Identification of innovative technology enablers and drone technology determinants adoption: a graph theory matrix analysis framework

Abstract

Two main things ensure technology is integrated into a system: enablers, which help technology get in; and determinants, which act as filters to ensure that the right technology gets in. The study develops a decision framework for ranking determinants of drone technology adoption from the perspective of enablers related to innovative technology integration. This study is based on qualitative expert opinion and quantitative integrated MCDM methods. It provides a valuable graph theory matrix analysis framework for managerial perspectives. Several insights are given into the areas of what makes it possible to use new technologies and what makes people adopt drone technology. The study also points out problems and places where more research is needed.

Introduction

Innovative system integration depends on the interaction of various enablers and determinants that play essential roles in easy adoption, diffusion, and absorption (Rogers 1995). Schot and Steinmueller (2018) found that these enablers and determinants work together in similar ways that make innovation possible. Innovative technologies make it easier for an organization to interact with global markets and simplify its operational and communication problems (Pattersson 2009). This helps the organization stay relevant and focused on its goals. Technical integration and collaboration helps organizations maximize time management and enhance operational flexibility. It gives them precision and creativity, enhancing their productivity and cost management. As a result, it eventually became a base for integrating differentiated technologies (Denti and Hemlin 2012). Technology helps the social and cultural environment thrive and continue to evolve.

In return, the culture, values, and goals of human societies become the basis for these technologies to continue to work. Integration of innovation depends on several things, such as the size of the organization, its business partners or competitors (Scott 2001), the availability of resources, the best practices of organizations or equipment, communication processes or the organization's structure, and how the market works and how institutions work (Scott 2001; Raymond 2001). Technology and how people interact have created a cycle that has helped societies stay helpful and productive while increasing the demand for these technologies. Understanding how these codependences work requires analyzing their origin and application's societal and technological attributes. Using three broad insights from academia, industry, and practice, we can identify interventions to help organizations integrate innovative technologies to improve performance. Technology innovations are hard to make, change over time, and need constant feedback and support to be used and have an effect in more than one way. Innovative technologies integrate socio-cultural, economic, and technological elements at macro and micro levels. Technological advances require standardization at macro and micro levels to rationalize their widespread diffusion for maximum benefits and minimum damage.

The complex nature of innovative technologies is based on the fact that their development results from the simultaneous interactions and interventions of multiple local and global factors. Social trends, physical patterns, policies, practices, and favorable circumstances affect their development and evolution. Therefore, the successful implementation of these technologies depends on beliefs, values, biases, needs, and legal and commercial structures that determine their viability. Multi-integrated elements drive innovative technologies to evolve for more extensive use cases to be reoriented and meet their potential. Therefore, these technologies require funding, platforms, processing power, software, and data to become scalable, valuable solutions. Hence, technologies that can bring radical changes to a system depend on external enablers: competition, industry and market characteristics, government suppliers, and customers (Chau and Tam 1997). Also, it depends on internal enablers like infrastructure, equipment, communication processes, and organizational structure (Schot and Steinmueller 2018) that help them exploit their optimum potential. During technological development, the diffusion of these new technologies determines the rate of economic growth and productivity change. It is therefore essential to maximize their outreach. Technology adoption and diffusion (Rogers 1995) rely on important determinants and criteria that must be met to become fully functional and operational. Innovative technologies must match the demands posed by the determinants of their usage. Innovative technologies include new releases of technology, software or hardware upgrades, or new integrations for an improved product or process improvements, and they are everywhere around us. Several advanced technologies are used for developing cyber-physical systems and ICT-integrated production-business processes, such as Big Data Analytics, Cloud Computing, the Internet of Things, and virtualization/simulation technologies (Zhu et al. 2006). Our research study is centered on integrating modern technologies, firstly and secondly, the integration of drone technologies. Currently, drone technologies hold a niche in the service provision sector because of their unique differentiation capability. Drones have a variety of multipurpose uses (Barmpounakis et al. 2016), including monitoring pollution, identifying accidents, investigating fires, delivering packages, servicing emergencies, delivering medicine, monitoring traffic, and overseeing construction sites (Agatz et al. 2018; Bamburry 2015; Dorling et al. 2016; Murray & Chu 2015; Otto et al. 2018). A drone, equipped with advanced sensors and data processing capability, offers access to hazardous areas, communications in hard-to-reach terrain (Silvagni et al. 2017), and civil and construction applications (Ham et al. 2016). Ali et al. (2022) pointed out that integrating drone technology can help conserve resources, minimize power consumption, reduce pollution, and better prepare for emergencies. Drone technologies have many benefits, but the question is how to add them to a system already in place. In any technological integration or adoption, the direction of advancement is not unidirectional. In their latest study, Ali et al. (2021) found that success or failure depends on various factors, including demand, consumer preferences, economies, people, and others. Technology determinists also believe that social capital based on values, culture, and legal structures is crucial to the acceptance and viability of technology (Ali et al. 2021). To understand this, we need to determine how and why some organizations choose any innovative technology while others resist drones and what factors play a role in these decisions. Will the integration of drone technologies require any specific measures?

To answer these questions in this study, we plan to examine innovative technologies, including drones, and set our goals accordingly.

1. To Identify enablers that facilitate the integration of innovative technology

2. To find the determinants affecting the adoption of drone technology.

In order to meet the stated objectives, our research focuses on innovative technology integration broadly considered by organizations and drone technology adoption in particular. In this study, the authors look at the existing research to figure out what makes innovative technologies work and what makes people adopt drones. A detailed questionnaire about the same is circulated to experts to gather information on the stated innovative technology enablers and determinants of drone technology adoption. Through the feedback received from experts and a literature review, nine enablers of innovative technology integration and twelve determinants of integration of drone technology are identified. The innovative technology enablers are considered the main determinants of the integration of drone technologies and are categorized into three modules based on research theory. The word module has been taken from French or Latin modulus and refers to a 'self-contained, standard unit' that can be combined with other different but compatible modules to assemble a wide range of varied end-products. We have used the term module as having related characteristics for determinants identified for integration of Drone technology adoption and are evaluated using a graph theory matrix.

The study advances with the next section of the literature review, followed by the decision analysis framework. Results and discussions are followed by the main findings and discussions, managerial and practical implications, the study's unique contribution, limitations, and future scope in the following section.

Literature review

The integration of innovative technologies consists of adoption-the early use of technology in particular contexts, the diffusion-the spread of technology relative to other setups and users, and absorption-the mass adoption of technology within many different contexts (Davis 1989; Rogers 1995; Venkatesh and Davis 2000; Grubler et al. 2012). Khilari et al. (2022) also advocate that adoption of innovative technologies is essential for developing the competitive edge in the global market. As demonstrated by researchers have taken a keen interest in technology acceptance and diffusion. A theory of Diffusion of Innovations (DIT), which first appeared in 1960; and the other theories were proposed by Davis et al. (1989)-the Technology Acceptance Model (TAM); Venkatesh and Davis (1996)-the final version of the TAM; Venkatesh and Davis (2000) the TAM2; Venkatesh and Bala (2008) -the TAM3. In light of the above-mentioned extant literature, different perspectives are investigated in terms of technology: stakeholders, context, unit of analysis, research methods, need, purpose, pace, processes, and nature (Brown and Venkatesh 2005). Some other theories, such as the practice-based view, organizational learning theory, dynamic capability theory, and contingent resource-based view, are also used for enabling technology and innovation. For instance, Mishra et al. (2022) analyses the complexities and interconnections of the elements influencing data-driven innovation using organizational learning theory and dynamic capability theory. In the recent study by Dubey et al. (2022), to understand the role of AI-driven big data analytics in humanitarian relief operations, a practice-based perspective is applied as a valuable way to look at the importance of well-known and easy-to-replicate practices. To intensify collaborative efforts, the stakeholders now request greater visibility and clarification of roles in the emergency supply chain. With a contingent resource-based view (C-RBV), Dubey (2022) investigates crisis leadership as an additional organisational resource for effectively using digital technologies (DTs) in the emergency supply chain. Innovative technologies could be radical, incremental, or disruptive in nature and, regional and sectoral (Geels 2002). Technology emerges, changes, and is absorbed within a range of geographic and operational settings (Ali et al. 2021) and at varying governance scales to meet the needs of increasing numbers (Markard and Truffer 2008). The absorption of technology depends on several factors, including system, organizational, and regional infrastructure, the distance between buildings, the state of connectivity, and other related indicators of social and cultural similarities between two regions. Integrating innovative technologies in a system brings a social change that alters its structures and operations to offer opportunities (Ali et al. 2019) or pose challenges (Zahra et al. 2018). The organization's structure, along with its strategies, resources, and capabilities, determine its performance and competitiveness (Amit and Schoemaker 1993; Barney 1991). Organizations with the ability to integrate, build, and reconfigure internal/external resources for adaptation to rapidly changing environments (Teece et al. 1997) will be able to differentiate themselves and succeed. The ability of an organization to integrate, build, and reconfigure internal and external resources and competencies is vital to its survival and performance in rapidly changing environments (Wernerfelt 1984; Amit and Schoemaker 1993; Gruber et al. 2008). Organizations have to partner with commercial or scientific agents (Van de Vrande et al. 2009) and facilitate the internal/external flow of knowledge to overcome weaknesses and become technologically competitive (Zhong et al. 2013). Integration of innovative technologies depends heavily on people's willingness to adopt, use, and embrace new stuff. Pioneer users are more likely to take risks, implement technology and benefit from it than skeptics, paranoid users, and laggards (Rogers 1995; Parasuraman and Colby 2001). An end user's perspective on technology is dependent on his perception of usefulness, ease of use, and relevance in the workplace (Venkatesh and Davis 2000). A user's socio-technical environment determines the degree of technology use and sustained usage. This environment directly results from cultural processes, ideas, and reconstructions in which leadership, industry, and government all play essential roles in developing policies and strategies. It makes it easier for technological co-evolution to happen (Schaffers et al. 2011). It stresses the importance of modern infrastructure and effective, open, and participatory processes to keep up with what people want. Collaboration among educational and research institutions, local businesses, government, and residents has been shown to successfully shift a work culture that is adaptable to new technologies and processes. A culture of communication, feedback, and discussion makes it easier for technology to be used from the top down and changes how organizations work. Technology integration in a techno-friendly culture is facilitated by stakeholders, leadership, governments, and legal institutions who, in turn, imagine its application from many perspectives: legal, economic, customer, and value perspective (Colding and Barthel 2017). Innovative technologies refer to the adoption of a new technological product and also the adoption of technological advances in industrial and institutional processes; therefore, a substantial investment of financial resources are needed to reap future benefits (Söderström et al. 2014; Sadowski and Pasquale 2015). It is essential to evaluate these innovative technologies from a cost–benefit perspective. In order to measure their effectiveness, profitability and share market analysis should be used to measure the integration's benefits (Andrews and Criscuolo 2013). Also, the cost of integrating this kind of technology affects what customers and buyers decide to buy. The cost of technologies varies based on their nature (breakthrough, ever-changing), their purposes (competitive advantage, flexibility, ease of use), their stage (developmental, established), and their demand (product, process, industry, and market-specific). Technological trends follow consumer preferences, which follow industrial trends. Technology innovation focuses on customer demand. Therefore, a careful selection of target markets is necessary to make these technologies more accessible to customers. Further consideration should be given to identifying market segments that offer tremendous potential, size, and anticipated timing and amount of potential revenue flow (Ali et al. 2021). For the investment to be worth it, the target market needs to get a lot of the value the innovation can offer. Even though technology can be made for a target market based on industry trends, its use depends greatly on its economic potential and value proposition. Drone technology involves an enormous investment due to the extensive infrastructure and technological requirements to support all the smart components, grids, and devices for managing data and information. Apart from infrastructure costs, operating and maintenance costs of technology, IT training, and skill development are other significant factors contributing to the economic potential of technology (Mohanty et al. 2016). As a result of investment in smart components, the advancement of health, safety, and governance are expected (Pereira et al. 2017), as higher economic competitiveness, enhanced social security, and ecological sustainability. Value offering is compounded if technology integration in a system is backed by good governance, institutional, industrial, and legal regulations (Lu 2017). In leadership, decision-makers are seen as pioneers and visionaries who offer guidance, incentives, and support for long-term plans (Chourabi et al. 2012). Leadership is a key driver of innovation, change, and financial decision-making, so they are essential to implementing innovative technologies. They are responsible for innovation, change, and financial decision-making as visionaries (Ali et al. 2022). A strong leadership team also navigates legal and bureaucratic hurdles for technology start-ups, as these investments are susceptible to government regulations and policy restrictions. Furthermore, technologies are associated with their problems, such as trust, security, and privacy (Khan et al. 2017). Therefore, legal frameworks and policies are also essential. Technologies are cost-intensive; thus, insurance claims for equipment damage and failure, cyber-attacks, and industrial espionage (Zoonen 2016; Zhang et al. 2017) are some issues that require legal backup and support. Drones, a technological breakthrough, have also been studied by many researchers from multiple hard dimensions, but there is a paucity of research on soft dimensions (Figs. 1 and 2).

Fig. 1.

Technology integration model. Sources: Authors’ creation

Fig. 2.

Enablers of Innovative Technology Integration. Sources: Authors’ creation

An analysis of the literature identified multiple enablers of integrating innovative technologies and determinants necessary to help integrate drone technologies. We evaluate peer-reviewed, quality articles published in Science Direct, Google Scholar, Wiley, Taylor and Francis, Scopus, Springer, and Emerald Journals. These enablers are discussed in detail in Table 1.

Table 1.

Enablers of innovative technology integration

Enablers	Theoretical Perspective
Structure for absorption and diffusion of new technologies (C1)	The structure of a system is made up of resources and capabilities (Christensen 2000), allowing it to generate new ideas, develop new products and processes, and develop new marketing and market disruption capabilities (Easterby-Smith et al. 2002). The structural capability enables a system to reallocate its resources to absorb newer or innovative capabilities to seize opportunities for competitive advantage (Teece 2007)
Leadership for innovation and new technologies (C2)	Active participation by leadership enhances the chances of successful integration of new technologies and innovative pursuits (Gambatese and Hallowell 2011; Cooper 2005). Their approval and acceptance of different settings for innovation projects and creating a learning and development climate in the organization facilitate knowledge and technology transfer. Active leadership participation with managers and subordinates supports financial and operational decisions for internal and external networking for technological integrations (e.g., cross-boundary, teamwork, or customer relationships) (Cooper 2005; Johnstone et al. 2011). The role of leadership is not limited to decision-making and implementation; rather, a progressive leadership approach enables knowledge acquisition, assimilation, and dissipation for technological innovations (Chen et al. 2012)
Economic potential of technology (C3)	Innovative technologies' economic potential is considered a ratio of investment and outcomes. Organizations spend time, knowledge, and financial and human resources on technologies and integration. The organization adds value in enhanced operations and functional capability (Nanda and Singh 2009)
Stakeholders in the technology ecosystem' (C4)	Stakeholders expect innovative technologies to optimize work and provide fast and reliable services with more transparency and flexibility (Ali et al. 2022) using advanced information and communication systems
Facilitate knowledge transfer (C5)	Smart technologies and devices connect multiple ports connecting systems located in different locations. Virtual classrooms, training platforms, and workshops have become new norms of e-learning. Digital knowledge facilitates learning through e-portals and encourages employees to innovate, adapt, and evolve (Bakir 2016). Knowledge thus acquired improves organizations' absorptive and innovative capabilities to reap maximum benefits (Chang et al. 2013)
Competitive benefits (C6)	Technology imparts digital flair to existing infrastructure, converts it into an intelligent urban system, and facilitates the renewal of established businesses. Integration of innovative technologies opens unexplored avenues which can provide extra edge and competitive benefits to the businesses (Zahra et al. 2018)
Legislative framework to facilitate (C7)	Integration of innovative technologies in specific resource conservation-oriented regions and following environmental obligations would require different legal frameworks and policies. Technologies, which are a high-risk category, vulnerable to theft, high investment intensive, and easily damaged, would require better policies and legal frameworks to facilitate their absorption (Ebersberger et al. 2011). Innovative technologies with patent and copyright issues also need specific legal frameworks which can protect the right of the original creator of the technology and users of the technology
Cost modelling to facilitate innovation (C8)	Customers prefer product models in which technological innovations deliver better functions with minimum cost. A low-end disruptive innovation caters to the demand of customers who prefer cost over quality (Christensen 2000)
Value offering (C9)	Integration of Innovative technologies binds urban infrastructure with digital networks. It provides sufficient data to improve the working efficiencies of routine and critical operations, thereby unburdening a load of human machinery (Cohen et al. 2016). E-working patterns digital patterns improve the quality of work in urban administration, education, hospitality, health care, culture and heritage, transport, industrial operations, resource management, etc.

For the next phase, a literature review is done based on keywords such as benefits, impacts, and outcomes of drone technologies in journals, articles, and blogs. However, the information related to its integration is found to be limited. Since the research literature is found lacking, expert opinion is sought to identify the determinants for integrating drone technologies. Twelve determinants of drone technologies (M1-M12) identified through the Integrated method based on literature review and expert feedback are categorized into three modules Market module, Technology, and Commercial module as shown in Fig. 3.

Fig. 3.

Three Module of Determinants of Drone Technology Adoption

The market module offers insights into the dynamics of markets before developing a product so that suitable product production and marketing strategies are formulated. Once the market requirements and dynamics are fully understood, the technology module is defined, and marketing strategies are formulated. The market module gives us an understanding of the market determinants, their relationships, and the conditions they impose on drone technologies for their adoption into any system or organization. It explains how industrial trends, competitive benchmarking, and understanding the market problem or customer's perspective help the firm identify the target markets that drone technologies need to penetrate. Next, clarity about the determinants related to drones' technical know-how, material, process, and objectives is established. Next commercial viability of the material concept is established, and the commercial module is defined. This module defines determinants related to the legal framework, alliances, cost, and value evaluated for the adoption of drone technologies. The exact determinants for integrating drone technology adoption have not been explored in research yet. However, researchers are focusing on last-mile delivery, route optimisation, and the feasibility of drone technology adoption. But none of the research talks about how to use drone technology for broader ideas like smart cities, factories, warehouses, logistics, and other new ideas. We have taken the determinants for further study based on expert feedback and determinants applicable to integrating breakthrough and innovative technologies. These determinants, with detailed explanations are discussed in Table 2.

Table 2.

Determinants of drone technology adoption

Main category	Determinants	Theoretical Perspective	Source
			Survey/Expert	Literature Review (LR)
MARKET	Industrial trends (M1)	Organizations engaged in drone technologies must align more closely to market needs and engage in market value research to understand industry trends and market orientation for maximum product absorption. Industrial trends for drone technologies favor its adoption, as can be seen in various applications, but diffusion and absorption of drone technologies are yet to happen	Survey	Ali et al. (2021), Ali et al. (2022)
	Customer’s perspective (M2)	The customer’s perceived ease of use and usefulness of a technological product, image, experience, work-related relevance, and quality output of technology becomes a criterion for its absorption	Survey	Rogers (1995) Venkatesh and Davis (2000)
	Competitive benchmarking (M3)	Competitive benchmarking offers security, long-term benefits, and a better image, so innovative technology should be integrated into a system based on its ability to strengthen benchmarking parameters. Efforts should be made to commercialize innovations based on benchmarking	Survey	Datta (2011)
	Target market (M4)	Integration of innovative technologies can offer market shares, productivity, or profitability in the short term. However, for sustained organizational performance and long-term success, commercialization of innovative technologies is a must. That too is in the right target market, which can absorb the product to drive its demand	Survey	Tsai and Yang (2013)
TECHNOLOGY	Product/ material offering (M5)	Drones must be made of lighter materials in terms of their hardware and software so that drones will fly at a height with excellent speed. For drone delivery systems to be more effective, better payloads, better technologies, and longer battery lives are important factors. These factors contribute to improving the operational efficiencies of drone delivery systems	Survey	Agatz et al. (2018)
	Product objectives (use and applications) (M6)	Drone technology serves a specific purpose and gradually evolves to perform other associated objectives. Clarity on specific objectives is a must for inclusion and use in a system	Survey	Otto et al. (2018)
	Product/Process ideation (M7)	Drones can pick, inspect, and deliver the items if drones are used as delivery drones and hence are required to cover distances in length and heights. The ideation of a drone should have flexibility as far as its processes and operations are concerned. Shorter routes, suitable locations of takeoff and landing, and availability of recharging vertiports can improve the quality of its operations	Survey	Cooper (2008); Cohen (1993)
	Knowledge transfer (M8)	Technical specification of innovative technology is identified, which defines its requirements and identifies the gaps related to its functions, operations, material, components, parts, etc., for which knowledge transfer is a must. Operations and use of drones require knowledge for accurate data collection and data processing procedures; hence without specific knowledge, integration of drone technologies seems complicated	Survey
COMMERTIAL	Strategic alliances (M9)	Drone technologies are expensive and need continuous financial support, which sometimes is beyond organizational capability. Also, new partnerships must explore new markets in the event of the unreadiness of specific markets	Survey	Ali et al. (2021)
	Overcoming regulation (M10)	Drone technology is interpreted as invasive by many non-users as its flying operation is seen as a privacy intrusion. Legal frameworks and policies are a must for operations, equipment damage, failure, cyber-attacks, industrial espionage, and control insurance claims	Survey	Pauner et al. (2015) Otto et al. (2018); Mohammed et al. (2014)
	Cost modelling (M11)	Unlike other technological products, Drone is cost-intensive as manufacturing, operations, and maintenance requires continuous investments. So, the return on investment must exceed over initial investment for its proper absorption. However, this seems complicated as drone technologies evolve with time and require ongoing funding. However, owning a drone and using it for deliveries could lower costs than delivery trucks	Survey	French (2017)
	Value offering (M12)	Adoption and absorption of technology are relatively easier if the value offered by its integration and continuous use outweighs the investment in terms of financial returns, improved image, and long-term sustainability		Mozaffari et al. (2019)

In this study, the Graph Theory Matrix Analysis (GMTA) is used to determine what makes organizations adopt drone technology. The GTMA is applied in the different management fields to rank the factors and develop an index and quantitative assessment of those factors. Some prominent applications are provided in Table 3.

Table 3.

Application of GTMA

Authors	Applied model	Research area	Objectives
Gupta et al. (2022)	GTMA	Digitalization of logistics	To develop the index of manpower readiness for logistics digitization in th Indian context
Sharma et al. (2022)	IVIFS based GTMA	Food supply chain	To analyze the impact of COVID-19 on perishable food supply chains
Ali and Ullah Khan (2022)	GTMA	IIoT	To develop a framework for ranking and selecting the best authentication mechanism in adopting IIoT
Kamat et al. (2022)	IVIFS based GTMA	Humanitarian logistics	To analyse the barriers to the adoption of UAVs in humanitarian logistics
Kumar et al. (2021)	GTMA	Big data analytics	To prioritize the barriers to big data analytics adoption in manufacturing
Singh et al. (2020)	GTMA and AHP	Circular economy	To investigate the barriers to the circular economy model in the mining industry
Gupta and Singh (2020)	GTMA	Logistics	Develop the sustainability index for the logistics service provider
Zhuang et al. (2018)	GTMA	Selection problem	Select the best paper shredder
Jain and Raj (2016)	GTMA, ISM and SEM	Flexible manufacturing system	To evaluate the performance of a flexible manufacturing system
Anand et al. (2016)	GTMA	Risk management	To develop the sustainability risk assessment index for mechanical systems
Muduli et al. (2013)	GTMA	Green supply chain management	To analyze the factors and sub-factors that hinder green supply chain management implementation

Methodology

There are many popular multi-criteria decision-making techniques like BWM, AHP, ANP, MAUT, SMART, and DEA, etc. (Ali et al. 2021; Wang et al. 2009; Govindan and Chaudhuri 2016; Luthra et al. 2018) could be applied to rank the determinants. These techniques have some limitations, such as AHP and TOPSIS considering the independent factor that is not the case for this study (Rao and Padmanabhan 2006). Although ANP acknowledges multiple interdependencies, it does not assign variables a tier (Saaty 2004). Further, the DEA has computational complexities, especially with the high number of enablers. This constraint does not apply to the GTMA, which is an organised and consistent decision-making approach. It simultaneously keeps the hierarchical structure and the interdependencies between enablers. The GTMA can be used with an unlimited number of quantitative and qualitative determinants simultaneously (Gupta and Singh 2020). Moreover, GTMA provides a visual picture of the problem not considered in the conventional MCDM method (Gupta et al. 2021). In contrast to the other methodologies, the GMTA can depict the interaction between the problem's components and express it mathematically (Hudnurkar and Ambekar 2019). As a result, complex network relations can be transformed into simple, understandable matrices that aid in more systematic and critical analysis. In addition, computer programs can easily handle the problem's matrix representation. GTMA has been extensively utilised in several fields of study, such as quality management (Grover et al. 2006), flexible manufacturing system (Raj et al. 2010); reverse logistics (Agrawal et al. 2016a, b); cleaner technology implementation (Bhandari et al. 2019), sustainable supplier selection (Sinha and Anand 2018); and resilience supply chain (Rajesh 2020). However, this study is based on ranking the drone's determinants in context of various organisational adoption for technology integration. In order to fulfil the objectives of this study, GMTA is applied. Therefore, we applied GTMA in this study to evaluate the determinants of drone adoption based on innovative technology integration enablers.

The research framework of the study is presented in Fig. 4. The three GTMA components are as follows:

• (i)Digraphs that allow visual analysis depict the system and its components.
• (ii)Matrix-based representation of the components and their interactions for computer processing
• (iii)Permanent function computation, appropriate for representing the influence of each dimension with a single value.

Fig. 4.

Research framework for this study

The GTMA defines digraphs into matrices as two fundamental elements known as nodes and edges. These nodes thus reflect the nine innovation enablers that contribute to the deployment of drones. Once the innovation enablers have been determined, a diagram is created to illustrate how the innovation enablers and their interdependencies are structured. When a node i is connected to a node j by an arrow from node i to node j, this shows that innovation enablers i are more important than innovation enablers j. The relative significance matrix is created by translating this digraph into a square matrix using Table 4.

Table 4.

Comparative significance of parameter (Muduli et al. 2013)

Description	$a_{\mathit{ij}}$	$a_{\mathit{ji}}=1-a_{\mathit{ij}}$
Both parameters are equally important	0.5	0.5
One parameter (i) is slightly important than other (j)	0.6	0.4
One parameter (i) is strongly important than other (j)	0.7	0.3
One parameter (i) is very strongly important over the other (j)	0.8	0.2
One parameter (i) is extremely important than other (j)	0.9	0.1
One parameter is exceptionally more important than other(j)	1	0

Off-diagonal components depict the relative significance of one innovation enablers over another. Each diagonal member of the relative importance matrix represents the relative significance of a system parameter. The diagonal elements of the matrix are determined using the Table 5. If the matrix is influenced by changes in the number of parameters, a standard type of matrix function known as permanent function is generated. The permanent function is identical to the general determinant, with the exception that it contains only positive signs and no negative ones. Usually, researchers have preferred to use the permanent function rather than the determinant function, as the latter loses information due to negative signs. The permanent function of an M $\times$ M matrix is shown as follow (Forbert and Marx 2003):

$$\mathrm{Per}(\mathrm{A})=\sum _p\prod _{i=1}^n{a}_i,P(i)$$ 1

Table 5.

Scale for the importance of determinant for each innovation enablers

Qualitative measure of attributes	Assigned Value of
Exceptionally low	0.0
Extremely low	0.1
Very Low	0.2
Low	0.3
Below Average	0.4
Average	0.5
Above Average	0.6
High	0.7
Very high	0.8
Extremely high	0.9
Exceptionally high	1.0

The steps of GMTA is provided as follows:

• Step 1: Determine the enablers of innovative technology integration and identify the determinants of drone technology adoption.

• Step 2: Develop a digraph for the enablers of innovative technology integration, and convert it to a matrix

• Step 3: Determine the relative importance of determinants of drone technology adoption based on the scale provided in Table 4. In this table, the off-diagonal elements of relative importance matrix [M] will be selected.

• Step 4: Determine the significance of each determinant of drone technology adoption with respect to enablers of innovative technology integration using the scale provided in Table 5.

• Step 5: Develop a matrix for evaluating the determinant of drone technology adoption according to enablers of innovative technology integration. This is an N x N matrix indicated by the letter "M". The matrix is derived from the input values from matrices developed in previous two steps. Values of the off-diagonal elements of the matrix [M] are filled with the relative importance of the innovation enablers derived from matrix. The value is selected for the diagonal elements of the matrix for each determinant from Table 5. Thus, each determinant generates a matrix, so the number of matrices should be the same as the number of determinants.

• Step 6: Determine the permanent function of matrix [M] for each enabler using Eq. (1). Alternatively, the permanent function can be calculated manually, or a program developed in any computational engine such as C, C +  + , Java, MATLAB, and R.

Application of proposed decision support framework

With the help of a literature review, we identify the enablers of integrating innovative technologies. Then, experts evaluate the essential drone technology determinants in the context of nine broader innovative technology enablers. We determined the weighted score of each enabler based on the score first and then combined each determinant with the calculated enabler’s score. With the help of the integrated method, we rank the determinant with the highest total score.

Identifying enablers of innovative technologies and determinants of drone technologies

Initially, research articles covering various dimensions of innovative technologies, including their conception, benefits, barriers, enablers, technology, people, and infrastructure, were considered. Also, the words "diffusion" and "adoption" of technology, "enablers" and "determinants" of technology integration, "infrastructure," "culture," "people for technology integration," and "recent" and "breakthrough" technologies are used as keywords. News articles, industry reports, academic articles, and papers in Google Chrome, Safari, and research papers published in Scopus and Web of Science were read thoroughly. In the next step, words like "drone technology," "integration of drone technology," "absorption of drone technology," and "drone feasibility" were used as search terms. Twelve enablers for integrating innovative technologies and fifteen determinants for integrating drone technologies were identified. Next, a consultation approach with experts (Luthra et al. 2018) was considered for moving further. These shortlisted enablers and determinants were sent to three experts for pretesting. One expert from academia with strong technical knowledge and two from an industrial background was chosen to finalize these enablers and determinants. With the help of experts' suggestions, the number of enablers of innovative technology integration (Table 1) and determinants of drone technology adoption (Table 2) is revised to nine and twelve, respectively. A detailed and integrated questionnaire about the enablers of innovative technology and determinants of drone technologies was prepared. This questionnaire was sent through e-mail to the three above-selected experts for validation and scale development.

The same questionnaire was sent to one expert working with the world's leading technology innovation organization with almost 15 + years of experience in automation and innovative technology integration. Conference calls meeting at pre-decided times were made to all experts for detailed discussions on a questionnaire related to the linguistics scale. The experts agreed to have the linguistics scale shown in Table 4 developed for GTM. After finalizing the questionnaire (copy attached in Appendix 1), it was also sent to experts for a response. According to earlier research studies by Khilari et al. (2022) and Khan et al. (2022), a complete response from eight experts was deemed appropriate. These experts were chosen because of their experience in the field, education, and deep knowledge of integrating new technology in Jeddah, Saudi Arabia. Three mechanical engineers, one computer engineer who works as a consultant, and three project managers round out the team. Others are working in artificial intelligence and have experience in programming in machine language. Their expertise lies in the automation and technology-related industries within Jeddah's New Industrial Region. A few of these experts work in the pharmaceutical and other fast-moving consumer goods industries.

The following section presents an analysis of the data collected from the experts.

Results and Discussions

A GTMA technique was used to examine the determinants of drone adoption by considering innovation capacities as criteria. For this reason, key innovation enablers are discovered through a literature survey and assisted by a domain expert. Experts are chosen based on their industry positions and years of professional experience. These experts have worked in innovation management, research and development, and technology transfer for more than ten years. In addition to nine members from the industry, the expert panel consists of three members from academia with experience in innovation and technology transfer. The nine adoption enablers listed in Table 1 are finalized with the help of an expert panel. The interrelationship among these enablers is shown through a digraph, as represented in Fig. 5.

Fig. 5.

Index evaluation of diagraph for enablers of innovative technology

In addition to identifying the innovation enablers, the literature survey and expert opinion are used to finalise the drone adoption determinants. Experts were consulted on the finalisation of drone adoption determinants. Through discussion with the team of experts, twelve determinants for the adoption of drones are consolidated.

In this manner, nine enablers of innovation and twelve determinants of drone adoption is finalised. The experts then assess the relative significance of innovation enablers. The expert panel was asked to select the values for the off-diagonal components to evaluate the relative importance based on the scale presented in Table 4. The experts' responses were compiled and examined, and the highest mode value was selected based on consensus. The developed questionnaire determines the relative importance of innovation enablers using the scale provided in Table 4. The upper triangular value (${\mathit{a}}_{\mathit{i}\mathit{j}}$)is provided by the experts and lower triangular value (1-${\mathit{a}}_{\mathit{i}\mathit{j}})$ is calculated as per the Table 6. In this manner, input is taken from the experts and relative importance of the innovation enablers in the form of matrix [M] is represented by Eq. (2).

$$[\mathrm{M}:\mathrm{Enablers}\mathrm{of}\mathrm{innovation}]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 1& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 1& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 1& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 1& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 1& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 1& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 1& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 1& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 1\end{array}\right]$$ 2

Table 6.

Diagonal elements values for determinants

Enablers	C1	C2	C3	C4	C5	C6	C7	C8	C9
Determinants
M1	0.5	0.3	0	0	0.5	0.5	0	0	0.3
M2	0	0.3	0	0.4	0	0.6	0	0.5	0.4
M3	0	0.7	0.8	0.1	0.9	0.7	0	0	0.7
M4	0.2	0	0	0.5	0	0	0	0	0
M5	0	0.4	0.3	0.6	1	0.6	0	0.3	0
M6	0.2	0	0	0	0	0	0	0	0.3
M7	0.3	0	0	0	0.4	0	0	0	0.2
M8	0.7	0.6	0	0	0	0.7	0	0	0.6
M9	0	0	0.2	0	0	0	0.8	0	0
M10	0	0.3	0	0	0.6	0	0	0	0
M11	0.1	0.2	0	0.2	0.4	0	0.3	1	0
M12	0	0	0.2	0	0	0.5	0	0	1

Also, the committee of experts was asked to decide how important each determinant was based on the innovation enabler. The experts are asked to give their input on the innovation enablers and their importance. They provide the importance of each determinant of drone technology adoption to achieve the enablers of innovative technology. Table 6 is a scale that shows how important each of the twelve determinants is for each of the nine enablers. It is used for the diagonal elements of the matrix [M] for which the experts gave answers for twelve determinants. The experts provided the values shown in Table 6 for twelve determinants.

These diagonal values for each enabler were entered into the matrix [M] from Table 6. In this manner, twelve matrices were formed (Refer to Appendix 2), and only one matrix is presented due to space constraint as Eq. (3).

$$[\mathrm{M}1:\mathrm{Industrial}\mathrm{trends}]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0.5& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0.3& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 0& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 0.5& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 0.5& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0.3\end{array}\right]$$ 3

Equation (1) is utilized to calculate the value of the permanent function for each of the twelve determinants. To determine the value of the permanent function for all twelve determinants, a computer program is developed based on Eq. (1) in the R4.0.2 software. The developed program in run in R Studio environment on i5 core processor, 8 GB RAM computation machine. This program takes the matrix [M] as input to calculate the permanent function value for each determinant. In this manner, permanent value of twelve determinants is calculated with the help of developed computer program. Based on the value of parament value, determinants of drone adoption are prioritized and shown in Table 7.

Table 7.

Ranking of the determinants of drone adoptions

Determinants	Permanent (M)	Rank
M1	280.17	5
M2	282.83	4
M3	421.6186	1
M4	196.7123	11
M5	351.0161	2
M6	190.8391	12
M7	208.7732	8
M8	314.133	3
M9	206.7972	10
M10	208.0103	9
M11	271.0243	6
M12	250.6388	7

The ranking of the determinants is in the following order: (M3)-Competitive benchmarking > (M5)-Product/ material offering > (M8)-Knowledge transfer > (M2)-Customer’s perspective > (M1)-Industrial trends > (M11)-Cost modelling > (M12)- Value offering > (M7)-Product/Process ideation > (M10)-Overcoming regulation > (M9) Strategic alliance (M4)-Target market > (M6)-Product objective.

The result given states that ‘competitive benchmarking’ is the most preferred determinant for drone technologies. Drone technology is already survived but needs efforts to make it commercialize. Ali et al. (2021) also claim that competitive benchmark is an important factor for the adoption of drone technology. The ‘materials offering’ specifications of drones are based on their type, weight, purpose, and range, so their configurations in terms of hardware and software are generally pre-decided and come as a strong determinant.

The strength/weight ratio should be high for the drone material in order to enhance the operational efficiency (Höche et al. 2021). Further, the power stage device should be compact to reduce the unnecessary weight. ‘Knowledge transfer’ in the form of training and learning for its smooth operation makes it a third important determinant as technical experts and tech-savvy persons operate the drones. The knowledge management/transfer is an essential component for successful adoption of any new technologies especially drone (Ali et al. 2021; Aydin 2019). Further, the ‘customer's perspective’ is the fourth preferred determinant. Customers' choice impacts technology integration, and drone's innovative technology has a strong impact on its adoption. As Aydin (2019) found, the general public hears about drones mainly from the news, media, and sci-fi television series; thus, they consider drones too risky for commercial purposes. Therefore, there is a need to develop awareness and create perceived knowledge about drone applications. Likewise, the following important determinant is ‘industrial trends’ for technology adoption. The use of Drone remains useful in specific geographical areas and operational areas; thus, integrating drone into a system's inventory and carrying drone operations is relatively beneficial (Hochstenbach, et al. 2015). Regional and operational alliances enhance the chances of effective uses of drones in broad areas and domains, which can benefit all the alliances. Ali et al. (2019) and D'Andrea (2014) also emphasis on the drone application in the industries for internal transportation and deliver packages.

‘Cost’ is a determinant of quality; thus, compromise on cost is not feasible. As Drone is not a commonplace digital device, its programming and operations need technical knowledge and understanding. Hence the cost of Drone is relative unless some startups come up with some breakthrough ideas. Therefore, the Drone is cost-intensive; thus, its ‘value’ in terms of cost, ease, benefits, and environmental sustainability are crucial for their integration. Product innovation starts with its ideation (Otto et al. 2018; Cooper 2005); once the idea is formalized, technology is integrated to either create a new product or upgrade a previous version with a given number of resources. Technology has changed the way products are used now; instead, they have changed the idea of products. For example, telephones from landlines to mobiles, computers from desktops to laptops to touch screen surfaces, etc. Product innovation is dependent on its popularity, managers' perception of its effectiveness, and risk assessment (Cooper and Edgett 2008). Ideation of product innovation also considers the concept of value voice of the product, and the quantum of disruption (Christensen 2000) that innovation can add to the product. It is explained that Drones are machines in need of hardware and software integrations which makes Drone a cost-intensive entity. Drone ‘process ideation’ needs careful attention because the viability of its operation is dependent on its processes. Short-range operations and use in closed and restricted territories offer operational and economic benefits. Regulations are large criteria for Drone because these machines are often seen as privacy invaders and are prone to theft by hacking or damage. Hence, they pass regional and operational regulation criteria, and their integration remains challenging. If a system wants to integrate Drone, it must have clarity in its use and maximization of its potential for economic benefits and justify the investment in drones. Strategic alliances are not crucial for the integration of drone technologies. Target market, cost modeling of Drone, and knowledge transfer has received subsequent ranking, respectively, as these determinants are essential but not considered decisive. The target market for Drone is limited but is expanding now, and Next, product or drone objectives are another vital determinant linked to its purpose and functions. Unless these objectives are clearly stated, the integration of Drone becomes difficult, and as a result, this determinant has not received a higher ranking.

Conclusion

The discussions and findings have identified the economic potential of technology as the main enabler for its integration into a system. Economic potential is taken as an indicator of functional and operational efficiency resulting in economic benefits. If technology integration proposes positive future outcomes, its adoption rate is high. Leadership plays a vital role as the leadership mainly decides to integrate or reject new technologies based on their corporate vision, mission, policies, and other strategic measures. Hence leadership enables the integration of technology. What technology offers in the short and long term in financial revenues, social and environmental benefits, brand image, and equity enable easy integration. So, a higher value offering of the technology enables its easier integration. Though the cost of the technology is important, its significance is relatively not very high for its integration. This is because the cost is relative to necessity; if the technology is vital, the system will integrate it, and not otherwise. Knowledge in a system is transferred over a period. Hence, technology integration in a system is not expected to deliver instant knowledge, so this enabler is important but not crucial. Legal matters in established systems generally facilitate technology integration and rarely pose a problem, so this enabler is on medium consideration. The integration of innovative technologies can be visualized as a novelty concept. It promises new solutions to older problems, enabling the transition of old technological models or setups into urban and smart models. An interplay of various smart elements promotes integrated, competitive, resilient, and sustainable development. Cultural beliefs propagate innovations in technology transfers and related outcomes. Integration of technological changes in daily and routine operations can be promoted through awareness programs and comprehensive training, leading to increased ICT competency. Stakeholders enable technology integration as they are prime users and drive demand, but sometimes innovative technologies create demand rather than meet demand. Competitive benefits and ideation of innovative products have less importance, though encouraging technology integration does not play a decisive role. Technology takes time to pervade and deliver results; hence the benefits are not immediate. Ideation of innovative technology offering delivers long-term results and is continuously evolving, so this enabler encourages technology integration but is not given a decisive ranking. Novelty concept or uniqueness of technology encourages its integration but is not considered a strong enabler. Though all ideally desire breakthrough technologies, they are difficult to integrate into a system because of their cost and installation and patent or legal issues. So, if a system desires a breakthrough or novel technology, it must clear all hurdles before its integration.

Similarly, local culture is important because the people endorsing or representing a culture are not decision-makers for technology integration. Culture enables the gradual adoption of technology as we have seen that now mobile phones, which used to be rare commodities, have become essential commodities for almost every person in a system because of cultural imprints. Culture does enable technology integration, but it is not the essential enabler.

Managerial implications

Practical implications that are derived from the result state that economic potential of a technology and strategic alliances for its integration are crucial points for managers to work on. Effective mechanism should be put in place to capture on the potential of top enablers for convenient and easy integration of innovative technologies in the systems. Managers should focus on building and supporting initiatives to deal with relevant determinants for easy integration of drone technologies. Mangers looking for strengthening the innovative technologies integration in their system must work on rather mild enablers and determinants for their stronger reinforcement. Working on barriers, processes and material of drone will help in creating newer version which are light, require less infrastructural and material inclusion and can be used for inhouse functions or performing civil duties. Educating stakeholders about the novelty concept of technologies could create a culture which would facilitate easy integration of technologies.

Unique contribution of the work

Dual perspective of enablers and determinants: This study offers unique insights into the field of integration of innovative technologies and specially integration of drone technologies in terms of ranking of the enablers and determinants of integration. Earlier works on innovative technologies have covered hard dimensions covering, technology type, integration mechanism, application of technologies etc. but rarely soft dimensions of technology integrations have found discussions in research fields.

Decision making framework integrating mixed method: The developed framework involves both qualitative (survey) and quantitative (numerical analysis) methods and provide comprehensive and real time data for evaluation. Accurate and complete data received from expert feedback and research review is numerically analyzed to improve the quality of decision making. This decision-making framework is easier to formulate and apply in practice.

Limitation and scope of future work

However, this study has limitations as it has covered 12 enablers for integration of innovative technologies. These enablers are identified through the literature review; thus, there is a chance to overlook some enablers while reviewing articles. Further, the number of experts is limited in this study, which might influence the enablers' identification. These selected enablers can be used to explore the potential of any specific innovative technology. Also, the determinants are taken for the integration of drone technologies only, other advance technologies such as IoT, Blockchain and AGV can also be considered and explored based on the results derived in this study (Ali et al. 2022). The prioritization of the determinants drone technology adoption is done with the help of experts’ feedback, thus, there is possibility of opinion biasness towards their working position. This could be overcome in the future studies by integrating the GTMA method with fuzzy or grey theories. We have considered the enablers and determinants of innovative technologies and have not paid attention to the challenges, and benefits and specific applications of innovative technologies which is a limitation and can further be explored. This study is conducted in the context of emerging countries and could be extended for the developed and underdeveloped countries. Further, the findings of this study could be validated from multiple case studies from different countries. In addition to this, these enablers and determinants can be validated using other alternative of decision models like DEMATEL, TOPSIS, ANP and systems dynamics modeling approach etc. BWM is one of the possible analyses to rank the enablers of innovative technologies integration. The hybrid method based on BWM alongwith VIKOR or CoCoSo or fuzzy TOSIS can provide other possibilities of decision-making framework for technology integration.

Appendix 1: Questionnaire

Dear Sir/Madam,

We require your valuable input for our research to assess the determinants affecting the adoption of drone technology. This questionnaire aims to collect data from experts who engage in production, technology integration, and smart production system design in supply chain management. All information obtained from you will be used for academic purposes only and handled with the utmost confidentiality.

This questionnaire contains two sections:

• Section [A] evaluates the relative importance of one enabler (i) over other enablers (j) in the integration of innovative technologies through your valuable responses.

• Section [B] deals with the general information of the respondents and their respective backgrounds where they work.

This questionnaire might take 10–15 min. Thank you for your valuable time and response.

Section [A]

1. In your opinion, what is the relative importance of one enabler (i) over other enablers (j) in integration of innovative technologies on using the scale (equally important: 0.5; slightly important: 0.6, strongly important: 0.7, very strongly important: 0.8; extremely important: 0.9 and exceptionally more important: 1.0).

Enablers of Innovative Technology Integration	Structure for absorption and diffusion of new technologies (C1)	Leadership for innovation and new technologies (C2)	Economic potential of technology (C3)	Stakeholders in the technology ecosystem' (C4)	Facilitate knowledge transfer (C5)	Competitive benefits (C6)	Legislative framework to facilitate (C7)	Cost modelling to facilitate innovation (C8)	Value offering (C9)
Structure for absorption and diffusion of new technologies (C1)
Leadership for innovation and new technologies (C2)
Economic potential of technology (C3)
Stakeholders in the technology ecosystem' (C4)
Facilitate knowledge transfer (C5)
Competitive benefits (C6)
Legislative framework to facilitate (C7)
Cost modelling to facilitate innovation (C8)
Value offering (C9)

• 2.What is the degree of importance of determinants of drone adoption to achieve enablers of innovative technology on ten-point scale (Exceptionally low: 0.0; Extremely low: 0.1; Very Low: 0.2; Low:0.3; Below Average: 0.4; Average: 0.5; Above Average:0.6; High:0.7; Very high: 0.8; Extremely high: 0.9; Exceptionally high: 1.0).

Determinants	Structure for absorption and diffusion of new technologies (C1)	Leadership for innovation and new technologies (C2)	Economic potential of technology (C3)	Stakeholders in the technology ecosystem' (C4)	Facilitate knowledge transfer (C5)	Competitive benefits (C6)	Legislative framework to facilitate (C7)	Cost modelling to facilitate innovation (C8)	Value offering (C9)
Industrial trends (M1)
Customer’s perspective (M2)
Competitive benchmarking (M3)
Target market (M4)
Product/ material offering (M5)
Product objectives (use and applications) (M6)
Product/Process ideation (M7)
Knowledge transfer(M8)
Strategic alliances (M9)
Overcoming regulation (M10)
Cost modelling (M11)
Value offering (M12)

Section B

Respondent Profile
Name (Optional):
Gender:
Age:
Qualification:
Year of experience:		Designation:		Job responsibility
Company Name:

Appendix 2

$$[\mathrm{M}2]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0.3& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 0.4& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 0& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 0.6& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0.5& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0.4\end{array}\right]$$

$$[\mathrm{M}3]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0.7& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0.8& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 0.1& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 0.9& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 0.7& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0.7\end{array}\right]$$

$$[\mathrm{M}4]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0.2& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 0.5& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 0& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 0& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0\end{array}\right]$$

$$[\mathrm{M}5]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0.4& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0.3& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 0.6& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 1& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 0.6& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0.3& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0\end{array}\right]$$

$$[\mathrm{M}6]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0.2& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 0& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 0& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 0& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0.3\end{array}\right]$$

$$[\mathrm{M}7]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0.3& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 0& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 0.4& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 0& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0.2\end{array}\right]$$

$$[\mathrm{M}8]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0.7& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0.6& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 0& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 0& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 0.7& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0.6\end{array}\right]$$

$$[\mathrm{M}9]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0.2& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 0& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 0& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 0& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0.8& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0\end{array}\right]$$

$$[\mathrm{M}10]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0.3& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ C4& 0.5& 0.2& 0.2& 0& 0.3& 0.5& 0.4& 0.7& 0.4\\ C5& 0.6& 0.3& 0.3& 0.7& 0.6& 0.7& 0.5& 0.5& 0.4\\ C6& 0.4& 0.2& 0.2& 0.5& 0.3& 0& 0.3& 0.3& 0.2\\ C7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0& 0.3& 0.3\\ C8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0& 0.5\\ C9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0\end{array}\right]$$

$$[\mathrm{M}11]=\left[\begin{array}{cccccccccc}-& C1& C2& C3& C4& C5& C6& C7& C8& C9\\ C1& 0.1& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ C2& 0.7& 0.2& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ C3& 0.8& 0.5& 0& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ \mathrm{C}4& 0.5& 0.2& 0.2& 0.2& 0.3& 0.5& 0.4& 0.7& 0.4\\ \mathrm{C}5& 0.6& 0.3& 0.3& 0.7& 0.4& 0.7& 0.5& 0.5& 0.4\\ \mathrm{C}6& 0.4& 0.2& 0.2& 0.5& 0.3& 0& 0.3& 0.3& 0.2\\ \mathrm{C}7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0.3& 0.3& 0.3\\ \mathrm{C}8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 1& 0.5\\ \mathrm{C}9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 0\end{array}\right]$$

$$[\mathrm{M}12]=\left[\begin{array}{cccccccccc}-& \mathrm{C}1& \mathrm{C}2& \mathrm{C}3& \mathrm{C}4& \mathrm{C}5& \mathrm{C}6& \mathrm{C}7& \mathrm{C}8& \mathrm{C}9\\ \mathrm{C}1& 0& 0.3& 0.2& 0.5& 0.4& 0.6& 0.5& 0.3& 0.2\\ \mathrm{C}2& 0.7& 0& 0.5& 0.8& 0.7& 0.8& 0.7& 0.6& 0.5\\ \mathrm{C}3& 0.8& 0.5& 0.2& 0.8& 0.7& 0.8& 0.4& 0.7& 0.8\\ \mathrm{C}4& 0.5& 0.2& 0.2& 0& 0.3& 0.5& 0.4& 0.7& 0.4\\ \mathrm{C}5& 0.6& 0.3& 0.3& 0.7& 0& 0.7& 0.5& 0.5& 0.4\\ \mathrm{C}6& 0.4& 0.2& 0.2& 0.5& 0.3& 0.5& 0.3& 0.3& 0.2\\ \mathrm{C}7& 0.5& 0.3& 0.6& 0.6& 0.5& 0.7& 0& 0.3& 0.3\\ \mathrm{C}8& 0.7& 0.4& 0.3& 0.3& 0.5& 0.7& 0.7& 0& 0.5\\ \mathrm{C}9& 0.8& 0.5& 0.2& 0.2& 0.6& 0.8& 0.7& 0.5& 1\end{array}\right]$$

Funding

This research work was funded by Institutional Fund Projects under grant no. (IFPRC-124-135-2020). Therefore, authors gratefully acknowledge technical and financial support from the Ministry of Education and King Abdulaziz University, Jeddah, Saudi Arabia.

Data availability

Data is available upon request from  S.S. Ali.

Declarations

Ethical statement

Hereby, I /Sadia Samar Ali/ consciously assure that for the manuscript /Identification of Innovative Technology Enablers and Drone Technology Determinants Adoption: A Graph Theory Matrix Analysis Framework/ the following is fulfilled:

1. This material is the authors' own original work, which has not been previously published elsewhere.

2. The paper is not currently being considered for publication elsewhere.

3. The paper reflects the authors' own research and analysis in a truthful and complete manner.

4. The paper properly credits the meaningful contributions of co-authors.

5. The results are appropriately placed in the context of prior and existing research.

6. The authors have no competing interests to declare that are relevant to the content of this article.

7. All authors have been personally and actively involved in substantial work leading to the paper, and will take public responsibility for its content.