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   Table of Contents      
Year : 2022  |  Volume : 8  |  Issue : 3  |  Page : 245-251

Translational Research in Health Care: A Paradigm Shift from Traditional Research

1 Healthcare Technology Innovation Centre (HTIC), Indian Institute of Technology Madras (IITM), Chennai, India
2 HSS Department & Centre for Technology and Policy, Indian Institute of Technology Madras (IITM), Chennai, India
3 Department of Electrical Engineering & Healthcare Technology Innovation Centre (HTIC), Indian Institute of Technology Madras (IITM), Chennai, India

Date of Submission22-Feb-2022
Date of Acceptance03-Apr-2022
Date of Web Publication13-Jul-2022

Correspondence Address:
Muthu Singaram
Healthcare Technology Innovation Centre, No. 1, 5th Floor, ‘C’ Block, Phase-II, IIT Madras Research Park, Kanagam Road, Taramani Chennai-600113, Tamil Nadu
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/mamcjms.mamcjms_15_22

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Background and Objective: The translational research objective is to produce meaningful and applicable results that directly benefit the community. The objective of translational research is to move from traditional research discoveries rapidly and efficiently into practice. Translational research encourages and promotes multidisciplinary collaboration among clinicians, researchers, industry, policy makers, and other related stakeholders. It further incorporates the needs of the general public with communities being engaged to determine their requirements for health invention. It identifies and supports medical and health practices. Translational research is frequently classified by which stage of restatement (from beginning exploration to societal operation and impact) it falls into. Translational research is the process of turning compliances in the laboratory, clinic, and community into interventions that apply to the health of individualities, public from diagnostics, and to medical procedures as well as behavioral changes. Methods: This study adopted a qualitative research methodology based on Hill et al. consensual qualitative research (CQR) to build multiple case studies to acquire the information. We ion.opted to apply a modified method of CQR[9] based on multiple case studies. This is an emerging methodological approach in research. Results: Based on the 24 semi-structured interviews, these interviews were directly with researchers who carry out the research. Twenty-four voluntary researchers participated in the research and these semi-structured interviews were made into 24 case studies to be analyzed. Each case study was built based on the questions on methods of research. These were used to identify and build the tools for practicing translational research. Conclusion: There is a huge untapped potential for India in the area of translational research.

Keywords: Health care, import substitutes, public health, traditional research, translational research Key Message: India needs to make a paradigm shift towards translational research from traditional research in order to reduce the overall health care burden.

How to cite this article:
Singaram M, Muraleedhran V, Sivaprakasam M. Translational Research in Health Care: A Paradigm Shift from Traditional Research. MAMC J Med Sci 2022;8:245-51

How to cite this URL:
Singaram M, Muraleedhran V, Sivaprakasam M. Translational Research in Health Care: A Paradigm Shift from Traditional Research. MAMC J Med Sci [serial online] 2022 [cited 2023 Feb 1];8:245-51. Available from: https://www.mamcjms.in/text.asp?2022/8/3/0/350871

  Introduction Top

Based on the Global Health Expenditure data by the WHO,[10] in India, the government contributes around 40 % and simultaneously 60% is out of pocket expenses from the patients.

References: Department for Promotion of Industry and Internal Trade (DPIIT), RNCOS Reports, Media Reports, Press Information Bureau (PIB), Union Budget 2021-22

India is a land full of opportunities for players in the medical devices industry. The country has also become one of the leading destinations for high-end diagnostic services with tremendous capital investment for advanced diagnostic facilities, thus catering to a greater proportion of population. Besides, Indian medical service consumers have become more conscious towards their health care upkeep.

Indian health care sector is much diversified and is full of opportunities in every segment, which includes providers, payers, and medical technology. With the increase in the competition, businesses are looking to explore the latest dynamics and trends that will have a positive impact on their business. The hospital industry in India is forecast to increase to Rs. 8.6 trillion (US$ 132.84 billion) by FY22 from Rs. 4 trillion (US$ 61.79 billion) in FY17 at a CAGR of 16–17%. The Government of India is planning to increase public health spending to 2.5% of the country’s GDP by 2025. India’s competitive advantage also lies in the increased success rate of Indian companies in getting Abbreviated New Drug Application approvals. India also offers vast opportunities in R&D as well as medical tourism. To sum up, there are vast opportunities for investment in health care infrastructure in both urban and rural India.

Note: The conversion rate used for November 2021 is Rs. 1 = US$ 0.01336.

Disclaimer: This information has been collected through secondary research and India Brand Equity Foundation (IBEF) is not responsible for any errors in the same.

In FY21 amid a push for local medical devices, India imported $6.24 b[11] The DPIIT amended its 2017 Public Procurement Order in June 2020, giving priority to local companies whose products contain 50% or more local content. Products less than 20% local content are categorized as ‘nonlocal suppliers’ and cannot participate in government tenders. India imports 80% of its medical devices.[12]

Public spending on health care in India is just 1.2% of GDP; the government has proposed increasing this amount to 2.5% by 2025, with a special focus on the underprivileged. As expenditures in the Indian health care sector increase, there will be a corresponding growth in the medical equipment market. 

  Literature Review Top

Roger Edwards[13] found some ‘robotic’ innovations to meet the need for a unique technological answer to previously unsolved problems. The compatibility of factors such as noise, smell, appearance, agility, grace, and sterility will affect the acceptance of a robot assistant in human service environments. If a potential consumer’s introduction to a new product is positive, they are more likely to adopt the innovation later. On the health care institutional level, a whole spectrum of decision-makers may need to be convinced at varying degrees of the potential benefits of robotic technology. The decision to implement a robotic innovation in a health care environment does not simply depend on convincing administration and employees. A key element in encouraging health care professionals to utilize and accept a robotic system will be a demonstration of job augmentation with robotization rather than a job replacement. Cost-effective robots, which might save labor costs and improve quality of care, are likely to succeed in the current health care climate provided health care personnel accept robotic technology.

Oturakci and Yuregir[14] found that characteristics of innovation, the external environment, and the organization are significantly associated with the adoption of ISO 9000 standards by manufacturing companies. These findings suggested that the characteristics of both external and internal influence the adoption of innovation. Still, they don’t reveal significant moderating characteristics on the relationship between invention characteristics and invention relinquishment. The purpose of the study was to develop an enhanced model that investigates the impacts of Roger’s invention characteristics with recently added organizational and users’ characteristics on the adoption rate of Enterprise resource planning (ERP) consumers in the Turkish environment. Unlike many studies in the literature in which only a few basic characteristics have been measured, this study uses all the characteristics in Rogers’ innovation diffusion theory and further, combining them with organizational characteristics in a new model, the factors that affect the rate of adoption by ERP applications consumers.

Murphy et al.[15] study explores whether absorptive capacity – one of the most important concepts in the literature on inter-partner learning and innovation in alliances – is often directly transposed to cross-sector alliances. The study suggests that current models of absorptive capacity only imperfectly reflect the learning and innovation dynamics characteristic of cross-sector alliances, thanks to the differences in alliance partners, their goals, and the type of innovations they pursue. This study also introduces the concept of relational capacity for Social Innovation, a model better suited to the analysis of learning and innovation, in the context of cross-sector alliances, especially those operating at the bottom of the economic pyramid.

Roberts et al.[16] studied how design thinking can be applied to health care research. This study also demonstrates how design thinking can foster new approaches to complex and protracted health care problems through human-centered research, collective and diverse teamwork, and rapid prototyping. With unprecedented and growing financial, social, and political pressures, health systems must develop a more robust capacity for better aligning current and future services with the foresight on where, how, when, and with whom health issues may occur. The design process enters a rapidly iterative prototyping and testing phase, in which multiple ideas get into action, often at a small scale and as a trial, to learn something new about the matter or potential solution. Design thinking is most useful in the early innovation process, when problems are not well defined, or it has become clear that current attempts to solve a problem are not working. Process improvement is most valuable when problems and possible solutions are less abstract and more relevant to the current day-to-day operations. Design thinking offers a framework for orienting diverse project teams around problems, as they exist within and are experienced by individuals and communities, rather than around individual expertise, methodology, or organizational structures. This study states that the expanded capacity for and application of design thinking approaches within health care can help drive necessary innovation in health care delivery models. The integration of a design thinking framework not only helps health systems in how to reply to certain changes but also offers them the chance to steer innovation.

Alcorta[17] reports the results of an inquiry into the diffusion of advanced automation in Brazil, India, Mexico, Thailand, Turkey, and Venezuela. It shows that the extent of the use of advanced automation on a normalized basis is higher in Mexican Firms, followed by Thai, Turkish, and Venezuelan. The factors for adoption comprised technical ones such as quality, flexibility, and machine productivity, although industry considerations permeated the relative importance of each factor. Economic factors for adoption included labor and price considerations. The study found that a developing country, while finding out information on advanced automation through trade fairs and suppliers, does not make use of all available sources. The assessment of the potential of the new technologies is comparatively simple and supported by management intuition. There was also little preparation and not enough skilled workers before the installation of the new equipment. The study highlights that the employment of advanced automation in developing countries involves policy intervention at the firm levels, owing to an unstable environment and limited dept of data.

Klingenberg et al.[18] suggest that the impact of an individual operation strategy is difficult to isolate from other activities such as its financial management. Similar variations in results exist in the literature on lean manufacturing and Just In Time (JIT) implementation. The authors suggest that for the former, inventory/current assets how Just in Time changes this ratio, which is the root cause of the insignificant results, is ambiguous.

Strand et al.[19] studies show that socio-technical imaginaries are visions of desired social and technological futures created and sustained by stakeholders in science, industry, and politics. Within the dominating innovation narratives, there are a variety of implicit and explicit beliefs – both descriptive and normative. The new narratives for innovation that the studies unfold may include different perspectives and sources of knowledge, including heterodox economics, bio-economics, science and technology studies, and post-normal Science. There are lots of policies that are aimed at innovation for growth. Many of them are also with some regard to sustainability and the ‘grand challenges’ relating to the environment. It may still be worthwhile to analyze how examples of degrowth statements of a more policy-like nature appear to imagine the role of science and technology in the future (desirable) social life and social order.

Rosenberg’s[20] study shows that medical innovations are highly dependent on breaking down barriers prevalent in the academic world, in the form of disciplinary boundaries that have coalesced into separate departments. To be more specific, some of the biggest breakthroughs for the Life Sciences were from the realm of the Physical Sciences. This study is connected to molecular biology and diagnostic technologies (as well as to the therapeutic technologies that have frequently been owed from them).

Opportunities for transfers of instrumentation and techniques across disciplinary boundaries have been strengthened as medical schools have been located, geographically and organizationally, closer to the universities. The reason is that many of the fundamental breakthroughs have come from outside of what we now call the ‘Life Sciences.’ To be specific, some of the biggest breakthroughs for the Life Sciences were from the realm of the Physical Sciences. The growth in medical science, which began at the antepenultimate of the 19th century with Pasteur’s brilliant creation of the science of bacteriology, led to a vastly increasing degree of specialization in the medical world in both medical research and practice.

Dibra[21] studied the influence of the factors on the integration of sustainable practices into business activities, which is a significant subject discussed in different industries and different scientific disciplines after the late 1980s. The study analyses those models, with the review of literature, which reveals their advantages and limitations within the study of the factors influencing businesses to adopt sustainable tourism practices. These studies conclude that Rogers theory on adaptation and diffusion of innovation is a suitable theoretical model in the study of factors influencing the adoption of sustainable tourism practices in tourism businesses. Theoretical models, more applied, are models to study cost or benefit, stakeholder theory, and theory of the innovation’s diffusion. When the expected benefits exceed the investment cost of a replacement practice, businesses could also be more motivated to adopt this practice. Characteristics of innovation help to elucidate different levels of the adoption of innovation. The spreading out of innovation model takes the dissemination of innovation into consideration among the members of the social organization. Rogers developed the initial model to explain the process of the proliferation of individual innovation. Rogers suggested that the examination of the external environment, measured by open model systems, led to innovation. The spread of innovation theory overcomes the issues of the economic model of the straightforward cost or benefit analysis. This also includes an incentive range covering both the simple model of cost/benefit analysis and the stakeholders theory concerning the adoption of innovation. To summarize, the goal of this study was to assess the theoretical model more suitable for use in research from the view of tourism businesses and to adopt sustainable tourism practices. The paper provides a conceptual research model most appropriate for researchers, who are in the field of sustainable business development.

Wonglimpiyarat and Yuberk[22] studied the issues in drawing on public sector R&D results towards efficient commercialization. The study uses a case study methodology to elucidate the method from the development towards diffusion/commercialization of the two major research funding organizations in Thailand: The National Science and Technology Development Agency (NSTDA) and Thailand Research Fund (TRF). It is argued that R&D takes on different roles within the models of technological change. The innovation process starts with research, invention, innovation, and therefore the diffusion of R&D results. The Thai government has helped private firms within the sort of research grants to bridge the interface between R&D and business opportunities. Variables influence the speed of innovation adoption. Ten projects progressed from the innovation development stage to the market development stage, showing that seven projects failed along the way.

The study suggests that the speed of innovation adoption depends on the interaction with the market and, therefore, the industry. The study found a conversation rate of innovation adoption generated from public R&D (NSTDA and TRF) forcing the Thai government to review its policies in managing the R&D system. The findings suggest that the establishment of a strategic partnership with other research organizations would help the govt research funding organizations to develop multidisciplinary knowledge to manage the complexities or difficulties of innovation. The government research funding organizations should involve customers in the development of product innovations and work closely with the trade promotion agencies to undertake the marketing activities.

Jahanmir and Lages[23] present two studies with high-tech products (mobiles and laptops) that measure the attributes of late adopters. Understanding the diffusion of innovation process means the process of acceptance of a specific product over time by an individual is linked to a social system (Katz, Levin et al (1963) [32]; Rogers, (1962) [33]. This underlines that it is imperative to comprehend why consumers adopt a product more quickly and make it a market winner. The diffusion of innovation curve (Rogers, 1962) introduces the adopter categories: innovators, early adopters, early majority, late majority, and laggards. Late adopters are difficult to be convinced about a new product because late adopters have different needs and expectations than the early adopters and their unique inputs might be useful to conquer new market segments and enter emerging economies. The late-adopter scale enables firms and researchers to identify late adopters and reason out late adoption. After identifying the late adopters, the firms intending to implement an open innovation can include these consumers in their innovation process and benefit from their insights.

In this context, this study’s scale presents three dimensions, representing major attributes of late adopters: slowness of adoption, resistance to innovation, and skepticism. Adoption over time is critical to evaluating the diffusion of innovation. The literature indicates that late adopters are not only resistant to change but also suspicious of the agents of change. They are cautious that innovation should not fail before they adopt it. Knowing the reasons for late adoption enables firms to improve their products based on the late adopter’s insights and address them in a different way. This reduces their innovation adoption time, accelerates the adoption of innovations, and thereby squeeze the diffusion of the innovation curve.

  Synthesis Top

  • The role of national culture in shaping innovation diffusion patterns in different markets.
  • Both external and internal factors influence the adoption of innovation.
  • The concept of relational capacity for Social Innovation, a model better suited to the analysis of learning and innovation in the context of cross-sector alliances.
  • It may still be worthwhile to analyze how examples of degrowth statements of a more policy-like nature appear to imagine the role of science and technology in the future (desirable) social life and social order.
  • Medical innovations are heavily dependent on breaking down the barriers prevalent in the academic world, in the form of disciplinary boundaries that have coalesced into separate departments.
  • Rogers theory on adaptation and diffusion of innovation is a suitable theoretical model in the study of factors influencing the adoption of sustainable tourism practices in tourism businesses.
  • Characteristics of innovation help to elucidate different levels of the adoption of innovation.
  • The spreading out of the innovation model takes up the dissemination of innovation into consideration among the members of the social organization.
  • The innovation process starts with research, invention, and innovation, and therefore the diffusion of R&D results.
  • The speed of innovation adoption depends on the interaction with the market and, therefore, the industry.

  Method Top

In total, 24 interviews[3],[4],[5],[6],[7],[8] were conducted among the reputed researchers around India from leading academic institutions. After each interview, the questions were reviewed to ensure relevance and consistency. A pilot study of two interviews was used to fine-tune the interview questions. Interviews were recorded using a phone recorder.

As far as the profile of the researchers is concerned, all were PhD holders (from local or foreign highly ranked universities), with a minimum of five years (or more) of research experience. Four were working on assistive technology, one in biomaterials, six in treatment, and 13 in devices. All were over 30 years old. All were employed as a faculty or researcher in Indian premier institutions. All faculty were associate professors or professors. Five of them had the industrial experience, but 19 had only academic experiences.

Only one interview was done for each researcher. This decision was made based on Hill et al.[1],[2] as they found second interviews were not as productive as they thought. Sixteen interviews were done face to face, six interviews via phone or skype, and two by email. Besides the pilot interviews and email responses, all interviews were recorded. (This was to ensure a reliable collection of data.) The semi-structured interview gathers information on the understanding of Translational Research and have developed and commercialized a product what methodology was applied for this. ([Table 2]).
Table 1 Medical device import by India

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Table 2 Response (Methodology applied) from the researchers

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  Discussion Top

Based on the study, it is clear that all the researchers are not clear with their understanding of translational research. However, saying that all of them have products, only one-third of them actually have reached the market. These have reached the market because they had a discussion with the stakeholders. They have first achieved their problem solution fit and later product market fit to understand the needs of both product and market. It shows that they performed an in-depth customer segment survey to understand the market needs and potential and side by side created value proposition by introducing accessible features and amicable presentation. These findings appear to be the same in all the areas. It is also clear that there are no mechanisms to conduct the research in a systemic way.


In the absence of any set method to conduct translational research, it is important that researchers are given an orientation on translational research when they join these institutions, in particular health care research. It is worth noting that all the researchers are able to produce a product. There are not able to take these to the market, so again a training or a center within the institution can help in this area.

A set of tools and principles can help India move towards translational research that in turn would reduce the health burden. We can start with the Three Box Solution.[24],[25] This solution has three boxes, Box 1 states manage the present, Box 2 states selectively forget the past, and Box 3 states create future. The researchers are extremely good at Box 1, we need to work on Box 2 to forget and replace things that do not work by doing this we will move to the Box 3 to create the future. In case of Box 3 would be Translational Research.

Now in order to move to Box 3, we need new skills and tools. A tool that has worked well for start-up business model[26] and lean canvas[27] used in lean start-ups[28],[29] can be adapted as a research monetization canvas.[30] It is also important to look at the quadruple aim[31] when looking at academic research. In doing so, we would ensure all the stakeholder interest is addressed.


The authors acknowledge the valuable inputs from the researchers who took part in the study.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Hill CE, Thompson BJ, Williams EN. A guide to conducting consensual qualitative research. Couns Psychol 1997;25:517–72.  Back to cited text no. 1
Hill CE, Knox S, Thompson BJ, Williams EN, Hess SA, Ladany N. Consensual qualitative research: an update. J Couns Psychol. 2005;52:196–205.  Back to cited text no. 2
Dul J, Hak T. Case Study Methodology in Business Research. 1st ed. Butterworth: Heinemann; 2008.  Back to cited text no. 3
Gillham B. Case study research methods. 1st ed. Continuum. 2000.  Back to cited text no. 4
Hancock DR, Algozzine B. Doing Case Study Research - A practical guide for beginning researchers. Teacher’s College Press; 2006.  Back to cited text no. 5
Towgood KJ, Meuwese JDI, Gilbert SJ, Turner MS, Burgess PW. Advantages of the multiple case series approach to the study of cognitive deficits in autism spectrum disorder. Neuropsychologia 2009;47:2981–8.  Back to cited text no. 6
Van den Berg A, Struwig M. Guidelines for researchers using an adapted consensual qualitative research approach in management research. Electron J Bus Res Methods 2017;15:109–19.  Back to cited text no. 7
Yin RK. Case Study Research: Design and Methods. 5th ed. SAGE, Inc. p. 201–4.  Back to cited text no. 8
Anderson CA, Leahy MJ, DelValle R, Sherman S, Tansey TN. Methodological application of multiple case study design using modified consensual qualitative research (CQR) analysis to identify best practices and organizational factors in the public rehabilitation program. J Vocat Rehabil. 2014;41:87–98.  Back to cited text no. 9
Global health expenditure database (WHO) captured on the 20/2/2022 https://apps.who.int/nha/database/country_profile/Index/en  Back to cited text no. 10
India imported $6.24b worth of medical devices in FY21 amid local production push Captured on the 20/2/2022 from https://www.thehindubusinessline.com/news/india-imported-624-b-worth-of-medical-devices-in-fy21-amid-local-production-push/article37984105.ece  Back to cited text no. 11
Healthcare and medical equipment. Captured on the 22/2/2022 from https://www.trade.gov/country-commercial-guides/india-healthcare-and-medical-equipment#.  Back to cited text no. 12
Edwards R. Diffusion of robotic innovations in health care environments using the interactive evaluation methodology. Robot Auton Syst 1989;5:241–50.  Back to cited text no. 13
Oturakci M, Yuregir OH. New approach to Rogers’ innovation characteristics and comparative implementation study. J Eng Technol Manag 2018;47:53–67.  Back to cited text no. 14
Murphy M, Perrot F, Rivera-Santos M. New perspectives on learning and innovation in cross-sector collaborations. J Bus Res 2012;65:1700–9.  Back to cited text no. 15
Roberts JP, Fisher TR, Trowbridge MJ, Bent C. A design thinking framework for healthcare management and innovation. Healthcare 2016;4:11–4.  Back to cited text no. 16
Alcorta L. The diffusion of advanced automation in developing countries: factors and adoption process. Technovation 1999;19:163–75.  Back to cited text no. 17
Klingenberg B, Timberlake R, Geurts TG, Brown RJ. The relationship of operational innovation and financial performance—a critical perspective. Int J Prod Econ 2013;142:317–23.  Back to cited text no. 18
Strand R, Saltelli A, Giampietro M, Rommetveit K, Funtowicz S. New narratives for innovation. J Cleaner Prod 2018;197:1849–53.  Back to cited text no. 19
Rosenberg N. Some critical episodes in the progress of medical innovation: an Anglo American perspective. Res Policy 2009;38:234–42.  Back to cited text no. 20
Dibra M. Rogers theory on diffusion of innovation—the most appropriate theoretical model in the study of factors influencing the integration of sustainability in tourism businesses. Procedia Soc Behav Sci 2015;195:1453–62.  Back to cited text no. 21
Wonglimpiyarat J, Yuberk N. In support of innovation management and Roger’s Innovation Diffusion theory. Gov Inf Q 2005;22:411–22.  Back to cited text no. 22
Jahanmir SF, Lages LF. The late-adopter scale: a measure of late adopters of technological innovations. J Bus Res. 2016;69:1701–6.  Back to cited text no. 23
Govindarajan V. Leading innovation with Vijay Govindarajan professional certificate on Edx; 2020. Available from: https://www.edx.org/professional-certificate/dartmouthx-leading-innovation-with-vijay-govindarajan  Back to cited text no. 24
Singaram M, Muraleedhran VR & Sivaprakasam, M; 2022. A Framework for Future Indian Healthcare Translation Research, International Conference On ’Interdisciplinary Research InTechnology and management’. http://irtm.smartsociety.org/  Back to cited text no. 25
Osterwalder A. Business model generation. 1st ed. Wiley; 2010.  Back to cited text no. 26
LEANSTACK AM. https://leanstack.com/  Back to cited text no. 27
Blank S. The Four Steps Epiphany Successful Strateg Prod That Win. 1st ed. Wiley; 2020.  Back to cited text no. 28
Ries E. The Lean Startup. UK: Penguin; 2011.  Back to cited text no. 29
Singaram M, Muraleedhran VR. Sivaprakasam, M & Pathak S; 2022. Monetization canvas framework to efficiently assess the impact of research outcome, 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) and the Affiliated Conferences. (Book Chapter) DOI: http://doi.org/10.54941/ahfe1001509  Back to cited text no. 30
Singaram M, Muraleedhran VR, M. Sivaprakasam and S. Pathak. Adapting The Quadruple Aim For The Benefit Of The Stakeholders In Academic Healthcare Research, 2022 IEEE Technology and Engineering Management Conference (TEMSCON EUROPE), 2022, pp. 146-151, doi: 10.1109/TEMSCONEUROPE54743.2022.9801924.  Back to cited text no. 31
Katz E, Levin M. L., Hamilton H (1963). Traditions of Research on the Diffusion of Innovation. American Sociological Review, 28,237–252.  Back to cited text no. 32
Rogers E. M (1962). Diffusion of Innovations. New York: The Free Press of Glencoe.  Back to cited text no. 33


  [Table 1], [Table 2]


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