Abstract
In the wake of the COVID-19 pandemic, the world seems to have jumped off the hinges. At the start of the pandemic countries needed to take number of steps to contain the spread and subsequently find their way to exit the pandemic and release the lockdowns. In the next steps the societies will need to prepare strategies to efficiently manage the consequent global endemic. In so doing, the role of information technologies and information systems will be pivotal.
The role of technology and engineering management has been instrumental and will continue to be significant in supporting economic growth, business development, and corporate strategies. The nationwide lockdowns as well as the logistics, transportation, and trade restrictions have led to huge disruptions in both demand and supply. Moreover, for healthcare related supplies and resources, government bodies, NGOs and industries worldwide are collaborating to fulfil the demand. Information technologies and information systems play significant roles in managing business operations as well as making society more resilient during pandemic situations inter alia to help establish versatile and timely data analytics tools in addressing business disruption challenges. From communication (Daim et al. 2012) and information transparency perspectives, technologies such as blockchain can enhance traceability among the blocks of the value chain (Zelbst et al. 2019). This allows the related parties and stakeholders to adopt the sense and respond strategy (Haeckel, 1999; Araz et al. 2020; Choi 2020).
On this basis, proper emergency plans, including the updated project management (Křečková et al. 2020) schemes and drug development programs (Simões-Freitas et al. 2019) can be established. Moreover, the use of information technology, such as artificial intelligence (AI) and business analytics (Einhorn et al. 2019; Elmousalami 2020), and Internet of Things (IoTs) can help create effective and efficient managerial decisions to enhance forecasting (Pereira et al.2019), smart disaster management (Neelam and Sood 2020), logistics service operations (Tsai et al. 2012), and healthcare industry (Yin et al. 2016; Firouzi et al. 2018; Thibaud 2018; Chung and Jung 2020). As a result, proper risk management (Sun et al. 2020) plans and tools should be developed to reduce the loss incurred by disruptions.
In a pandemic, decisions have to be made ad hoc based on incomplete and sometimes unreliable information. A good example is the social distance that individuals are recommended to keep while in physical proximity. Depending on the country/context, this distance varies between 3 feet and 2 meters (Helsenorge, 2020; CDC, 2020; Australian Department of Health, 2020; GOV.UK, 2020), since clearly, reliably calculating the safe distance requires virologic and epidemiologic information that was/is not (immediately) available (Blocken et al, 2020). There is an array of similar examples. Scientific community has already recognised this gap (Jewell et al, 2020; Wenham, 2020). Consequently, the research concerning pre-disaster plans and post-disaster responses are crucial (e.g., Sadiqi et al. 2017; Basu et al. 2018; Shavarani et al. 2019). Furthermore, COVID-19 can become a disease that is present at an approximately constant level within society i.e. endemic, but new pandemics are likely to emerge. The scientific communities can support the shift to more evidence-based policy-making (Marston and Watts, 2003) in times of pre-pandemic, pandemic, post-pandemic and endemic.
Bridging these gaps is essential for all future pandemics as well as handling the pandemics occurring alongside endemics. Re-thinking the existing information technologies and information systems can support bridging the gaps, as it is information systems that help decision makers by providing accurate and timely information, which can be critical for authorities to make right decisions in turbulent environments (Alkhaffaf, 2012). In contrast, unreliable information can result from conflicts that arise when trying to create local information systems for pandemic response within centralized healthcare systems (Timpka et al, 2011). While each of the stakeholders have relied on modern information technology during recent infectious disease outbreaks, insufficient attention has been paid to the fact that the theoretical possibilities of this technology are limited by characteristics of the health system of which the information system is but a part (Sandiford et al, 1992). Connecting various information systems must be comprehensive, and only as such can it consequently lead to understanding new and more robust implications of information systems adoption, as well as provide evidence-based information to support effective and efficient decision-making process and policy changes (Leidner et al, 2015). There seems to be more value to be derived from information systems support – with advances possible in terms of system functions, technical components or pandemic evidence compilation (Timpka et al, 2011).
The role of technology and engineering management has been instrumental and will continue to be significant in supporting economic growth, business development, and corporate strategies. The nationwide lockdowns as well as the logistics, transportation, and trade restrictions have led to huge disruptions in both demand and supply. Moreover, for healthcare related supplies and resources, government bodies, NGOs and industries worldwide are collaborating to fulfil the demand. Information technologies and information systems play significant roles in managing business operations as well as making society more resilient during pandemic situations inter alia to help establish versatile and timely data analytics tools in addressing business disruption challenges. From communication (Daim et al. 2012) and information transparency perspectives, technologies such as blockchain can enhance traceability among the blocks of the value chain (Zelbst et al. 2019). This allows the related parties and stakeholders to adopt the sense and respond strategy (Haeckel, 1999; Araz et al. 2020; Choi 2020).
On this basis, proper emergency plans, including the updated project management (Křečková et al. 2020) schemes and drug development programs (Simões-Freitas et al. 2019) can be established. Moreover, the use of information technology, such as artificial intelligence (AI) and business analytics (Einhorn et al. 2019; Elmousalami 2020), and Internet of Things (IoTs) can help create effective and efficient managerial decisions to enhance forecasting (Pereira et al.2019), smart disaster management (Neelam and Sood 2020), logistics service operations (Tsai et al. 2012), and healthcare industry (Yin et al. 2016; Firouzi et al. 2018; Thibaud 2018; Chung and Jung 2020). As a result, proper risk management (Sun et al. 2020) plans and tools should be developed to reduce the loss incurred by disruptions.
In a pandemic, decisions have to be made ad hoc based on incomplete and sometimes unreliable information. A good example is the social distance that individuals are recommended to keep while in physical proximity. Depending on the country/context, this distance varies between 3 feet and 2 meters (Helsenorge, 2020; CDC, 2020; Australian Department of Health, 2020; GOV.UK, 2020), since clearly, reliably calculating the safe distance requires virologic and epidemiologic information that was/is not (immediately) available (Blocken et al, 2020). There is an array of similar examples. Scientific community has already recognised this gap (Jewell et al, 2020; Wenham, 2020). Consequently, the research concerning pre-disaster plans and post-disaster responses are crucial (e.g., Sadiqi et al. 2017; Basu et al. 2018; Shavarani et al. 2019). Furthermore, COVID-19 can become a disease that is present at an approximately constant level within society i.e. endemic, but new pandemics are likely to emerge. The scientific communities can support the shift to more evidence-based policy-making (Marston and Watts, 2003) in times of pre-pandemic, pandemic, post-pandemic and endemic.
Bridging these gaps is essential for all future pandemics as well as handling the pandemics occurring alongside endemics. Re-thinking the existing information technologies and information systems can support bridging the gaps, as it is information systems that help decision makers by providing accurate and timely information, which can be critical for authorities to make right decisions in turbulent environments (Alkhaffaf, 2012). In contrast, unreliable information can result from conflicts that arise when trying to create local information systems for pandemic response within centralized healthcare systems (Timpka et al, 2011). While each of the stakeholders have relied on modern information technology during recent infectious disease outbreaks, insufficient attention has been paid to the fact that the theoretical possibilities of this technology are limited by characteristics of the health system of which the information system is but a part (Sandiford et al, 1992). Connecting various information systems must be comprehensive, and only as such can it consequently lead to understanding new and more robust implications of information systems adoption, as well as provide evidence-based information to support effective and efficient decision-making process and policy changes (Leidner et al, 2015). There seems to be more value to be derived from information systems support – with advances possible in terms of system functions, technical components or pandemic evidence compilation (Timpka et al, 2011).
| Original language | English |
|---|---|
| Specialist publication | IEEE Transactions on Engineering Management |
| Publisher | IEEE |
| Publication status | Submitted - 2020 |
