture is based on methodological knowledge of disruptive innovations. In question 5, the participants were asked to describe the importance and role of the individual cultural values in developing and implementing disruptive innovations in their organizations. The comments received in response to this question are added to the answers received in response to question 6.

In question 6, the participants were asked to rank the listed cultural values by their relevance in terms of their contribution to disruptive innovations in a changing environment and to provide a qualitative comment. The results are presented in Figure 4 .

Figure 4. Cultural values by relevance, ranked from 1 (most relevant) to 12 (least relevant) in terms of their contribution to disruptive innovations in a changing environment ( n = 49; source: authors).

The cultural values listed according to their relevance are:

(1) Openness to change : The processes of change in SMEs are seemingly independent of each other, but the facts clearly show that they are closely interrelated. Specific social rules (e.g., legal, economic, and ethical) apply to each phase of change. It is important to be aware that change always has a deterrent effect on employees and that employees often feel threatened by innovations, which is why it is necessary to convince them of the benefits of change.

For these reasons, the focus of leadership and management shifts spontaneously from functions and processes closer to direct relations with employees. Managers should be careful, when implementing organizational changes, to establish an appropriate work environment and rules and regulations, because only the efficient use of intellectual resources allows continuous improvement. It is appropriate to have such processes in a firm internal staff in a company that manages these processes.

This distrust of employees toward the introduction of innovative solutions in the company requires that organizational change behavior should be encouraged at all levels of leadership, management, and implementation. Organizations need creative employees who can become involved in strategic thinking processes and can pass on new values, creativity and innovation to other colleagues.

(2) Innovation approach, innovation culture and climate : From the content analysis of the qualitative attitudes of the interviewees, it can be concluded that digitalisation and informatisation stand for the transformation of organizational processes through the use of innovative, disruptive technologies and solutions that will change the supply chain, technology, technological processes, the value chain and the future employee structures of companies. As it can also be seen from the next respondent’s answers, employees expect the emergence of a new corporate culture, increasing awareness of the importance of innovation and introducing new technologies and the interaction between management and employees for mutual cooperative cooperation in developing an innovative environment (including reach goals and creating a list of incentives for employees). Approximately 1–3% of company staff dedicates SME time for innovation, so it is important to stimulate and reward such staff (not only financially but also through other means of motivation – knowing individuals’ cultural values might help managers to obtain the optimum performance from an innovative team). It is important to note that the benefits of innovation are inevitable in the background of innovation culture. According to the respondents’ experiences, people were more inclined to embrace innovation if they saw a benefit to the individual. It is also important to emphasize that it is easier to manage an innovative company when managers and other employees originate from the same technical background because it is then easier to understand the situation in the market and transfer the appropriate knowledge for reaching the set goals. As part of developing cultural values for developing an innovative company, it is necessary to ensure that the natural curiosity of employees is maintained. It is also necessary to consider that better relationships promote the development of the company’s culture and climate toward unification, better understanding, and the achievement of its set goals.

(3) Willingness to acquire new knowledge : Companies must realize that in a modern organization in the Fourth Industrial Revolution, learning must take an active role in operations. Employees who want to educate themselves further to make the organization more sustainable must be encouraged to do so because further education is not connected with costs. The management should know that considerable benefit can be derived from having qualified employees.

(4) Tolerance to failures : the respondents point out the need to consider that mistakes occur in developing and implementing disruptive innovations. According to the respondents, intolerance to mistakes is the biggest obstacle to disruptive innovation. The reaction to mistakes also depends on the employee’s position, so the higher the decision-making level of a person, the more lenient the reaction to mistakes. However, learning experiences are never drawn from a mistake.

(5) Orientation to end customers (clients) : the respondents believe that customer orientation depends on the nature of the company’s products or services. However, awareness of empathy and listening to the customers helps in achieving/satisfying customer needs and thus improving the business.

(6) Trust : according to the respondents, “trust and security” are related, but they are also influenced by the “appreciation and treatment of the employee” by his superiors. Unfairness is just as detrimental to the issue of trust as it is undesirable.

(7) Organization agility : respondents indicate that their companies are dedicated to technological solutions and the openness of ownership/management structures to introducing new technologies.

(8) The propensity to take risks : risk-taking is evident in large new technology projects in organizations. Companies in which the culture discourages risk-taking become moribund. Innovation is 99% failure and 1% success.

(9) Internal organizational participation : internal organizational collaboration is carried out in accordance with employee rules and qualifications. If innovation is perceived as a process, and different departments participate in the development, then the innovation process is more effective and productive.

(10) Communicative: this pertains less to cultural values than it does to the nature of a person’s character – extroverted vs. introverted. However, certain environments can influence good communication and bad communication, so, in part, the community’s cultural values influence the form and scope of the communication action.

(11) Technology orientation : according to the respondents, it is an asset for a company if the owners/managers originate from a technical background: a vision/strategy that is built into the culture needs to be passed on to the other employees.

(12) Entrepreneurship : according to the respondents, no individual would become an entrepreneur if their attitude was not one that is oriented toward exploring opportunities. The difference in how to do so is grounded in moral-ethical standards, which are part of one’s cultural values (also derived from childhood). Certain respondents pointed out that entrepreneurship is tied to making money from innovation. Thus, it might be a good step if management can explain how an innovative entrepreneurial spirit in the company can increase profitability. Among other answers, it is worth noting then that many employees started their careers in start-up companies.

(13) Cooperation : two different relationships emerged between companies: cooperation vs. competition. It is typical for small high-tech companies to cooperate (otherwise, they have little chance of surviving in the larger market). From this point of view, the younger generation’s cultural values are somewhat different from those of the older generation or those of the larger companies in which there is a competitive relationship between companies. In a cooperative relationship with external companies, communication occurs at the level of the most qualified professionals.

The cooperative relationship is gaining importance because the innovation life cycle is becoming shorter, and companies cannot afford to develop everything themselves. Therefore, the involvement of external parties plays an important role (e.g., outsourced development of partial technologies, test procedures, supply chains, etc.).

Following the analysis of organizational culture factors and innovative SMEs, it is possible to form the key meanings of the individual roles of organizational culture. Thus, it is important for SMEs, which want to be leaders in innovative development that the leaders and managers of the company enable the knowledge and information to be shared between all key personnel as quickly as possible. Within the framework of enabling an innovation approach and the innovation culture and climate, it is necessary to ensure that the emergence of new technologies does not have a negative impact on employees (the issue of dismissal of employees). Thus, the key social capital must be represented by employees, who will be given support in the form of guidance and motivation supplied by the company’s management to dedicate themselves to development without possible existential threats. It is important that employees trust their managers and leaders. As part of knowledge management, which we understand as a long-term and complex process of knowledge creation, transfer, and use within an individual organization, companies must provide the function of knowledge transfer and use as we have already established and enable employees to have constant access to the acquisition of new knowledge. The company must therefore encourage and motivate employees to attend various forms of education. It is also important for an innovative organization to accept certain risks as one of the factors. Therefore, a certain level of attention must be paid to risk management and tolerance to the failures in R&D. The company’s technological infrastructure must enable the customer to fulfill almost every wish regarding the company’s products efficiently and with high quality. However, the technology infrastructure alone is not enough to fulfill the wishes of customers in the best possible way. Of course, the essential factor of the company philosophy must become an absolute focus on the customer and on the best educated and most highly motivated employees. Within the framework of organizational agility, both business owners and management must focus on permanent investment in new technologies. It is beneficial for the company if the owners and management support the technological orientation of the company, and define this in the vision/strategy of the company. An innovative entrepreneurial spirit is also encouraged in innovative organizations. In doing so, the company must provide employees who join the internal enterprise with payment outside the usual salary system in the organization. The employee must thus agree to a reduction in salary in the event of business failure, which is understood as entrepreneurial risk. In the event of success and generated profit, the individual is, of course, rewarded. An internal entrepreneur is, of course, different from a classic entrepreneur. The basic characteristic of an internal entrepreneur is that they are directed by the management of the company, while a classic entrepreneur is completely independent. The internal entrepreneur is also less risk-averse, but at the same time knows that in the event of failure, they will remain relatively safe within the company. Finally, we must mention the importance of developing a cooperative culture, which is important for creating a positive climate between individual organizations involved in the development or manufacture of a particular product.

Discussion and Conclusion

A Delphi method was applied as a tool in order to identify points of agreement about disruptive innovations within a group of experts. The study’s goal was to determine the answer to the research question: What organizational changes should be expected from SMEs that enable the development and implementation of disruptive innovations and how do disruptive innovations pertaining to organizational changes influence future organizational agility?

This section will briefly summarize the key results and add the discussion, which illustrates the results and enables a wider picture and a comprehensive answer to the research question.

At the beginning of the research, the participants were asked how they define disruptive innovations. We discovered that participants have very similar definitions of what disruptive innovation means. The definition could be summarized as innovations based on developing specific and affordable products or services. They are not considered to be breakthrough innovations or ambitious upgrades of existing products or services. Into their organizations, they introduced, for example, the following disruptive innovations: several modules for the smart factory, different approaches to regular workdays, product innovations (e.g., products that reduce emissions in diesel gate engines), technological improvements (e.g., the technology that changes the production of components for electric motors), innovations of supply models and working processes.

In our opinion, a significant part of the identified and presented examples of disruptive definitions are only partially compliant with the basic definition of disruptive innovation. In the work of Christensen (1997) , disruptive innovation is defined as something that creates a new value by disrupting existing value network(s), resulting in displaced dominating market-leading organizations or dominating products and services. Such innovations are more often than not produced by newcomers or even complete outsiders rather than existing market-leading entities. Moreover, “Disruption” often describes a process whereby a smaller company with fewer resources can successfully challenge established incumbent businesses ( Christensen et al., 2013 ). The Disruptive Innovation is not each innovation, but those that significantly affect the way a market or industry functions.

Before continuing with a discussion, we shall provide a synopsis of the second part of the research findings. The participants pointed out that disruptive innovations in business processes initially bring some resistance due to a lack of internal knowledge but can be mitigated with the right methods. Some organizations had problems with employee resistance to all methods and need more time for organizational changes based on information support. Disruptive innovations impact product/process development method changes, new production concepts, new materials for products and new organization schemes (flat organizations, organizational flow changes, and more internal communications). So, they enable higher effectiveness, real-time information for better decision making, fewer bottlenecks, seam tracking systems enable better penetration and smaller spread of weld quality, and changes to the supply chain management (e.g., the supplier was allowed to observe inventories through online access).

Analyzing the “disruptive” innovation examples in this section we can realize that innovation examples are mainly not true disruptive innovations, but often improvements as a result of horizontal enabling technologies such as tracking systems and chain management tools, and ICT/digitalisation implementation. In other cases, the innovation was an implementation of widely accepted management models such as flat organization and improved internal communication. If we merge findings from this and previous paragraphs, it is clear that in many cases we detected a misunderstanding of the term ‘disruptive innovation.’ According to innovation typology ( Nedelko and Potočan, 2013 ; OECD, 2021 ), respondents often presented process and organizational innovations which were new for the company but did not have the disruptive innovation character. This is compliant with the finding by Prof. Christensen that: “In our experience, too many people who speak of “disruption” have not read a serious book or article on the subject. Too frequently, they use the term loosely to invoke the concept of innovation in support of whatever it is they wish to do. Many researchers, writers, and consultants use “disruptive innovation” to describe any situation in which an industry is shaken up and previously successful incumbents stumble. But that’s much too broad a usage.” ( Christensen et al., 2013 ).

Why are we stressing this issue? It is not the basic problem that the respondents do not know exactly what disruptive innovations are. It is more worrying that they might be satisfied with their innovation activities, believing that they properly manage disruptive innovations.

The last part of the summarized results presents the most important organizational factors capable of enabling the further development of disruptive innovations in the internal and external environment. These are as follows: the cosmopolitanism of the team, which can bring courage, openness and open-mindedness, which drives innovation, communication with people and their consultation, competition in the market, competitiveness, the desire for progress, new working methods, and the gathering of ideas. Helping top management to adjust and urge the adoption of high-level, open-source development toolkits allows a high level of abstraction and rapid development. Among the internal factors that have proven to be the most effective in all aspects are openness to change, the willingness to adopt new or innovative business models, organizational culture, budgeting, and external subjects’ willingness to participate. Among the external ones are competition (and cooperation, where complementary technologies are available or have the x-industrial application potential) and environmental friendliness (no safe/clean environment and no existential duration). Regarding the position of which organizational changes will occur in 5–10 years due to the development of disruptive innovations (third research question), the participants drew a satisfying conclusion that in 5–10 years there will be companies that develop disruptive innovations, while the rest will probably not survive in the market. The views regarding organizational changes that will occur in the future include full digitisation, more virtual development, a different way of working, new offerings, new knowledge, new production concepts and market opportunities, shorter time-to-market, and cooperation between different market participants. They also indicate that organizations will have fewer working staff, and supervisors with a higher educational level. Smart factories will require, for the purposes of managing their systems, more people with a higher level of education and continuous updating of knowledge. Some participants also state that the paradigm is currently changing dramatically due to the coronavirus and it is hard to predict what will happen. Participants expect that artificial intelligence will have an increased presence in business, especially in regard to big data, so that fewer people will be needed in administrative workplaces or middle management places, especially in larger companies. Decisions must made more quickly; the time to develop new products will be shorter; the niches will become more critical because people will expect personalized products or services. The robotic lines will require different methods of guidance and monitoring. Reorganization of information support will be essential, as will the increased awareness of line managers.

Based on these interesting research findings, we can make some conclusions. The first obvious finding deals with the business landscape, which is changing drastically and will continue to do some in the coming years. Companies that are not able or willing to adapt are losing their market shares to new companies with “disruptive” visions and monetisation approaches. We also estimate that companies are aware of present and future organizational challenges and mechanisms which are essential for a successful near future (5–10 years) organization, as presented in previous paragraphs. Our research results also reflect the idea of the Top 10 Skills of 2025, introduced by World Economic Forum ( WEF, 2021 ). In addition to the presented key success factors, we would like to explicitly stress the Open Innovation and Triple/Quadruple Helix concept, which are already “a must.” Cooperation with academia is also an important tool for achieving disruptive and breakthrough innovations. Last, but not least, there are also methods available that enable the creation of disruptive innovations ( Likar and Trcek, 2020 ). However, companies are, in our opinion, aware of the necessary organization culture instruments, representing prerequisites for disruptive innovations. But it is not enough to be aware of appropriate key success factors only. It is obvious that these must be applied in a creative and efficient way. Thus, the presented instruments can enable improvement of organizational changes.

Nevertheless, it seems that one aspect is missing – a clear understanding of the term “disruptive innovation.” Companies should understand what disruptive innovations are and set clear goals, i.e., more ambitious disruptive innovation development goals. Only in this way will they be able to focus their potential appropriately and perform all the necessary activities to achieve disruptive innovations and improve business results.

Practical Implications

Based on the results, we prepared a set of practical implications for companies.

Firstly, a clear understanding of the term “disruptive innovation” is often missing. Companies should understand what disruptive innovations are - those that significantly affect the way a market or industry functions. Therefore, they should reconsider and set clear goals, i.e., more ambitious disruptive innovation development goals. Only in this way will they be able to focus their potential appropriately and perform all the necessary activities to achieve disruptive innovations and improve business results. A prerequisite is a clear vision of top management, which should be supported by concrete, clear and focused systemic changes and activities as follows.

It is important to develop employee competencies so that they feel confident to be ready for new challenges. One of the crucial competencies is the desire for progress, readiness to learn, prompt adoption of new working methods, and creativity/innovation orientations. In addition, the development of cosmopolitanism of the team is important as this can bring courage and open-mindedness, which drives innovation and competitiveness.

How to achieve this in praxis? The company should systematically develop these competencies in employees, using well prepared and focused training, communicating with them and giving them their own (top management) example. In addition, target competencies should be selection criteria when hiring and employing new staff. What is more, it is not enough to focus on employees. The company should also require such competencies from external partners.

One of the crucial areas is related to organizational culture improvements. It should support openness to change, the willingness to adopt new or innovative business models, and new production concepts. Therefore, companies should strive more toward flat organizations and enable organizational flow changes. They should strive toward the improvement of internal communication, enabling the knowledge and information to be shared among all key personnel as quickly as possible. Attention should be given to the company’s knowledge management, meaning a long-term and complex process of knowledge creation, transfer, and use. The next important aspect is related to motivation and the rewarding of individuals/employees, especially in the event of business success. When focusing on disruptive as well as other types of innovations, it is essential to accept certain risks and introduce a clear tolerance model for the failures. Special attention should be focused on improvements in the supply chain management. Obviously, the activities should be supported by appropriate budgeting. Last, but not least, trust among management and employees is one of the “hygienic” prerequisites for success.

The open innovation concept should also be implemented. Within this concept, special attention should be paid to cooperation with academia representing an important tool for achieving disruptive and breakthrough innovations.

As to marketing, companies should implement a dynamic market opportunities identification concept as well as provide shorter time-to-market. The research also stressed absolute focus on the customer as an important factor. It should be mentioned that such an approach can also be vague, as the company only focuses on fulfilling the customers’ needs. We think that such a concept can often kill disruptive innovations. Therefore, it is also important to develop breakthrough innovations which are not based directly on customers’ needs but have a clear market acceptance verification.

Enabling technologies should also be implemented, i.e., full digitisation at all company levels. One of these should be focused on the working process, especially within/after the Covid-19 experience. It is related to more virtual development and the adoption of working from home. In addition, artificial intelligence should be considered as a support to various business processes.

Limitations of the Study

A possible limitation of the research is the homogeneity of the participants. It is related to the companies encompassed having different innovation and economic levels. In addition, there are differences between countries. Taking into account these differences, further studies would be welcome. In the future, it will be necessary to carry out studies in the field of SMEs in accordance with their innovation level, economic performance, and business sector. In addition, quantitative approaches would illustrate complementary aspects, but these require an appropriately higher number of respondents. Obviously, it will be necessary to focus on steps that enable the successful introduction of “real” disruptive innovations.

Data Availability Statement

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

Ethics Statement

Ethical approval was not provided for this study on human participants because the research was performed in accordance with relevant institutional and national guidelines. In Slovenia, the consent of ethical commission is required for other types of research (e.g., medical research). For social science research there is no such praxis. But the authors have to stress that our respondents were informed about the research goal and the fact, that their opinion will be used for the analysis and published anonymously. Only those respondents who have agreed with the aforementioned filled out the questionnaire. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Author Contributions

VR: performance of all tasks, analysis, and basic text preparation. MM and BL: concept preparation, involvement in international data collection, writing of parts of text, and supervisory work. FP: concept preparation and supervisory work. All authors contributed to the article and approved the submitted version.

This study was supported by Slovenian Research Agency - ARRS. Programme: P2-0266 Advanced manufacturing technologies for high quality and sustainable production.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords : digital transformation, disruptive innovation, Industry 4.0, Delphi study, SME, smart factory

Citation: Roblek V, Meško M, Pušavec F and Likar B (2021) The Role and Meaning of the Digital Transformation As a Disruptive Innovation on Small and Medium Manufacturing Enterprises. Front. Psychol. 12:592528. doi: 10.3389/fpsyg.2021.592528

Received: 07 August 2020; Accepted: 10 May 2021; Published: 09 June 2021.

Reviewed by:

Copyright © 2021 Roblek, Meško, Pušavec and Likar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Borut Likar, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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What Is Disruptive Innovation?

• Clayton M. Christensen,
• Michael E. Raynor,
• Rory McDonald

For the past 20 years, the theory of disruptive innovation has been enormously influential in business circles and a powerful tool for predicting which industry entrants will succeed. Unfortunately, the theory has also been widely misunderstood, and the “disruptive” label has been applied too carelessly anytime a market newcomer shakes up well-established incumbents.

In this article, the architect of disruption theory, Clayton M. Christensen, and his coauthors correct some of the misinformation, describe how the thinking on the subject has evolved, and discuss the utility of the theory.

They start by clarifying what classic disruption entails—a small enterprise targeting overlooked customers with a novel but modest offering and gradually moving upmarket to challenge the industry leaders. They point out that Uber, commonly hailed as a disrupter, doesn’t actually fit the mold, and they explain that if managers don’t understand the nuances of disruption theory or apply its tenets correctly, they may not make the right strategic choices. Common mistakes, the authors say, include failing to view disruption as a gradual process (which may lead incumbents to ignore significant threats) and blindly accepting the “Disrupt or be disrupted” mantra (which may lead incumbents to jeopardize their core business as they try to defend against disruptive competitors).

The authors acknowledge that disruption theory has certain limitations. But they are confident that as research continues, the theory’s explanatory and predictive powers will only improve.

Twenty years after the introduction of the theory, we revisit what it does—and doesn’t—explain.

Please enjoy this HBR Classic.

• Clayton M. Christensen was the Kim B. Clark Professor of Business Administration at Harvard Business School and a frequent contributor to Harvard Business Review.
• Michael E. Raynor is a director at Deloitte Consulting LLP. He is the coauthor, with Mumtaz Ahmed, of The Three Rules: How Exceptional Companies Think (New York: Penguin Books, 2013).
• Rory McDonald is the Thai-Hi T. Lee (MBA 1985) Associate Professor of Business Administration in the Technology and Operations Management unit at Harvard Business School.

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Disruptive Innovation Theory: What It Is & 4 Key Concepts

• 15 Nov 2016

Disruptive innovation has been a buzzword since Clayton Christensen coined it back in the mid 1990s to describe the way in which new entrants in a market can disrupt established businesses. It’s gained even more prominence in the past two decades as companies like Uber, Lyft, Etsy, and countless other startups have emerged with a goal of changing their respective industries .

For a term thrown around so frequently, it’s surprising how often it’s misunderstood. What does “disruptive innovation” actually mean, and how can today’s businesses—both the disruptors and the disrupted—form an understanding that will allow them to spot potential opportunities and threats?

This post explores disruptive innovation and offers four key concepts that can help you apply the theory to your business.

What Is Disruptive Innovation?

According to Christensen, disruptive innovation is the process in which a smaller company, usually with fewer resources, is able to challenge an established business (often called an “incumbent”) by entering at the bottom of the market and continuing to move up-market. This process usually happens over a number of steps:

• Incumbent businesses innovate and develop their products or services in order to appeal to their most demanding and/or profitable customers, ignoring the needs of those downmarket.
• Entrants target this ignored market segment and gain traction by meeting their needs at a reduced cost compared to what is offered by the incumbent.
• Incumbents don’t respond to the new entrant, continuing to focus on their more profitable segments.
• Entrants eventually move upmarket by offering solutions that appeal to the incumbent’s “mainstream” customers.
• Once the new entrant has begun to attract the incumbent business’s mainstream customers en masse, disruption has occurred.

4 Tips for Understanding the Theory of Disruptive Innovation

1. not all innovation is disruption.

According to Merriam Webster , disruption is "to cause (something) to be unable to continue in the normal way: to interrupt the normal progress or activity of (something)." If this definition is applied to business, then really anything that enters a market and is successful can be seen as "disruptive." At least that’s how the term is often used today.

But this isn’t how Christensen defined it when writing in the 1990s.

An article by Ilan Mochari discusses the misuse of the word disruption when referring to business. As he clarifies, disruption is "what happens when the incumbents are so focused on pleasing their most profitable customers that they neglect or misjudge the needs of their other segments."

2. Disruption Can Be Low-End or New-Market

Disruption can come in different varieties: Low-end disruption and new-market disruption.

• Low-end disruption refers to businesses that come in at the bottom of the market and serve customers in a way that is "good enough." These are generally the lower profit markets for the incumbent and thus, when these new businesses enter, the incumbents move further "upstream." In other words, they put their focus on where the greater profit margins are.
• New-market disruption refers to businesses that compete against non-consumption in lower margin sectors of an industry. Similar to low-end disruption, the products offered are generally seen as "good enough," and the emerging business is profitable at these lower prices.

The main difference between the two types lies in the fact that low-end disruption focuses on overserved customers, and new-market disruption focuses on underserved customers.

3. Disruptive Innovation Is a Process, Rather Than a Product or Service

When innovative new products or services, such as Apple’s iPhone or Tesla’s electric car, launch and grab the attention of the press and consumers, do they qualify as disruptors in their industries?

In the Harvard Business Review , Christensen cautions that it takes time to determine whether an innovator’s business model will succeed. He cites Netflix as an example that didn’t threaten Blockbuster at first; its DVDs-by-mail service didn’t satisfy customers who wanted to get their hands on the latest new release instantaneously. But in shifting to an on-demand streaming model, Netflix siphoned away Blockbuster’s core users before the company could stage an adequate response.

Will the next new launch be a flash in the pan, or a formidable competitor? Keeping a close eye on the process, and being able to determine whether that product or service is evolving its business model to better serve customers’ needs, will help you evaluate the extent of the threat.

4. Choose Your Battles Wisely

If you’re currently an incumbent, you want to be on the lookout for potentially disruptive emerging businesses . It’s important to note, however, that not all new entrants will prove to be disruptive.

Every fire doesn’t need to be extinguished, nor will it threaten your house. If you treat every fire as dangerous because someone else calls it “disruptive,” you’ll soon discover it’s not possible to put every fire out and, in the interim, will waste your resources. The fires you have to worry about are the ones that truly threaten you. Understanding the correct meaning and application of the word “disruption” will help you identify and target true threats.

On the other hand, new entrants can also benefit from achieving a better understanding of disruption, as it will help you identify opportunities to start or scale your business. An understanding of disruption, coupled with Christensen’s other theory of "Jobs to be Done," can help you create products and services that will be desired by customers and, ideally, left alone by incumbents.

Understanding the Impact of Disruptive Innovation

Whether you're an incumbent intent on defending your market share and profits or you are a new entrant seeking to grab a piece of the pie, understanding disruptive innovation as a process can offer valuable insights you can incorporate into your business plan .

Do you want to learn more about disruption and explore other theories from Professor Christensen? Our six-week online Disruptive Strategy course will equip you with the tools, frameworks, and intuition to develop executive-level strategy and organize for innovation.

This post was updated on August 30, 2019. It was originally published on November 15, 2016.

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Debating Disruptive Innovation

“How Useful Is the Theory of Disruptive Innovation?” was the question raised by an article in the fall 2015 issue of MIT Sloan Management Review . In this issue, several more experts weigh in on the topic.

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• Developing Strategy

Few MIT Sloan Management Review articles garner as much attention as Andrew A. King and Baljir Baatartogtokh’s article “ How Useful Is the Theory of Disruptive Innovation? ” in the fall 2015 issue. After interviewing and surveying 79 industry experts, King and Baatartogtokh concluded that many of the 77 industry cases cited as examples of disruptive innovation by Harvard Business School professor Clayton M. Christensen and his coauthor Michael E. Raynor did not actually fit four of the theory’s key elements well.

King and Baatartogtokh’s article attracted the attention of a number of media outlets — and generated a number of interesting responses. In the essays here, two authors — Juan Pablo Vázquez Sampere of IE Business School and Martin J. Bienenstock of the law firm Proskauer Rose LLP — take issue with King and Baatartogtokh’s conclusions. A third author, Ezra W. Zuckerman of the MIT Sloan School of Management, explores an intriguing question: What if the most important aspects of the theory of disruptive innovation are something different from what its proponents — and its detractors — emphasize? Finally, in an article on page 83, Joshua S. Gans of the University of Toronto’s Rotman School of Management discusses King and Baatartogtokh’s findings in the context of his own research on disruption.

Missing the Mark on Disruptive Innovation

By Juan Pablo Vázquez Sampere

Every time I hear about a new study on disruptive innovation, I feel excited about the possibility that someone will come up with a way to explain the theory in a much clearer and more transparent manner. More often than not, I end up disappointed — as I was by Andrew A. King and Baljir Baatartogtokh’s article, “How Useful Is the Theory of Disruptive Innovation?” in the fall 2015 issue of MIT Sloan Management Review .

For starters, King and Baatartogtokh argued that Clayton M. Christensen’s theory of disruptive innovation has not been adequately tested in the academic literature. I would encourage the authors to revisit the literature, because to my count, there are more than 40 articles, including much of an entire issue in a leading academic journal (the Journal of Product Innovation Management in January 2006), that test and challenge disruption in many different ways. Furthermore, disruptive innovation is composed of more than four elements, yet the authors chose to test only four.

What’s more, the authors surveyed only 79 experts to evaluate 77 industries. As a result, some of the conclusions attributed to the experts are questionable — such as one expert’s argument that it was unreasonable to assume that wood-products companies could respond to disruption from plastics, since the capabilities required were different. Yet many companies develop new and different capabilities. To name just a few examples, the Goodyear Tire & Rubber Co. retooled extensively to develop radial tires, IBM was successful at diversifying from mainframes to personal computers, and incumbent landline telephone operators developed capabilities for wireless communication. If incumbents can increase their profitability by introducing a particular product or technology, they often find a way. However, one of the fundamental tenets of the theory of disruptive innovation is that, when contemplating a disrupter, incumbents are motivated by profits to flee rather than fight the disrupter.

Another conclusion King and Baatartogtokh reach is that 38% of incumbents did not flounder as a result of disruption. That statistic may not be meaningful for several reasons. In some industries, such as retailing, the process of disruption can take decades. (In other industries, such as minicomputers when they were disrupted by personal computers, things can happen relatively fast, which makes it easier to see the entire picture of how the industry evolves.) Second, the disruption might affect only one business unit of the incumbent, so in some cases, the entire company survives even though that particular unit is no longer successful. Regulators may also intervene to help protect powerful incumbent companies. For all of these reasons, a long period of coexistence between incumbents and disrupters does not necessarily mean that the process of disruption has halted.

More generally, I believe there is a responsibility on the part of researchers to proceed carefully when testing a theory. It is truly important to find some sort of data set that is large enough and verifiable enough to support valid conclusions. That’s more important than making headlines.

Juan Pablo Vázquez Sampere is a professor of operations and technology at IE Business School in Madrid.

Did the Critique of Disruptive Innovation Apply the Right Test?

By Martin J. Bienenstock

Having specialized in reorganizing companies in financial distress for 38 years, I have had a ringside seat to the causes and consequences of business failure. I use that experience to counsel boards of directors about formulating corporate governance to promote growth and avoid failure. It is vital to help boards detect and understand their companies’ problems when those problems can still be solved outside bankruptcy — and when the companies can still grow profits for shareholders.

In my experience, the cause of business distress that is most detectable, but often undetected or disregarded until material damage is done, is a disruptive innovation as defined by Harvard Business School professor Clayton M. Christensen. In his theory of disruptive innovation, Christensen has explained how and why industry-leading companies that pay attention to their best customers and improve products for them are susceptible to failure stemming from competitors’ products or services that are initially inferior and only attract a different market or the lower end of the leading company’s market. Of all the many different types of advice I give boards, the means of detecting disruptive innovations has been one of the most critical staples.

In their article, “How Useful Is the Theory of Disruptive Innovation?” in the fall 2015 issue of MIT Sloan Management Review , Andrew A. King and Baljir Baatartogtokh acknowledge that Christensen’s disruptive innovation theory “has gripped the business consciousness like few other ideas.” But they incorrectly conclude that the theory simply “provides a useful reminder of the importance of testing assumptions, seeking outside information, and other means of reducing myopic thinking.” That overlooks what Christensen discovered and vastly underestimates the importance of Christensen’s insights to executives and corporate directors.

When Christensen studied successful companies whose fortunes declined, he discovered one category of companies that failed or suffered diminished success when overtaken by companies that had initially offered inferior products appealing to customers who either could not afford the successful companies’ products or were the least profitable for the successful companies. More often than not, the market leaders were capable of offering the cheaper product. But, for seemingly valid business reasons, they declined to do so.

It is critical that boards of directors and senior management understand when following accepted principles of good management (such as paying attention to your best customers and focusing investments where you can increase profit margins) leads to failure. Christensen demonstrated that those accepted management principles are only situationally appropriate. That insight can be used not only to avoid failure but also to go on offense to displace competitors. Identifying and harnessing disruptive innovations to avoid failure and to grow shareholder value became far more attainable once Christensen identified the essential elements of a disruptive innovation — a phenomenon previously unnoticed.

The tests to identify a potentially disruptive innovation that Christensen and his coauthor, Michael E. Raynor, include in their book The Innovator’s Solution form a critical aspect of the theory for executives. The first test is to ask whether an idea or product will appeal to a large population of potential users who have gone without it or who have had to go to an inconvenient location to use it. If so, then there is a potential new market to be exploited.

The second test is to ask whether there are already customers at the low end of the market who would purchase an inferior, but still sufficient, product at a discount price that would enable a disrupter to earn a sufficient profit. If so, then there is a low-end market to be exploited. Finally, if either or both of the first two tests are passed, the final question is whether the disruptive idea is disruptive to all significant incumbent companies in the industry. If not (in other words, if the disruptive product is a sustaining innovation to a leading player’s product that that player can also improve), an entrant will likely fail with the idea, because an incumbent will have the advantage.

King and Baatartogtokh’s article did not test whether Christensen’s formula to identify a disruptive innovation that could take a leader’s market share holds up. Rather, they tested whether each of four variables they selected are present in each of 77 examples of disruptive innovation that Christensen and Raynor identified.

The bottom line is that Christensen’s theory is invaluable to business executives. He showed the power of a disruptive innovation to infiltrate a new market or low-end market with a product inferior to an incumbent’s product. He explained that disruptive products often improve and displace the incumbent’s products because the organizational cultures of incumbents usually cause them to avoid inferior products offering lower profit margins, which initially do not appeal to their best customers. This explains the problems and declines of countless once-successful companies — and is detectable and avoidable. King and Baatartogtokh’s article does not recognize this value of the disruptive innovation theory. Using Christensen’s theory has helped companies such as Intel Corp. and Johnson & Johnson identify and formulate innovative products. Simultaneously, the theory helps incumbents spot disruptions so they can deal with them without being overtaken.

Many incumbents end up floundering as a result of a disruptive innovation, while some extraordinarily well-capitalized incumbents do not. In some cases, for example, the incumbent ends up purchasing the disruptive innovator. Accordingly, King and Baatartogtokh’s assertion that 38% of the 77 cases from Christensen’s books resulted in an outcome other than the incumbent floundering does not undermine Christensen’s warning to incumbents about the potential threat from disruptive innovation. The point is that if incumbents do not identify and respond correctly to disruptive innovations at the outset, they can pay dearly by losing market share. Moreover, some of the 77 cases took place after publication of Christensen’s first book, The Innovator’s Dilemma , in 1997. Given the enormous influence and popularity of that book, it would be surprising if some of the incumbents in the 77 cases did not benefit from Christensen’s insights. Similarly, King and Baatartogtokh’s finding that in 31% of the 77 cases the disrupter competed with a product for which there had been no significant trajectory of sustaining innovation does not detract from Christensen’s discovery of the power of a disruptive innovation to infiltrate new markets and then go up-market to displace the leader.

Christensen has done what businesspeople wish all advisors would do. He extracted from his research a key reason why so many dominant companies fall. He explained it in understandable and compelling terms. He articulated simple tests to identify potentially disruptive innovations to help companies avoid failure and grow profits. Indeed, every board of directors anxious to carry out its fiduciary duties of care and loyalty wants to understand what makes successful companies lose dominance or fail. Christensen’s disruptive innovation theory addresses one of the most vexing and unsolved problems of decades of successful companies that faltered, failed, or simply stopped growing. Disruptive innovation theory thus rightfully earned its honored place on the board agenda.

Martin J. Bienenstock is chair of the business solutions, governance, reorganization, and bankruptcy group at the law firm Proskauer Rose LLP; he is also a lecturer at both Harvard Law School and the University of Michigan Law School.

Crossing the Chasm to Disruptive Innovation

By Ezra W. Zuckerman

No theory or framework is perfect. And one common imperfection, which is present in Clayton M. Christensen’s theory of disruptive innovation as well as many other frameworks, is that it is not entirely clear what is the core idea and what is peripheral. This ambiguity has in turn made it unclear how valuable the theory is and what adjustments might make it more valuable. My own view is that there is a very useful core idea at the heart of the theory, one that scholars and executives alike would do well to heed, but this idea has yet to be articulated clearly, either by Christensen or by critics such as Andrew A. King and Baljir Baatartogtokh. This core idea is what I call “the surprisingly bridgeable chasm.”

Let me back up. When we consider any management theory or framework, it is useful to start by asking a few basic questions:

• What question is the theory meant to address?
• Does the theory improve upon (as a complement or substitute for) other answers to the question it addresses?
• What ideas are at the core of the theory and what is peripheral?

Let’s consider the theory of disruptive innovation through the lens of those three questions.

1. What question is the theory meant to address?

Christensen’s theory of disruptive innovation is animated by an excellent question:

How is it that capable, motivated incumbent companies are unseated by startups that tend to have weaker capabilities and fewer resources? This would seem improbable, yet it happens more frequently than one would expect. Why?

Regardless of what one thinks of the theory of disruptive innovation’s answer to this question, the question remains a good one. In my view, this is the main weakness of Harvard University historian Jill Lepore’s prominent critique of the theory of disruptive innovation in a 2014 article in The New Yorker . Lepore raised a set of interesting points. A chief weakness of her critique, however, was that she did not adequately acknowledge the importance of the question that the theory of disruptive innovation addresses. I suspect this comes in part from the fact that Lepore is an outsider to the business field. She does not have to confront the question of why capable, motivated incumbent companies might be vulnerable. But we (both managers and management scholars who aspire to guide them) do.

2. Does the theory improve upon (as a complement or substitute for) other answers to the question it addresses?

One of the downsides of the great popularity of the theory of disruptive innovation is that that popularity has obscured the fact that there are other good answers to the question the theory addresses. In particular, two compelling answers to the question of why incumbents are vulnerable are “competency traps” (a phrase that was introduced by Barbara Levitt and James G. March in 1988 and that describes the paradoxical fact that it is more difficult for companies that are highly capable in one area or with one approach to develop new capabilities than it is for a new entrant to do so) and internal competition (that a company’s units have difficulty sharing common resources such as their brand and sales channels when the units compete for the same business).

Christensen and his coauthors are well aware of each of these issues and discuss them as part of their framework. But one does not need the theory of disruptive innovation to appreciate these points of incumbent vulnerability. The question is whether the theory has a distinctive insight to add to complement existing insights. Are incumbents vulnerable even when they do not fall prey to competency traps and are not riven by politics? Christensen and colleagues counsel that the answer is “yes.” But how and why is that?

3. What is at the core of the theory and what is peripheral?

Here is where things become fuzzy. In their article in the fall 2015 issue of MIT Sloan Management Review , King and Baatartogtokh argue that one key claim of the theory of disruptive innovation is that incumbents (precisely because they are so competent and motivated) overshoot customer requirements. And King and Baatartogtokh demonstrate convincingly that this customer overshoot usually does not occur. It is not clear to me, however, that the customer overshoot concept is at the core of the theory. When I teach the theory of disruptive innovation, I barely mention customer overshoot. Rather, I see it as essentially a secondary, reinforcing process but not a core one. My question is:

If we remove this assumption from the theory of disruptive innovation, does the theory still have a distinctive answer to the question of incumbent vulnerability?

A related question can be asked about “high-end disruption.” Since the earliest formulations of the theory of disruptive innovation, Christensen has been adamant that disruption can only come from “below” — in other words, beginning with customers that have zero or low willingness to pay for the dominant technology. Christensen’s premise seems to be the following: Since customers with low willingness to pay are the most dissatisfied with the existing technology, those with high willingness to pay will be most satisfied with current technology, and so incumbents who are capable and motivated to serve them are less vulnerable to losing those customers. The problem, however, is that those with high willingness to pay might be willing to pay even more if incumbents were willing or able to deliver products that better met their needs. And good research on “high-end encroachment” by Joseph Van Orden, Bo van der Rhee, and Glen M. Schmidt now indicates that incumbents can often be displaced from above — in other words, by entrants that begin by attacking customers with a high willingness to pay. (Schmidt and van der Rhee explained the practical implications of that research in a 2014 MIT Sloan Management Review article .)

One way to address this issue is to assert categorically that examples of high-end encroachment are not cases of disruption because by definition they come from the high end. This is essentially the approach that Christensen has taken. But the question I ask about Christensen’s insistence that disruption can only come from the low end is the same one I raised with respect to overshooting:

If we eliminate this assumption from the theory of disruptive innovation, does the theory still offer a distinctive answer to the question of incumbent vulnerability?

Put differently, what really is the core idea of the theory of disruptive innovation?

My own view is that the core insight of the theory of disruptive innovation can be captured — without requiring us to assume that disruptions always entail customer overshoot by incumbents and must always start with low-end customers — when we relabel it the “theory of the unexpectedly bridgeable chasm.” I take the term “chasm” from Geoffrey A. Moore’s classic 1991 book on technology marketing, Crossing the Chasm . Moore’s core insight was that new technologies often fail to parlay their popularity among early adopters into mass-market appeal; the reason is that, since mass-market customers typically have different needs and desires, early adopters serve as negative reference points.

Ironically, even though Moore’s book has been enormously influential, it has rarely been recognized that its core idea is in significant tension with what I believe is the theory of disruptive innovation’s core idea. Moore argued that niches are often very hard to use as springboards for “crossing the chasm” to the mass market. Christensen argued the opposite — that such “springboarding” happens more often than we might expect. Incumbents generally assume that innovations appealing to a niche will never threaten them because their customers have different needs, but surprise, surprise — sometimes those customers change their minds. And by that point, it is often too late for incumbents to play catch up.

If disruption is viewed in this broader way as a “theory of unexpectedly bridgeable chasms,” how is it that chasms that seem unbridgeable may be bridged? There are at least three well-known processes of bridging chasms by increasing returns — experience curves, network effects, and demand discovery — whose shape cannot be known until one starts to embark upon them. The first of these processes is the idea made prominent by the Boston Consulting Group in the 1960s and 1970s — the idea that the more that one engages in (or invests in) a production process, the better one gets at it. The second of these is the idea that became widely known with the rise of Microsoft in the 1980s — that demand is often driven by the number of other users that use a platform either directly or indirectly, causing markets to quickly tip from one platform to another. And the third is the very straightforward point (exploited to the hilt by Steve Jobs) that people often do not know what they like until they see it. None of these processes for bridging chasms is surprising in the abstract. But when one or more of these processes is salient, surprises can happen because no one can say in advance what particular shape these processes will take.

A second key question is why, in this broader view of the theory, incumbents are more vulnerable to such surprises than entrants. Here Christensen points to an important factor — that incumbents face a higher hurdle rate (in other words, expected rate of return above which they will invest) for investments in nascent markets than entrants. One reason for this applies to public companies: Pressure to maintain their current valuation “multiple” can dissuade them from pursuing opportunities in small, emerging new markets that appear to promise a lower multiple. Another reason, which draws on recent work in economic sociology, is that investment in a different niche can signal lower commitment to existing stakeholders (customers, employees, and investors).

The upshot of the above is that there is indeed a very useful idea at the core of the theory of disruptive innovation. In short, it is quite instructive to recognize that niches can potentially be the launching pads for ventures that unexpectedly come to compete successfully with the most capable, motivated incumbent companies. It is just one part of a larger set of ideas we have for understanding the vulnerability of incumbent companies. But it remains a very valuable insight, and we have Christensen and colleagues to thank for it. One hopes that in the future, the theory of disruptive innovation is recognized for what it is rather than promoted or attacked for what it is not. It is only through such judicious use and thoughtful revision that ideas become most valuable for clarifying thinking and action.

Ezra W. Zuckerman is the deputy dean of the MIT Sloan School of Management as well as the Alvin J. Siteman (1948) Professor of Strategy and Entrepreneurship at the MIT Sloan School.

About the Authors

Juan Pablo Vázquez Sampere is a professor of operations and technology at IE Business School in Madrid. Martin J. Bienenstock is chair of the business solutions, governance, reorganization, and bankruptcy group at the law firm Proskauer Rose LLP; he is also a lecturer at both Harvard Law School and the University of Michigan Law School. Ezra W. Zuckerman is the deputy dean of the MIT Sloan School of Management as well as the Alvin J. Siteman (1948) Professor of Strategy and Entrepreneurship at the MIT Sloan School.

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Alfonso siri, martin bienenstock, theodore piepenbrock.

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Innovation Research Topics: That You Need To Look Into

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Best Project Innovation Ideas in Management

Interesting innovation technology ideas, hot innovation project ideas for students, most captivating innovation project ideas in healthcare, easy innovative business topics for research paper, trendy innovation research topics, simple innovation essay topics in education, top innovative research topics on social media, fascinating product innovation ideas, awesome innovative research ideas in agriculture.

In your innovation research, focus on your interests based on what you learn in your course. That’s the best way to have a topic you can effectively write and excite your professor or sponsor. This article will focus on 100 innovative research topics you can consider to improve your chances of scoring a top grade.

In addition to social media research topics , there’s a lot you can focus on to write excellent projects. Here are some of the management innovation research examples to get you started.

• Management innovations as a critical factor in increasing consumers
• Disruptive innovations in management nobody expected this year
• Comparing the internal and external management innovations
• A look at innovations in business management post-COVID-19
• The needed innovations in manufacturing companies to improve waste management
• Exploring the impact of customer relationship management tools in 2023
• How digital transformation has changed management processes in big ventures
• How innovations are transforming the risk management space
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• The role of machine learning in project management

A topic that allows you to write about what the majority like most will make you stand out. As you read more on social issues research topics , the innovative technology ideas below are also worth it.

• Analyzing the innovations in the airline industries over the years
• The role of technology innovations in the crime sector
• Are digital technologies losing the sense of innovativeness?
• Innovations in technology and service delivery: The truth revealed
• Understanding how tech innovations cause job losses
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• Machine learning algorithms in maintaining production systems
• Analyzing how smart homes are becoming better with artificial intelligence
• Is the continuous development of apps with blockchain technology viable?
• Understanding the security of mobile apps from a technological perspective

Every student desires a project showing their detailed understanding of the innovation idea. Besides these research topics for STEM students , here are some hot product innovation examples for students:

• AI as a solution for mild illnesses
• Comparing tech innovations based on project budgets
• The impacts of blockchain technology in developing voting systems
• The role of AI in surveillance systems
• Part of the innovations in energy generation using renewable sources
• Part of the innovations in traffic control
• Online shopping innovations transforming the retail sector
• How innovations are making it easy to handle cycle crimes
• Developing a health and wellness app for students with bad eating habits
• Using waste materials to build tech machines and hardware

A common question about innovation in healthcare is, how do people come up with many exciting biochemistry topics that are out there in published papers? Worry not because this section will reveal more diverse ideas to try out.

• Analyzing the usage of health and fitness apps among the elderly
• Using electronic health data in apps development
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• Tracking blood electrolyte levels without sample collection
• Challenges of using automation to diagnose infants
• Blockchain as key in health records
• Expected innovations in telemedicine going forward
• How technology has changed hospital consultations
• Blood pressure interventions using the latest technologies
• Are innovations that track patient progress online practical?

From the many innovation project examples you’ll come across in your research, innovative business topics are among the most exciting to read. Read on for more exciting topics.

• Challenges of innovations in business
• Innovation and passive income
• Online stores’ key growth parameters
• Using technology to get legit business advice
• Artificial intelligence in business data management
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• Encouraging innovations to increase product consumption
• Innovations in businesses are capital intensive
• A new era of hiring and staffing
• Role of management in business innovations

Economics research paper topics tell a lot about the current times. However, a trendy example of an innovation research topic expounds more on what many now prefer. These sample innovation topics show what’s trending.

• The benefits of quantum computing
• Automation in customer management
• A look at predictive analysis
• Using the Internet of Things Correctly
• Database improvement with blockchain
• New cybersecurity interventions
• 5G revolution
• Using edge computing in research
• A look at machine learning advancements
• Artificial intelligence vs. machine learning

Education innovation and changes attract a lot of controversies. Here are some essay topics in education you’ll be happy to focus on.

• The impact of outside-class learning
• Brain breaks in the academic journey
• Early learning trauma and academic excellence
• Virtual vs. physical presence learning
• Grades and student improvement
• Mastery-based grading
• Personalize learning curriculum
• Role of tech in homeschooling
• Role of STEM in education innovations
• Benefits of blended learning

First, read more about the thesis statement about social media . You’ll realize it’s pretty easy to create some fantastic research topics. These innovation samples revolve around social media.

• Social media and brands authenticity
• Social media and propaganda
• Addressing costs of social media advertising
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• Why prioritize social media integrations?
• Are cookies making social media sites worse?
• Comparing Facebook and Instagram ads
• A look at crucial TikTok analytics
• Comparing short and long-form social media content
• A new approach to social media ads

As you learn more about anatomy research papers , we’d love to emphasize more on research product ideas that apply to other fields. These ideas include the following:

• E-learning short courses taking over major courses
• Adaptation of drones in fighting crimes
• New car accessories and improved efficiency
• Candle innovations that sell
• Technological advancements in Cannabis processing
• Food products for intolerant kids
• Baby products now save costs
• Tech in safe training machines
• Humidifiers and COVID-19
• Kitchen air fryers and their health concern

You probably have many questions about innovation, especially in the agriculture sector. We will list some innovative topics below to help you write the best research paper.

• A detailed overview of automated farm machines
• Are laser scarecrows effective?
• On-site agriculture product testing
• Innovations for improving harvest quality
• Using IoT technology to conserve water
• Mobile apps in agriculture
• Role of tech in animal feeding
• Current innovations in farm management
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How does research make human innovation possible? If you have been wondering about this question, the topics listed in this article will give you the best answer. Once you have decided on what you want to focus on, reach out to us, and let’s help you write a research paper that guarantees a top grade.

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