call-for-papers

Special Issue: Reimaging emerging technologies in the new normal: Forecasting growth trajectory, risk and resistance towards a friction-free diffusion in varied industry verticals

Guest Editors

Nazrul Islam, University of Exeter Business School, England, UK 
N.Islam@exeter.ac.uk

Amandeep Dhir, University of Agder, Norway
amandeep.dhir@uia.no

Shalini Talwar, K.J. Somaiya Institute of Management, India
shalini.t@somaiya.edu

Steven Walsh, University of New Mexico, USA
walsh@unm.edu

Theme

Emerging technologies refer to the technologies that are still in infancy as far their development and applications are concerned. In this context, technologies such as blockchain, the internet of things (IoT), artificial intelligence (AI), robotics process automation, 3D printing, big data analytics, and cloud computing have been discussed by scholars as key emerging technologies that are changing the face of businesses (e.g., Islam et al., 2020; Kache & Seuring, 2017; Kapletia et al., 2019). These technologies have transformed engineering as well as organizational workflow by enabling automation of tasks previously unthought of, digitization of assets, integration of value chains, unhindered communication, collaboration in virtual settings, and so on (PwC, 2016). Organizations across the globe spanning economies at different levels of development have become mindful of the technologies associated with Industry 4.0 revolution due to their multiple benefits (Adebanjo et al., 2021). At the same time, these technologies have disruptive potential with implications for planning, engineering and enterprise research, development investment and government (X. Li et al., 2019)

In addition to the aforementioned emerging technologies related mainly to Industry 4.0, various other technological innovations with more user orientation can also be included under this umbrella. These are wearables, virtual and augmented reality (VR/AR) products, drone-based delivery, next-generation mobile payment solutions, mobile applications, and online shopping, which impact individuals’ work and personal lives (Kaur et al., 2020; Talwar, Dhir, et al., 2020; Talwar, Talwar, et al., 2020). Consequently, these technologies can be put into two distinct buckets, one with business-oriented applications (e.g., blockchain, artificial intelligence, 3D printing, and so on) and the second with a consumer orientation (e.g., drone-based delivery, next-generation mobile payments, and so on).

A vital aspect of technological and engineering innovations is their acceptance by potential users (businesses/individuals) and fast diffusion. However, scholars have noted that despite offering several advantages and affordances, diffusion of most technological innovations has been less than smooth, inhibited by individual and organizational resistance, ranging from postponement, opposition to out-right rejection ( Talwar et al., 2020). In this regard, scholars have drawn upon a combination of both technology adoption and resistance theories to examine resistance towards technological and engineering innovations (Oh et al., 2019). Notably, most of the research in the area has remained focused on products/services such as mobile payments (Kaur et al., 2020; Khanra et al., 2021), smart products (Mani & Chouk, 2017), and so on. In comparison, forecasting growth, risk and resistance to emerging technologies such as 3D printing, IoT, blockchain, artificial intelligence, big data analytics, and so on has not been examined much by scholars. This represents a visible gap in the existing literature since it is crucial to understand individual and organizational resistance and the potential barriers that can hinder the smooth diffusion of these technologies. Due to the lack of research findings, the concerned stakeholders continue to remain deprived of incisive theoretical and practical insights that can help in better diffusion of these technologies.

The review of the prior literature examining the resistance to technological innovations indicates the availability of limited methodological and theory-based perspectives (Talwar et al., 2020). Such little variety in research design and data analysis methods is counterproductive for advancing research in the area. Thus, it is essential to promote a research agenda focussed not only on examining the drivers of resistance to emerging technologies but also on applying varied research approaches to yield robust results on technology forecasting and growth trajectory. Additionally, there is little clarity about what constitutes individual and organizational resistance in the context of emerging technologies and how it hinders their smooth and early diffusion. Furthermore, despite the life-changing experience of the COVID-19 pandemic unfolding across the world, very few studies have endeavoured to examine how the pandemic has transformed the perception of multiple stakeholders towards these emerging technologies anecdotally discussed to be too disruptive in the past. The uncertainty unleashed by the ongoing pandemic has also made it crucial for developing better ability of forecasting growth and risks associated with specific emerging technologies. This is in consonance with prior studies, wherein scholars have contended that risk forecasting and analyses of varied emerging technologies are very important ingredients of proactive governance and strategic planning (M. Li, 2019)

Special Issue’s scope, including potential themes to be addressed in the Special Issue

Since it is well-acknowledged in the literature that academic research can contribute positively towards the development and evolution of emerging technologies (Tegarden et al., 2012), the lack of findings as discussed above is a void that needs to be addressed exigently. The current call for papers responds to this imperative need to enhance the theoretical and practical understanding of reimaging emerging technologies to the new normal and for forecasting their growth trajectory. In this regard, we invite researchers to provide insights and future directions on how resistance to these game-changing technologies can be countered and how they can be leveraged to evolve an eco-system offering multiple advantages to organizations, society, and individuals. Thereby, we invite scholars and practitioners to submit path-breaking conceptual, theoretical, and empirical studies examining individual and organizational perspectives on resistance towards the successful application and integration of emerging technologies.

The submissions may be related to but not limited to the following research topics:• What are the antecedents and outcomes of the individual and organizational resistance towards emerging technologies?• Why some managers and businesses oppose or resist the adoption of emerging technologies, even though these technologies offer ubiquitous and game-changing business opportunities?• What factors exacerbate multiple stakeholders’ resistance toward using emerging distributed manufacturing technologies such as 3D printing despite their vast potential to support point-of-contact manufacturing of products?• How can seminal (e.g., Innovation Resistance Theory, Status Quo Bias, Dual Factor, and Valence) and novel theoretical frameworks be used to conceptualize and uncover the foundations of individual and organizational resistance towards the use of emerging technologies?• What is the scope for deepening methodological approaches to better understand individual and organizational resistance towards using emerging technologies (e.g., experimental, longitudinal, experience sampling, and log data-based studies)?• Why are regulators, social and political systems in many countries resisting the adoption of various emerging technologies (e.g., blockchain, drone-based delivery)• How has COVID-19 impacted the resistance towards using emerging technologies such as drone-based delivery of essentials (e.g., food, medicine, medical equipment, COVID-19 testing kits) sync with the social distancing requirements imposed by the ongoing COVID-19 pandemic?• How has resistance towards the use of various technological innovations (e.g., mobile payments, shopping, and other retail sectors) changed in response to the quarantine and self-isolation measures introduced to control the spread of COVID-19?• How will individual and organizational resistance towards the use of emerging technologies at work mutate with the increase in remote working culture (work from home) due to COVID-19?• How critically important it is to focus on forecasting the evolution, development and diffusion of emerging technologies in the backdrop of the relatively new threat of health crisis (i.e., COVID-19 pandemic), which has become an additional dimension to be considered in governmental and organizational decision-making?

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper.Manuscripts should be submitted through the publisher’s online system. Submissions will be reviewed according to the journal’s rigorous standards and procedures through a double-blind peer review by at least two qualified reviewers. 

Submission Process

Please prepare the manuscript according to IEEE-TEM’s guidelines (http://ieee-tmc.org/tem-guidelines) and submit to the journal’s Manuscript Central site (https://mc.manuscriptcentral.com/tem-ieee). Please upload the paper on the IEEE TEM Editorial Manager clearly indicating in the cover letter that the submission is for the IEEE TEM Special Issue on ‘Reimaging emerging technologies in the new normal: Forecasting growth trajectory, risk and resistance towards a friction-free diffusion in varied industry verticals’.

Schedule
Papers submitted by December 31, 2022

Guest Editor Bios 

Nazrul Islam is Associate Professor of Innovation/Entrepreneurship at the University of Exeter Business School, England, UK. He holds a PhD in innovation management. His research interests include innovation in high-tech industries, the management of emerging and discontinuous innovations, organizational capabilities and collaborative innovations. His research was published in the leading international journals and he has complemented his peer reviewed journal efforts with three books. Prof Islam’s research received awards including the ‘Brad Hosler Award for Outstanding Paper’ from USA; and the ‘Pratt & Whitney Canada Best Paper Award’ from Canada. Prof Islam serves on the board of directors for Business and Applied Sciences Academy of North America. He is currently Editor-in-Chief of International Journal of Technology Intelligence and Planning and an Associate Editor of Technological Forecasting & Social Change. Prof Islam has published in a number of Management and Engineering journals, such as Technological Forecasting and Social Change, Technovation, IEEE Transaction on Engineering Management, Journal of Business Research among others. 

Amandeep Dhir is a Professor of Research Methods at University of Agder, Norway. He is also a visiting professor at Norwegian School of Hotel Management, University of Stavanger, Norway. His research appears in Technological Forecasting and Social Change, Journal of Retailing and Consumer Services, International Journal of Information Management, Computers in Human Behaviour, Computers in Industry, International Journal of Hospitality Management, Journal of Cleaner Production, Food quality and preferences, Appetite, Information Technology & People, Australasian Marketing Journal, and Enterprise Information Systems among others

Shalini Talwar is Associate Professor at KJ Somaiya Institute of Management Studies and Research, Mumbai, India. She has over 22 years of experience in industry and management education. She has published 4 books and more than 25 research papers in national and international publications of repute. Her book on Security Analysis and Portfolio Management, published by Cengage Publishers, is being used as textbook in many institutes. She is the founding editor-in-chief of a research journal and has edited several research publications over the years.

Steven Walsh is a Distinguished Full Professor of Management of Technology at Anderson School of Management, University of New Mexico, USA. Prof. Walsh received his Ph.D. in Strategic Management from the Rensselaer Polytechnic Institute in 1995 and joined the faculty at UNM in 1998. Prof. Walsh has published in a number of Management and Engineering journals, such as Technological Forecasting and Social Change, Technovation, Creativity and Innovation Management, Journal of IEEE Transaction on Engineering Management, Journal of Small Business Management, among other publications. Prof. Walsh has been a Special Issue editor for a number of journals such as Journal of Business Ethics, Technovation, Creativity and Innovation Management Journal and Technological Forecasting and Social Change

References

Adebanjo, D., Laosirihongthong, T., Samaranayake, P., & Teh, P. L. (2021). Key Enablers of Industry 4.0 Development at Firm Level: Findings From an Emerging Economy. IEEE Transactions on Engineering Management, 1–17. https://doi.org/10.1109/TEM.2020.3046764

Islam, N., Marinakis, Y., Majadillas, M. A., Fink, M., & Walsh, S. T. (2020). Here there be dragons, a pre-roadmap construct for IoT service infrastructure. Technological Forecasting and Social Change155, 119073. https://doi.org/10.1016/j.techfore.2017.09.016

Kache, F. and S. (2017). Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International Journal of Operations & Production Management37(1). https://doi.org/10.1108/IJOPM-02-2015- 0078

Kapletia, D., Phillips, W., Medcalf, N., Makatsoris, H., McMahon, C., & Rich, N. (2019). Redistributed manufacturing – challenges for operations management. Production Planning & Control30(7), 493–495. https://doi.org/10.1080/09537287.2018.1540057

Kaur, P., Dhir, A., Singh, N., Sahu, G., & Almotairi, M. (2020). An innovation resistance theory perspective on mobile payment solutions. Journal of Retailing and Consumer Services55. https://doi.org/10.1016/j.jretconser.2020.102059

Khanra, S., Dhir, A., Kaur, P., & Joseph, R. P. (2021). Factors influencing the adoption postponement of mobile payment services in the hospitality sector during a pandemic. Journal of Hospitality and Tourism Management46, 26–39. https://doi.org/10.1016/j.jhtm.2020.11.004

Li, M. (2019). Capturing the Risk Signals for a Specific Emerging Technology: An Integrated Framework of Text Mining. IEEE Transactions on Engineering Management, 1–14. https://doi.org/10.1109/TEM.2019.2930335

Li, X., Xie, Q., Jiang, J., Zhou, Y., & Huang, L. (2019). Identifying and monitoring the development trends of emerging technologies using patent analysis and Twitter data mining: The case of perovskite solar cell technology. Technological Forecasting and Social Change146, 687–705. https://doi.org/10.1016/j.techfore.2018.06.004

Mani, Z., & Chouk, I. (2017). Drivers of consumers’ resistance to smart products. Journal of Marketing Management33(1–2), 76–97. https://doi.org/10.1080/0267257X.2016.1245212

Oh, Y. J., Park, H. S., & Min, Y. (2019). Understanding location-based service application connectedness: Model development and cross-validation. Computers in Human Behavior94(October 2018), 82–91. https://doi.org/10.1016/j.chb.2019.01.003

PwC. (2016). Industry 4.0: Building the digital enterprise., 2016 Global Industry 4.0 Survey. https://www.pwc.com/gx/en/industries/industries-4.0/landing-page/industry-4.0-building-yourdigital-enterprise-april-2016.pdf

Soh, P. Y., Heng, H. B., Selvachandran, G., Anh, L. Q., Chau, H. T. M., Son, L. H., Abdel-Baset, M., Manogaran, G., & Varatharajan, R. (2020). Perception, acceptance and willingness of older adults in Malaysia towards online shopping: a study using the UTAUT and IRT models. Journal of Ambient Intelligence and Humanized Computing0123456789. https://doi.org/10.1007/s12652-020-01718-4

Talwar, S., Dhir, A., Kaur, P., & Mäntymäki, M. (2020). Barriers toward purchasing from online travel agencies. International Journal of Hospitality Management89(June 2019), 102593. https://doi.org/10.1016/j.ijhm.2020.102593

Talwar, S., Talwar, M., Kaur, P., & Dhir, A. (2020). Consumers’ resistance to digital innovations: A systematic review and framework development. Australasian Marketing Journal28(4), 286–299. https://doi.org/10.1016/j.ausmj.2020.06.014

Tegarden, L. F., Lamb, W. B., Hatfield, D. E., & Ji, F. X. (2012). Bringing emerging technologies to market: Does academic research promote commercial exploration and exploitation. IEEE Transactions on Engineering Management59(4), 598–608. https://doi.org/10.1109/TEM.2011.2170690

IEEE Transactions on Engineering Management is journal of the Technology and Engineering Management Society of IEEE, published quarterly since 1954. It is dedicated to the publication of peer-reviewed original contributions, by researchers and practitioners, regarding the theory and practice of engineering, technology, and innovation management.

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Tugrul U Daim, PhD PICMET Fellow
Professor and Director
Technology Management Doctoral Program
Department of Engineering and Technology Management
Maseeh College of Engineering and Computer Science
Portland State University, Portland OR
United States

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