Technology, IS and Sustainability: A Public Interest Research Agenda
Section 3.2: Education, awareness & changed working practices
Contribution 12: Technology, Information Systems and Sustainability: A Public Interest Research Agenda Professor Katina Michael and Dr Roba Abbas
3.2.7. Contribution 12 – technology, information systems and sustainability: a public interest research agenda – Professor Katina Michael and Dr Roba Abbas
3.2.7.1. The negative impact of technology and information systems on the environment
The coupling of natural and human systems is defined by highly integrated and complex system dynamics resulting from human-nature interactions (Liu et al., 2007). This has presented significant global challenges and wicked problems (Buchanan, 1992, Brown et al., 2010) that require immediate attention in view of sustainability, particularly given the centrality of technology and information systems (IS) to these interactions. A multifaceted feature of the natural system that is integral to all forms of life is biodiversity, which can be considered at three levels: genetic diversity, species diversity and ecosystem diversity (Chapin III et al., 2000). Biodiversity is both implicitly and explicitly linked to health and wellbeing, in addition to sustainable development programs (Naeem et al., 2016, World Health Organization and Secretariat of the Convention on Biological Diversity, 2015). Human actions, notably decisions concerning technology and information systems, increasingly impact biodiversity. In line with the 26th UN Climate Change Conference of the Parties (COP26) Sustainability Governing Principles, there is a pressing need to engage in deliberate management of potential environmental impacts to encourage inclusivity, health and sustainability (UN Climate Change Conference UK 2021).
Adverse impacts on the natural world resulting from existing and emerging technologies and IS can be described as negative externalities (Dasgupta and Ehrlich, 2013, Perrow, 1991). The field of environmental economics, among other things, involves the study of externalities that generate tangible and intangible costs to the physical environment and its inhabitants (Cropper & Oates, 1992). It is often difficult to quantify these costs given the reach of an incident, and the extent of its irreversible impact. For example, significant oil spills cause major externalities that cannot readily be measured, such as the Deepwater Horizon oil spill, which was estimated to have spilled 4,900,000 barrels of crude oil into the Gulf of Mexico in 2010 (Beyer, Trannum, Bakke, Hodson, & Collier, 2016). There are two main types of negative externalities; the first refers to negative production externalities that can cause, for example, air or water pollution through manufacturing plants powered by technology and other forms of engineering; and the second denotes negative consumption externalities that can cause for instance, traffic congestion and noise pollution that are generated by systems (Biglan, 2009). Externalities caused by technologies and IS may be unanticipated, unintended, and even paradoxical (Pringle, Michael, & Michael, 2016).
Unanticipated externalities refer to those incidents and system failures that were not factored into scenario planning and risk management processes during systems design and development, such as the Fukushima Daiichi nuclear disaster whereby a substantial wave surged over defences and flooded reactors causing major radiation leakage (von Hippel, 2011). Unintended consequences of technologies and IS are those that were discounted as potential outcomes of a respective system, but nonetheless transpired (Ash, Berg, & Coiera, 2004). An example is the use of irrigation systems for crops, which subsequently contributes to soil erosion and increased soil salinity (Khan, Tariq, Yuanlai, & Blackwell, 2006). Conversely, paradoxical externalities emerge from attempts to use technologies and IS for advantage and benefit, but where the result is a negative outcome on another aspect of the environment. An example is the introduction of Internet of Things (IoT) devices to monitor energy systems to lower consumption that requires the devices to be powered and over time to be replaced, causing often toxic and non-biodegradable e-waste that is disposed of in landfills (Mukhopadhyay & Suryadevara, 2014).
A common element underpinning these types of negative externalities is the impact on public resources that are shared by communities (Pigou, 1920). These include the ocean and its fisheries and clean drinking water, amongst others, leaving individuals and communities vulnerable, potentially compromising their health and wellbeing. Furthermore, these undesirable impacts extend to the natural system and environment. These impacts can be linked to technologies and IS that do not suitably consider socio-ecological and socio-technical considerations, and that fail to recognize the value of design, testing and validation, with sustainability and people in mind (Chen et al., 2008, Trist, 1981).
The mitigation of the undesirable consequences of existing and emerging technologies and IS necessitates intervention in the form of sustainability transitions (Loorbach et al., 2017, Smith et al., 2005), moving beyond the existing multi-level perspective (Geels, 2004, Geels, 2011) toward transdisciplinarity. At the heart of these transitions is the establishment and socio-technical (re)design of higher education frameworks resulting in new forms of knowledge production, allowing for the design and redesign of human-centered socio-technical systems for sustainability, and consequently for human benefit (Geels, 2010, Verbong and Geels, 2010). The proposed socio-technical intervention would require commitment to a series of stages or flows, as depicted in Fig. 1, which we define as the Socio-Technical Sustainability Design Cycle. These include: (i) establishing a detailed understanding and conceptualization of the tightly coupled natural and human systems in context and in view of interactions and feedback loops; (ii) implementing the appropriate sustainability transition through a process of socio-technical (re)design; (iii) measuring the effect of the design over time in view of the degree to which negative externalities are reduced or mitigated; (iv) assessing the impact on human health and wellbeing, in addition to environmental sustainability; and (v) iterating to ensure continual evaluation of the tightly coupled system given its evolving nature. It should be noted that despite this proposed cycle, there will be cases in which paradoxical externalities occur, which is an inherent and unavoidable characteristic of tightly coupled systems. This occurs for two reasons: (i) events in nature are not always predictable no matter how “controlled” the socio-technical transitions are through, for example, regulation and policy mandates (Smith et al., 2005), and (ii) interventions themselves are a form of “technology” that are subject to independent and autonomous forces that are “uncontrollable” (Winner, 1978).
Fig. 1. Socio-technical sustainability design cycle.
3.2.7.2. Sustainability transitions through transdisciplinarity
The proposed model suggests that our global challenges and significant problems require a transdisciplinary lens, beyond a multi-level perspective, in which design interventions are required in the form of sustainability transitions. Within this model, the information systems discipline has a significant and mediating role given its socio-technical orientation and appreciation of the open systems paradigm (Scott and Davis, 2015, von Bertalanffy, 1950, Watson et al., 2010). For instance, step (ii) in Fig. 1 would markedly involve a redefinition of technological and information system design and development processes (Schoormann, Stadtländer, & Knackstedt, 2021), characterized by the emergence of a supportive human-centered, transdisciplinary educational framework (Crow & Dabars, 2015) oriented toward a public interest technology (PIT) research agenda (Abbas et al., 2021a, McGuinness and Schank, 2021, Michael and Abbas, 2020).
Transdisciplinarity, in the context of the proposed sustainability transitions, typifies trans-institutional, trans-sectoral and trans-national frameworks bringing together at a minimum industry, government and academia toward the production of knowledge (Crow & Dabars, 2017, p. 474; Hadorn, 2008). This involves recognition that while all problems are local and community focused, their impacts are increasingly global, given the age of entanglement we now live in (Hillis, 2016 as cited in Crow & Dabars, 2020, p. 381), and the tight coupling of natural and human systems, as described above. In considering sustainability transitions more specifically, the proposed Socio-Technical Sustainability Design Cycle would promote Public Interest Technology (PIT) research, empowering citizens and communities (Pitt, Michael, & Abbas, 2021). It would additionally emphasize the importance of directing attention to highly integrative basic and responsive (HIBAR) research (Crow & Dabars, 2020, p. 376), which is still lacking internationally, despite the creation of globally oriented goals such as the United Nations Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs) (World Health Organization, 2015). In transitioning to HIBAR research and practice that requires PIT processes and innovations, we are seeking to recognize negative externalities and to continually strive to reduce them by introducing alternative socio-technical design options in each selection environment (Nelson & Winter, 1977, pp. 61–70).
3.2.7.3. A public interest technology research agenda for sustainability
A preliminary phase in operationalising the proposed design cycle and implementing sustainability transitions is the strategic realignment of IS, and/or the higher education system to proceed toward the production of knowledge and socio-technical innovations that are purpose driven and in the public interest (Abbas & Michael, 2021), facilitating an integrated and responsive approach to addressing our global challenges and key problems (Melville, 2010). Capturing first principles from foundational theories and frameworks across disciplines, including IS, and merging them to form a transdisciplinary lens will allow for the creation of models and simulations that afford a high-level view or conceptualization of existing major forces and counterforces (Frodeman, 2014, Scholz, 2020). Achieving such a capability commands stakeholder engagement in the provision of data to an emergent knowledge system, encapsulating multi-level perspectives (local-national-global) within socio-cultural, business, techno-economic and institutionally-relevant policy contexts (Köhler et al., 2019). We suggest that the role of emerging technologies and IS, as they relate to this knowledge system, be embedded within a PIT framework (see Abbas, Pitt, & Michael, 2021, Fig. 1), represented as a complex, open socio-technical ecosystem that is informed by the landscape of technological and IS developments. The framework also acknowledges the corresponding application areas and the link to financing models, stakeholder engagement (balancing lived experience and professional expertise), transdisciplinary theorizations/conceptualizations and operationalisation to achieve the goal of sustainability toward human health and wellbeing (Abbas et al., 2021).
3.2.7.4. The role of IS/IT education
The subsequent and corresponding phase in operationalising the proposed Socio-Technical Sustainability Design Cycle relates to the elimination of disciplinary silos in higher education institutions, that have existed since scientific endeavor was acknowledged as the foundation of the Age of Enlightenment. Through the deliberate reconfiguration or redesign of university structures, new transdisciplinary agendas can be positioned to respond to global challenges (Crow & Dabars, 2015, ch. 5; Gholami, Watson, Hasan, Molla, & Bjorn-Andersen, 2016). In order to ensure our long-term sustainability as a species and a planet, university design must undergo a rapid rethink, becoming more adaptive and agile but also closely aligning to public and planetary challenges (Crow & Dabars, 2020). The transition to transdisciplinarity, even interdisciplinarity, remains fraught with risk principally with respect to forming meaningful ties between Computing, Informatics, Business (including Information Systems) and Engineering schools in addition to other non-STEM domains of knowledge. A harmonization is required not only within the STEM disciplines, but going beyond traditional collaborative fields to incorporate action-oriented endeavors through the creation of Schools dedicated to Sustainability or Life Sciences (Tejedor, Segalàs, & Rosas-Casals, 2018). Here the traditional research university is challenged to apply itself to real-world problems. However, irrespective of the inevitable difficulties, the COVID-19 pandemic has demonstrated the importance of solidarity toward collective action, harnessing the knowledge produced from both professional expertise/practice and the lived experience. The IS discipline is in a prime position to offer information and knowledge management expertise to support transdisciplinarity, and it is our obligation to actively implement sustainability transitions and responsible systems design (Monson, 2021),IS research (Pan & Zhang, 2020) and innovation (Stilgoe, Owen, & Macnaghten, 2013) in the interest of sustainable futures (Hadorn et al., 2006, Hess and Ostrom, 2007).
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Citation: Katina Michael and Roba Abbas, 12 November 2021, “Technology, Information Systems and Sustainability: A Public Interest Research Agenda“, in Y Dwivedi et al., “Climate Change and COP26: Are Digital Technologies and Information Management part of the problem or the solution? An Editorial Reflection and Call to Action”, Journal International Journal of Information Management , 102456, JJIM_102456PIIS0268-4012(21)00149-3. https://www.sciencedirect.com/science/article/pii/S0268401221001493
Additional information for editorial at large:
Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action
☆ Yogesh K. Dwivedia,b, Laurie Hughesc, Arpan Kumar Kard,e, Abdullah M. Baabdullahf, Purva Groverg, Roba Abbash, Daniela Andreinii, Iyad Abumoghlij, Yves Barlettek, Deborah Bunkerl, Leona Chandra Krusem, Ioanna Constantioun, Robert M. Davisono, Rahul De’p, Rameshwar Dubeyq, Henry Fenby-Taylorr, Babita Guptas, Wu Het, Mitsuru Kodamau, Matti M ̈antym ̈akiv,*, Bhimaraya Metriw, Katina Michaelx, Johan Olaiseny, Niki Panteliz, Samuli Pekkolaaa, Rohit Nishantab, Ramakrishnan Ramanac,ad, Nripendra P. Ranaae, Frantz Roweaf, Suprateek Sarkerag, Brenda Scholtzah, Maung Seinai, Jeel Dharmeshkumar Shahaj, Thompson S.H. Teoak, Manoj Kumar Tiwarial,am, Morten Thanning Vendeløan, Michael Wadeao
aEmerging Markets Research Centre (EMaRC), School of Management, Swansea University, Bay Campus, Fabian Bay, Swansea SA1 8EN, Wales, UK
bDepartment of Management, Symbiosis Institute of Business Management, Pune & Symbiosis International (Deemed University), Pune, Maharashtra, India
cEmerging Markets Research Centre (EMaRC), School of Management, Swansea University, Bay Campus, UK
dSchool of Artificial Intelligence, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India
eDepartment of Management Studies, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India
fDepartment of Management Information Systems, Faculty of Economics and Administration, King Abdulaziz University, Jeddah, Saudi Arabia
gInformation Systems, International Management Institute New Delhi, Qutab Institutional Area, New Delhi, India
hSchool of Business, University of Wollongong, Wollongong, Australia
iDepartment of Management, University of Bergamo, Italy
jDirector of Faith for Earth, United Nations Environment Programme, USA
kMontpellier Business School (MBS), Montpellier, France
lProfessor (Research Affiliate), Systems and Information, The University of Sydney Business School, Honorary Professor, Systems and Information, Sydney Institute for Infectious Diseases, Australia
mUniversity of Liechtenstein, Vaduz, Liechtenstein
nDepartment of Digitalization, Copenhagen Business School, Denmark
oDepartment of Information Systems, City University of Hong Kong, Hong Kong
pIndian Institute of Management Bangalore, India
qLiverpool Business School, Liverpool John Moores University, UK
rHead of Information Management, the Centre for Digital Built Britain, University of Cambridge, UK
sCollege of Business, California State University Monterey Bay, USA
☆Roba Abbas, Daniela Andreini, Iyad Abumoghli, Yves Barlette, Deborah Bunker, Leona Chandra Kruse, Ioanna Constantiou, Robert M. Davison, Rahul De’, Rameshwar Dubey, Henry Fenby-Taylor, Babita Gupta, Wu He, Mitsuru Kodama, Matti M ̈antym ̈aki, Bhimaraya Metri, Katina Michael, Johan Olaisen, Niki Panteli, Samuli Pekkola, Rohit Nishant, Ramakrishnan Raman, Nripendra P. Rana, Frantz Rowe, Suprateek Sarker, Brenda Scholtz, Maung Sein, Jeel Dharmeshkumar Shah, Thompson S.H. Teo, Manoj Kumar Tiwari, Morten Thanning Vendelø, and Michael Wade have made equal contributions and are placed in alphabetical order.
* Corresponding author. E-mail addresses: y.k.dwivedi@swansea.ac.uk, ykdwivedi@sibmpune.edu.in (Y.K. Dwivedi), d.l.hughes@swansea.ac.uk (L. Hughes), arpan_kar@yahoo.co.in (A.K. Kar), Baabdullah@kau.edu.sa (A.M. Baabdullah), groverdpurva@gmail.com (P. Grover), roba@uow.edu.au (R. Abbas), daniela.andreini@unibg.it (D. Andreini), iyad.abumoghli@un.org (I. Abumoghli), y.barlette@montpellier-bs.com (Y. Barlette), deborah.bunker@sydney.edu.au (D. Bunker), leona. chandra@uni.li (L. Chandra Kruse), ic.digi@cbs.dk (I. Constantiou), isrobert@cityu.edu.hk (R.M. Davison), rahul@iimb.ac.in (R. De’), r.dubey@ljmu.ac.uk (R. Dubey), Henry.Fenby-Taylor@cdbb.cam.ac.uk (H. Fenby-Taylor), bgupta@csumb.edu (B. Gupta), whe@odu.edu (W. He), kodama.mitsuru@nihon-u.ac.jp (M. Kodama), matti.mantymaki@utu.fi (M. M ̈antym ̈aki), director@iimnagpur.ac.in (B. Metri), katina.michael@asu.edu (K. Michael), johan.olaisen@bi.no (J. Olaisen), niki.panteli@rhul.ac.uk (N. Panteli), samuli.pekkola@tuni.fi (S. Pekkola), rohit.nishant@fsa.ulaval.ca (R. Nishant), director@sibmpune.edu.in (R. Raman), nrananp@gmail.com (N.P. Rana), frantz.rowe@univ-nantes.fr (F. Rowe), ss6wf@comm.virginia.edu (S. Sarker), Brenda.scholtz@mandela.ac.za (B. Scholtz), Maung.K.Sein@usn.no (M. Sein), jeelshah.2412@gmail.com (J.D. Shah), bizteosh@nus.edu.sg (T.S.H. Teo), mkt09@hotmail.com (M.K. Tiwari), mtv. ioa@cbs.dk (M.T. Vendelø), michael.wade@imd.org (M. Wade).
ABSTRACT
The UN COP26 2021 conference on climate change offers the chance for world leaders to take action and make urgent and meaningful commitments to reducing emissions and limit global temperatures to 1.5 ◦C above pre- industrial levels by 2050. Whilst the political aspects and subsequent ramifications of these fundamental and critical decisions cannot be underestimated, there exists a technical perspective where digital and IS technology has a role to play in the monitoring of potential solutions, but also an integral element of climate change solutions. We explore these aspects in this editorial article, offering a comprehensive opinion based insight to a multitude of diverse viewpoints that look at the many challenges through a technology lens. It is widely recognized that technology in all its forms, is an important and integral element of the solution, but industry and wider society also view technology as being part of the problem. Increasingly, researchers are referencing the importance of responsible digitalization to eliminate the significant levels of e-waste. The reality is that tech-nology is an integral component of the global efforts to get to net zero, however, its adoption requires pragmatic tradeoffs as we transition from current behaviors to a more climate friendly society.
Introduction
The 2021 United Nations (UN) Climate Change Conference (COP26) held in Glasgow UK, brings together many of the worlds’ leaders to address the critical aspects of global warming. The conference aims to gain commitment for sustained progress towards the Paris Agreement and UN framework convention on climate change, by limiting increased global temperatures to 1.5 ◦C above pre-industrial levels (COP26, 2021). The Intergovernmental Panel on Climate Change (IPCC) identified in its 2018 report that global emissions would need to be at net zero by at least 2050 to retain a “high confidence” level of limiting temperature in-creases to sustainable levels (Masson-Delmotte et al., 2018). In her speech at the conference, US Treasury Secretary Janet Yellen stated that - “rising to this challenge will require the wholesale transformation of our carbon-intensive economies," and that "addressing climate change is the greatest economic opportunity of our time." (COP26, 2021).
The transition toward net zero requires significant changes at a societal and industrial level and governments, as well as corporations, are increasingly turning to technological innovations to meet net zero emission targets (Miller, 2020). Digital technologies offer the potential to deliver sustained solutions to many of the seemingly intractable societal challenges relating to climate change (George, Merrill, & Schil-lebeeckx, 2021). The World Economic Forum (WEF) in its - Harnessing Technology for the Global Goals report, jointly authored with PwC, identifies the significant role that digital technology can play in improving resilience to global warming related, natural hazards, reducing emissions and enhancing the ability for humans to take the necessary steps to realize net zero. The WEF report identifies how digital technologies can help to automate and significantly improve the efficiency of industrial, manufacturing and agricultural processes and that Artificial Intelligence (AI) based systems could contribute to a reduction of 4% in global emissions by 2030 (World Economic Forum & PwC, 2021).
Although advancements in technologies are closely associated with offering solutions to global warming, the digital discourse also high-lights the negative impacts of the widespread use of technology in the context of waste products, resource usage and CO2 emissions. The widely reported impact of vast bitcoin mining farms in various parts of the world and their appetite for significant energy consumption - 121.36 terawatts hours per year (CBECI, 2021) – illustrates the dichotomy of rapid technological advancement and potential barriers to net zero by 2050 (Mora et al., 2018). The debates surrounding the convergence of the digital and net zero imperatives are beginning to gain traction within the academic literature, where studies have started to focus on the role of digital technologies through a positive contribution lens, but also a reflective perspective, recognizing some of the negative aspects of the rapid adoption of technology (George et al., 2021; Merrill, Schille-beeckx, & Blakstad, 2019). What is clear is that, whilst the emerging diverse and disparate discourse has offered insight to many of the significant challenges and barriers to net zero from the digital perspective (George, Howard-Grenville, Joshi, & Tihanyi, 2016; Luo, Zhang, & Marquis, 2016), there exists a limited contribution from a wider and more informed multiple perspective context. This study contributes to the digital technology and climate change discourse, via the individual discussions on a multitude of interrelated sub-topics. Each invited expert has offered their own unique insight to the myriad of complexities and dependencies to attaining net zero by 2050.
The remaining sections of this article are organized as follows. Section 2 presents a brief review of existing literature in this space. Section 3 presents the experts’ perspectives related to core themes surrounding Y.K. Dwivedi et al. information management (IM)/information technology (IT)/information systems (IS) and climate change. Section 4 - presents an overview of the key perspectives from the submitted full opinion articles. The main discussion section is presented in Section 5, where we assess the significant challenges and key contributions from the invited expert sub-missions. Section 6 concludes the paper by discussing implications for both research and practice.
2.Background literature review
The primary database used for the literature search was Scopus. Keywords such as “information systems” or “information technology” or “IT sector” were combined (AND operator) with keywords “environ-ment”, “sustainability”, “sustainable” and “climate”. The search taxon-omy retrieved articles that had the combination of keywords in the article title, author keywords, or abstract. Via a process of filtering to eliminate non-relevant studies, a total of 372 articles remained. These articles were evaluated via their abstract to assess their suitability against the following two research questions.
•RQ1: Does the digital technology and IS/IT sector have a negative impact on the environment and how can it be reduced?
•RQ2: How can digital technology and IS/IT be utilized to mitigate the causes and impact of climate change?
After a further process of scanning of the title and abstract for the relevance of the article to the research questions, 88 articles remained. Additionally, ScienceDirect and Web of Science were also used, following similar approaches which resulted in 16 additional articles.
2.1.(RQ1) Does the digital technology and IS/IT sector have a negative impact on the environment and how can it be reduced?
Despite the contribution of the IS/IT industry toward the economic and social welfare of society, IS/IT has often been criticized for having a negative environmental impact. Concerns surrounding the adverse ef-fects both hardware and software have on the environment date back to the Y2K era which led to the massive adoption of enterprise systems (Miyamoto, Harada, & Fujimoto, 2001). These negative impacts include high levels of energy consumption, greenhouse gas emissions and toxic disposal of IS/IT systems (Muregesan, 2008). The disposal of electronic waste (e-waste) while following recycling processes has been widely viewed as not being environmentally friendly, especially the impact of fossil fuels or respiratory inorganics (Barba-Guti ́errez, Adenso-Diaz, & Hopp, 2008). Refurbished ICTs are often used in developing countries where devices tend to have a short life-span and subsequently create environmental damage during disposal (Osibanjo & Nnorom, 2007). Studies have argued that electricity is a major cause of climate change, as many power stations throughout the world still rely on fossil fuels to generate electricity (Asongu, Agboola, Alola, & Bekun, 2020; Tambur-ini, Rossi, & Brunelli, 2015). Energy hungry technologies such as ap-plications of blockchain in the form of bitcoin, has been widely criticized for producing over 22–29 million metric tonnes of carbon dioxide emission each year. These figures are comparable to the carbon dioxide production of entire countries such as Jordan and Sri Lanka (Marr, 2018; Stoll, Klaaßen, & Gallersd ̈orfer, 2019). Technologies such as the Internet of Things (IoT), sensors and actuators have a shorter lifespan which leads to increased waste in the environment (Chakraborty & Gupta, 2016; Chakraborty, Gupta, & Sarkar, 2014; Niˇzeti ́c, ˇSoli ́c, Gonz ́alez-de, & Patrono, 2020). Digital transformation initiatives such as smart cities have concerns surrounding ICT waste management, energy manage-ment and emission management which needs to be addressed for achieving long term sustainability and viability (Ismagilova, Hughes, Dwivedi, & Raman, 2019).
From an IS/IT perspective, IoT and Artificial Intelligence (AI) could potentially offer solutions for reducing the impact of technology projects (Salam, 2020). High ICT-driven initiatives need to plan for sustainability by thinking from the perspective of social welfare and e-waste impact (Kar, Ilavarasan, Gupta, Janssen, & Kothari, 2019). Wireless communication technologies need adaptations so that emissions can be further reduced. AI can operate with such technologies to enhance the usage of bandwidth and energy consumption to significantly reduce the carbon footprint of the telecom sector Ullah et al. (2020). Similarly, AI inte-grated with blockchain has been found to positively impact water management and climate control (Lin, Petway, Lien, & Settele, 2018). AI can manage and reduce energy consumption within smart cities (S ̧erban & Lytras, 2020). Studies have identified that blockchain applications can improve sustainable practices in supply chain management and agricultural practices (Kshetri, 2021). Similarly, within nano-technology applications, AI has provided benefits through better precision in agricultural water distribution delivering positive impacts on efficient use of natural resources. The communication of sustainability related messages within social media has greatly increased during the pandemic (Grover, Kar, & Ilavarasan, 2019; Grover, Kar, Gupta, & Modgil, 2021; Yadav, Kar, & Kashiramka, 2021). The literature has highlighted that during crisis periods IS research can provide “signposting” for sustainability actions through improved digital monitoring, tackling information flow and paranoia, and orchestrating data ecosystems for improved decision making (Pan & Zhang, 2020).
The focus towards renewable energy has increased dramatically. The IRENA (2021) report indicates that jobs in sustainability and cleaner energy are increasing exponentially year on year, especially in solar and wind energy. This shift towards greener energy consumption is common across industries producing and consuming technology products and services. There is evidence that if stakeholders are convinced about energy management, their engagement in Green IS/IT programs will increase (Nyberg, 2018).
The literature highlights the use of theories such as: Institutional Theory, Resource Based View, Technology Organization Environment framework, Theory of Planned Behavior and Motivational Theory as the dominant models used in the IS literature (Asadi & Dahlan, 2017). Lesser used theoretical lenses such as: Upper Echelon Theory, Self Determination Theory, Green Theory, Norm Activation Model, Elaboration Likelihood Model, Dynamic Capability Theory, Actor-Network Theory and Expectancy Theory. could be used to explore future research relating to environmental impacts of technology. (Tables 1 and 2).
2.2.(RQ2) How can digital technology and IS/IT be utilized to mitigate the causes and impact of climate change?
As early as 2008, Murugesan (2008) provided directions towards a greener IS/IT strategy. A holistic focus towards Greener IT entails reducing the energy consumption of computational devices. It also gives directions on reuse, refurbish and recycling of IS/IT products. Such a focus requires an organizational imperative as indicated by Butler (2011), whereby the study draws on institutional theory to explain the multitude of forces acting on organizations from the institutional, environment and organizational fields for environmental sustainability. Reduction of carbon based energy consumption directly leads to reduction of greenhouse gas emissions. The study by Simmonds and Bhattacherjee (2012) indicates that existing IT infrastructure, alignment of business strategy and relative advantages of green IT initiatives, have an overall positive impact on the adoption of IT initiatives within firms.
Recent IT/IS literature indicates that technology can be a solution for better environmental management and sustainability. For example, Wang X. (2015), Wang Y. (2015) highlights that IS/IT competence enables the integration of technology within the environmental management processes to improve performance. The same study demonstrated the positive impact of IT competence on IT-environmental management integration. The research by Jnr (2020) indicates that there is a signif-icant relationship between integrated technologies and Green IS/IT innovation. The study by Ojo and Fauzi (2020) indicates that Y.K. Dwivedi et al.
Miyamoto,Harada,&Fujimoto,2001Muregesan,2008Osibanjo&Nnorom,2007Asongu,Agboola,Alola,&Bekun,2020Tamburini, Rossi,&Brunelli,2015Marr, 2018Chakraborty&Gupta,2016Chakraborty,Gupta,&Sarkar,2014Ismagilova,Hughes,Dwivedi,&Raman,2019Salam,2020Kar, Ilavarasan,Gupta,Janssen,&Kothari,2019Ullah et al. (2020)Lin, Petway,Lien,&Settele,2018Kshetri,2021Grover,Kar,&Ilavarasan,2019Grover,Kar, Gupta,&Modgil,2021Yadav,Kar,&Kashiramka,2021Pan&Zhang,2020IRENA(2021)Nyberg,2018Asadi&Dahlan,2017Murugesan(2008)Butler(2011)SimmondsandBhattacherjee(2012)WangX. (2015)WangY. (2015)Jnr (2020)Ojo and Fauzi(2020)
environmental awareness and leadership commitment positively impacts engagement in Green IS/IT practices. Further Marques et al. (2019) highlight that universities now consider emissions and Green IT principles to reduce the adverse impacts on the climate, while designing their curriculum. Audits in Green IT in enterprises help to enhance focus towards maintaining environmental orientation and better impacts on climate (Pat ́on-Romero et al., 2021). These audits offer a view on the organization’s position along the green IT capability maturity model from ISO/IEC 15504 to ISO/IEC 33000.
Within workplace infrastructure management, sensors and actuators are often being used for water management and energy consumption in smart buildings (toilet management, ventilation and air quality management) and smart devices (like air conditioners and lighting systems). These technologies have been observed to have brought in wide positive impacts on the climate within the existing literature (Zarindast, Sharma, & Wood, 2021). For example, blockchain applications are not always energy hungry, and often applications in different use cases such as SolarCoin and VerdePay may actually help in reducing carbon footprints (Howson, 2019). Applications of analytical models for information management enables more efficient energy management in smart cities (Gellert, Florea, Fiore, Palmieri, & Zanetti, 2019). Blockchain applications may enable a more efficient IoT ecosystem and thereby reduce energy consumption (Sharma et al., 2020). AI technologies such as deep learning together with big data analytics have been used for image mining for underwater environment management and air quality management (Kushwaha et al., 2021; Nair et al., 2021).
Driven by the pandemic, working from home has significantly increased, which has drastically reduced travel to workplaces, thereby reducing the carbon footprint from travel and maintaining office infra-structure. This change toward a work from home culture has been facilitated using video conferencing and collaboration systems enabled through ICTs (Chakraborty & Kar, 2021; Galanti et al., 2021; Richter, 2020). A recent review on AI and its possible impacts towards sustain-ability argue that AI will play a critical role beyond enabling better consumption of energy, water, and land usage, and it will facilitate environmental governance with greater effectiveness (Nishant et al., 2020). Whilst the literature has exhibited an emerging focus on Green IS and sustainability within the information management literature, there is still tremendous scope for impactful research on many aspects of the use of technology to combat climate change.
3.Multiple perspectives from invited contributors
This section, in alignment with the approach set out in previous studies (Dwivedi et al. 2015, 2020, 2021a, 2021b, 2022), develops a set of unique expert contribution narratives that explore many of the key topics related to digital and IS technologies and climate change. This topic has numerous threads and interdependencies as many of the invited experts offer their own perspectives and viewpoints on the topic. The expert contributions are largely presented in an unedited form, as expressed by each of the contributors. The perceived unevenness of the logical flow inherent with this approach is countered by the capturing of the distinctive orientations of the expert perspectives related to the chosen topic (Dwivedi et al. 2015, 2020, 2021a, 2021b, 2022). The list of contributions is provided in Table 3 and extended in further detail within this section.