Main Menu

My Account
Online Free Samples
   Free sample   Covid 19 and the new technologies of organizing digital exhaust

COVID19 and the new technologies of organizing: digital exhaust, digital footprints, and artificial intelligence in the Wake of remote work


Task: State the purpose of the report. Why your technological topic is important How this technological topic developed; past to present development of the topic including year and if name changed for example, Google pay started as Google wallet in 2011.Brief description of the technology used in this topic and what it is used for.How is it used as a business tool and is this effective. You can compare with the past.How does this relate to course content and discussion on the nature of the relationship between digital technologies and both old and newly emerging theories on business and management structures and practices



This research examines the significance of COVID-19 and the new organizing technologies, notably the usage of artificial intelligence, digital exhaust, and digital footprints in the wake of remote work (Teiuan and Deaconu 2021). The platform and software used, as well as the different kinds of enterprises and organizations that employ these technologies, are all thoroughly described in the paper. The paper also explores how the organization has changed its practices as a result of these technologies, as well as the rise of new organizations that are centered around digital technology and pose a threat to an established organization.


Importance of the topic

The COVID-19 epidemic has significantly increased the usage of digital and remote work, necessitating adoption and competitiveness from organizations (Teiuan and Deaconu 2021). Understanding the significance of digital exhaust digital footprints and artificial intelligence is crucial if organizations are to succeed in the post-pandemic era.

Development of the topic

For many years, digital technology development has been an ongoing process. But the COVID-19 epidemic has expedited the uptake and application of digital technologies. Remote employment has become the norm as a result of the widespread lockdowns and social isolation tactics, which have increased digital exhaust and digital footprints (Aloisi and De Stefano 2022). The expansion of digital footprints is also a result of e-commerce and online buying. More than ever, artificial intelligence (AI) is a crucial tool for companies to address the needs of their customers. Artificial intelligence (AI) is being used to automate tasks, enhance decision-making, and provide individualized experiences through chatbots and virtual assistants in addition to predictive analytics and machine learning. Businesses have started to embrace blockchain technology more frequently as they realize its potential to simplify processes and cut expenses. With the advent of smart homes and cities, the Internet of Things (IoT) has also undergone substantial evolution (Pal, Zhang and Siyal 2021). The creation of 5G networks is anticipated to hasten the adoption of IoT by enabling the connection of more devices and facilities quicker and more effective data transport.

Description of the technology

The enormous amount of data produced by digital interactions is referred to as "digital exhaust”. All online behavior, including web searches, social media posts, and email correspondence, is included in this data. A digital footprint is a trail of data left behind by people as they move around the digital world and it is made up of the information that is generated from these interactions. Artificial intelligence (AI) is a field of study that uses machine learning and algorithms to analyze vast volumes of data and anticipate future outcomes (Teiuan and Deaconu 2021). Artificial intelligence (AI) can be used to analyze digital waste and produce insightful data on consumer behavior and preferences. AI may be used to automate processes and give the user more individualized experiences. AI can be used, for instance, to analyze consumer sentiment trends in social media posts. Businesses can utilize this data to customize their marketing campaigns and enhance customer service. AI can also be used to automate processes like chatbots and customer service questions. In addition to enhancing client experience, this can save businesses time and money.

Technological platforms and software usage

People generate a vast amount of data in their daily interactions with technology as a result of the expansion of digital platforms. One example of a platform that creates digital exhaust and digital footprints is a search engine (Comunello, Martire, and Sabetta, 2022). Other examples include social media sites, email providers, and messaging apps. The term "digital exhaust” describes the information produced as a result of using digital platforms such as search history, website visiting patterns, and online purchases. Digital footprints, on the other hand, refer to the traces that people's online behavior, such as social media post email correspondence, and online comments, leave behind. Specialized software is needed to make sense of this enormous volume of data.

Examples of software that can assist with the analysis of digital pollution and digital footprints include machine learning techniques and data analytics tools. Data analytics tools can visualize and understand data to find insights and guide decision-making whilst machine learning algorithms can spot patterns and trends in the data and forecast future behaviors (Sarker 2021). The way Businesses and organizations work has been revolutionized by the use of digital platforms and software. They have made marketing more personalized, increased client involvement, and improved communication possible. The usage of digital platforms and software can expose people to potential data breaches and cyberattacks, thus there are privacy and security issues as well. Therefore, it is crucial to put policies in place to safeguard personal data and guarantee its ethical usage.

Businesses and organizations that use the technology

Healthcare: One of the biggest shifts in recent years has been the adoption of telemedicine services, which has put the healthcare sector at the forefront of digital transformation (Stoumpos, Kitsios, and Talias, 2023). Remote patient access to medical care is made possible through telemedicine services, which is crucial during the COVID-19 pandemic. Telemedicine has decreased the number of hospital visits required by patients, lowering the risk of infection spread. Additionally, telemedicine has made it possible for medical professionals to schedule consultations and follow-up appointments for patients who reside in far-off locations, hence enhancing patient access to medical services. Healthcare institutions have made investments in Electronic Health Records (EHRs) and video conferencing technologies in order to deploy telemedicine services.

Finance: The financial sector has also embraced digital tools to enhance customer experience and streamline internal operations. To provide 24/7 customer care, for instance, numerous banks and financial institutions have introduced chatbots and virtual assistants (Khan and Rabbani 2020). Finance organizations have invested in digital infrastructure for corporate digital solutions including customer relationship management (CRM) systems and data analytics tools. By allowing businesses to gather and analyze client data, they are better able to provide and visualized financial goods and services. In order to create detective models and automate decisions making processes, finance organizations have also engaged in data analytics and artificial intelligence specialist.

Retail:To increase their online presence and draw customers, retail companies have reacted to this trend by investing in eCommerce platforms and digital marketing. Retail businesses have invested in digital infrastructures such as order management systems and online payment gateways, to adopt e-commerce platforms. Organizations can securely and effectively execute online transactions with the help of these solutions.

Use of technology as a business tool

The retail industry nowadays going to significant changes.Digital technology has also been utilized by the retail sector to facilitate online shopping and enhance supply chain management. A growing number of consumers now prefer to shop online in order to lower the risk of infection, Especially, during the COVID-19 pandemic. To increase their online presence and draw customers, retail companies have reacted to this trend by investing in eCommerce platforms and digital marketing. Retail businesses have invested in digital infrastructures such as order management systems and online payment gateways, to adopt e-commerce platforms. Organizations can securely and effectively execute online transactions with the help of these solutions. Additionally, to analyze customer data and create predictive models for better product recommendations and supply chain management, retail organizations have engaged data analysts and artificial intelligence specialists.


The implication of this technology in Retail industry

Numerous industries have been significantly impacted by digital technology and organization has changed their management procedures to include digital decision-making. This has been especially clear in the business use of digital tools to facilitate online commerce, permit remote work, and enhance the consumer experience in response to the covid19 pandemic.Retail Industry utilized the data to learn more about the behavior, Preferences, and needs of their customers, Businesses can personalize product offers, target marketing campaigns, and optimize their operations for optimal efficiency by analyzing this data. Similar to digital footprints, digital footprints describe the trail of information users leave behind when using digital tools and services. This includes data on internet behavior geography location and personal preferences. This information can be used by Retail Industry to generate comprehensive consumer profiles and more successful marketing plans. Retail Industries are utilizing artificial intelligence (AI) another technology to analyze and exploit data. This can acquire insights into customer behavior patterns, automate procedures, and make data-driven decisions by utilizing machine learning algorithms (Teiuan and Deaconu 2021).

Old and new emerging theories

• Decision-making theory:The decision-making theory is an old idea that is still important in the retailsector (Mishra, Singh and Koles 2021). According to decision-making theory making a decision entail identifying a problem, gathering pertinent data, weighing your options, and selecting the best course of action.This theory is relevant to decisions made in the retail sector about pricing customer experience and inventory management.

• Quantitative theory:The quantitative theory which emphasizes the value of data and statistical analysis and decision making is another old theory.This theory is applicable to the use of data analytics in the retail sector to uncover patterns in consumer behavior, products, and sales performance. The retail sector can use data to decidepricing, marketing tactics, and inventory management.

• System theory: Another old theory that pertains to the retail sector is the system theory. This theory emphasizes the significance of comprehending how various system components interact and function together (Liu et al. 2021). This theory is applicable to supply chain management in the retail sector, where retail sector organizations must comprehend how various supply chain elements interact to ensure prompt delivery of goods and services to clients.

• Contingency theory: Contingency theory is the newly emerging theory that emphasizes the value of adjusting to ever-changing environments(Hanelt et al., 2021). Businesses in the retail sector must adjust to the shifting demands and tastes of customers. Businesses must adapt and incorporate digital technologies, for instance, when more customers switch to online purchasing, to suit these shifting needs.

Challenges and opportunities


The requirement for high-quality data is one of the main difficulties posed by the usage of digital technology (Almeida, Santos, and Monteiro 2020). It might be challenging to acquire the data and analyze it efficiently given the growing volume of data that retail sector organizations are producing. Inaccurate insight and decision-making may result which could be harmful to an organization's success.

The possibility of biases in algorithms presents another difficulty. Although algorithms are intended to be objective, their developers’ prejudices might nonetheless have an impact on them (Almeida, Santos, and Monteiro 2020). Unintended repercussions could include biased hiring or lending practices.

In addition, cyber security is a challenge in digital technology. The risk of cyberattacks has increased along with the use of digital technologies (Almeida, Santos, and Monteiro 2020). Organizations of the retail sector must make sure that their systems are secured from data breaches.


Despite these difficulties, the employment of digital technologies offers a wide range of options.

The opportunity to increase operational effectiveness is one such opportunity. Organizations of retail industry can minimize the time and resources needed for tasks and processes by automating them, freeing up resources for higher-value operations (Almeida, Santos, and Monteiro 2020).

Personalizing customer interactions is a further possibility. Organizations of retail industry can gather information on the preferences and behavior of their customers by using digital technologies like customer relationship management (CRM) systems, which enables them to better adapt their offers and suit their needs.

Additionally, data-driven decision-making is improved by digital technologies. The large volume of data may be gathered and analyzed, enabling organizations to make better decisions that result in better outcomes (Almeida, Santos, and Monteiro 2020).

New organizational models and business models

The rise of new business models and organizational structures is possibly the most important opportunity provided by the use of digital technology (Almeida, Santos, and Monteiro 2020). The capacity to access customers through digital media allows businesses to operate in novel ways, upending established markets and generating new business prospects. The sharing economy which has been made possible by digital technology is one illustration of this traditional industries like transportation and hospitality have been disrupted by businesses like Uber and Airbnb, who have developed new cost-effective business models.


On the above discussion of this topic, this is concluded thatIt is vital for organizations to comprehend the ramifications of digital technologies because the COVID-19 epidemic has expedited their uptake and use in businesses and management. Organizations need to employ digital exhaust, digital footprints, and artificial intelligence to succeed in the post-pandemic environment. While adopting these technologies successfully might bring both possibilities and problems, doing so can increase operational efficiency. Personalize consumer experience, and enable data-driven decisions that give businesses a competitive edge.


Almeida, F., Santos, J.D. and Monteiro, J.A., 2020. The challenges and opportunities in the digitalization of companies in a post-COVID-19 World. IEEE Engineering Management Review, 48(3), pp.97-103.

Aloisi, A. and De Stefano, V., 2022. Essential jobs, remote work and digital surveillance: Addressing the COVID19 pandemic panopticon. International Labour Review, 161(2), pp.289-314.

Comunello, F., Martire, F. and Sabetta, L., 2022. Brushing Society Against the Grain: Digital Footprints, Scraps, Non-Human Acts, Crumbs, and Other Traces. American Behavioral Scientist, p.00027642221144844.

Hanelt, A., Bohnsack, R., Marz, D. and AntunesMarante, C., 2021. A systematic review of the literature on digital transformation: Insights and implications for strategy and organizational change. Journal of Management Studies, 58(5), pp.1159-1197.

Khan, S. and Rabbani, M.R., 2020, November. Chatbot as Islamic finance expert (CaIFE) When finance meets artificial intelligence. In proceedings of the 2020 4th international symposium on computer science and intelligent control (pp. 1-5).

Liu, J., Tong, T.W. and Sinfield, J.V., 2021. Toward a resilient complex adaptive system view of business models. Long Range Planning, 54(3), p.102030.

Mishra, R., Singh, R.K. and Koles, B., 2021. Consumer decisionmaking in Omnichannel retailing: Literature review and future research agenda. International Journal of Consumer Studies, 45(2), pp.147-174.

Pal, D., Zhang, X. and Siyal, S., 2021. Prohibitive factors to the acceptance of Internet of Things (IoT) technology in society: A smart-home context using a resistive modelling approach. Technology in Society, 66, p.101683.

Sarker, I.H., 2021. Data science and analytics: an overview from data-driven smart computing, decision-making and applications perspective. SN Computer Science, 2(5), p.377.

Stoumpos, A.I., Kitsios, F. and Talias, M.A., 2023. Digital Transformation in Healthcare: Technology Acceptance and Its Applications. International Journal of Environmental Research and Public Health, 20(4), p.3407.

Teiuan, S.C. and Deaconu, S.C., 2021. Artificial intelligence and covid-19: an analysis in business and economics. Annals of'ConstantinBrancusi'University of Targu-Jiu. Economy Series, (5).


Related Samples

Question Bank

Looking for Your Assignment?

Search Assignment
Plagiarism free Assignment









9/1 Pacific Highway, North Sydney, NSW, 2060
1 Vista Montana, San Jose, CA, 95134