disruptive technologies
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2022 ◽  
Vol 12 (1) ◽  
pp. 1-40
Author(s):  
Michelle Karim ◽  
Christina Swart-Opperman ◽  
Geoff Bick

Learning outcomes The learning outcomes are follows: critically assess the impact of disruptive technologies, such as automation, on the organisation, its processes and employees; evaluate the structural changes required within the organisation to prepare for digital transformation; apply change models to the unique challenges associated with disruptive technologies; and recommend solutions for the organisation to proceed with the implementation of disruptive technologies, while keeping employees central to the change. Case overview/synopsis The Dimension Data automation case provides students and executives with a glimpse of the future that organisations and employees must prepare for. The case starts out with the protagonist and product owner of digital at Dimension Data, Andrew Harmse, reflecting on his three-year automation journey within the Automation Centre of Excellence. The world of automation is growing exponentially, and Andrew’s team will have to support the organisation as they scale up their automation journey and navigate the uncertain future of an increased, blended human-robot workforce. Individual employee reactions, positive and negative, will have to be balanced with the opportunities that ever-changing technology enables. The case focusses on the themes of digital transformation, digital disruption, change management and the very real factors to consider when faced with decision-making on automation as the world is constantly changing. The COVID-19 pandemic has forced organisations to relook processes and increase investment in technologies that enable digital client engagement and servicing, considering social distancing requirements. Automation at dimension data has been largely internally focussed, but there is a drive to increase delivery for clients. Andrew’s team will have to guide organisations through the journey and continuum of changes and uncertainties, such as large- scale unemployment and robot ethics. Complexity academic level The target audience for this teaching case are postgraduate and Master level students, specifically Master of Business Administration (MBA) students as well as Executive Education courses. Students who are responsible for making strategic decisions that impact the future of their organisations as well as students with an interest in the role of technology in the future will benefit from the case. Supplementary materials Teaching notes are available for educators only. Subject code CSS 6: Human Resource Management.


2022 ◽  
Vol 8 (2) ◽  
pp. 85-98
Author(s):  
Walter Timo De Vries

Changes in spatial planning and land management practices, regulations and operations have frequently relied on the uptake of innovations in geospatial technologies. This article reviews which ones the spatial planning and land management domains has effectively adopted and which new ones might potentially disrupt the domain in the near future of 2021 and beyond. Based on an extensive concept-centric trends synthesis and meta-review, the analysis demonstrates that whilst geospatial technologies are clearly gaining wider societal recognition and while private companies are indeed developing promising applications, its adoption in office work of public officials and public decision makers remains almost as limited as before. The potentially most disruptive technologies for the domain are however BIM, Block chain and Machine learning.


2022 ◽  
Vol 12 (1) ◽  
pp. 152-160
Author(s):  
Leonid Melnyk ◽  
Oleksandr Kubatko ◽  
Vladyslav Piven ◽  
Kyrylo Klymenko ◽  
Larysa Rybina

Digitalization, dematerialization of production and consumption, and structural shifts in the direction of service economy forming do promote to reduction of material use and sustainable development. The paper aims to investigate the role of digital, structural, economic, and social factors in sustainable development promotion in OECD countries. The paper uses the data on digital achievements, social and economic development of OECD member states from World Bank data sources for the period 2007–2018. The random-effects GLS regression model is used, and empirical regression models to estimate the influence of key factors related to digital transformation on GDP per capita and CO2 emissions per capita are constructed. The results of the regression analysis show that using the number of Internet users as an indicator for achievement in digitalization has a positive and statistically significant influence on GDP per capita due to lower transaction costs and higher share service economy. An increase in urbanization rates (as an indicator of capital concentrations and labor specialization) by one percent promotes a GDP per capita increase of 299 USD. Also, an increase in Gini coefficient by one percentage point correlates with decrease in GDP per capita on 196 USD and the reduction of CO2 per capita by 0.12 tones due to the structural shifts in aggregate demand. Still, improvements in digital transformations have no significant environmental effect in OECD members, while processes related to urbanization, income inequality, and share of industrial output are important drivers for CO2 per capita reduction. AcknowledgmentsThe paper contains the results of a study conducted within the framework of research projects: “Sustainable development and resource security: from disruptive technologies to digital transformation of Ukrainian economy” (No. 0121U100470); “Fundamental bases of the phase transition to an additive economy: from disruptive technologies to institutional sociologization of decisions” (No. 0121U109557).


2022 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Denis Trček

Digital transformation is, among others, notably driven by servitization, and consequently, IT artifacts called Application Programming Interfaces (APIs), together with disruptive technologies and innovations. In order to set up proper policies, the understanding of the above factors is essential, including their influences on value adding chains. This paper therefore provides an analysis of APIs developments together with their impacts on digital transformation. As they can affect organizations and even national economies at strategic level, appropriate management from a systemic perspective is justified, including e-Government initiatives. Further, APIs cannot be treated without their relations to disruptive technologies, innovations and value chains. Therefore, the advancements of theoretical understanding of evolution of value chains, and practical directions for e-government initiatives are given in this paper. In addition, an archetype model is developed that provides a basis for further research efforts in the area.   Received: 7 October 2021 / Accepted: 29 November 2021 / Published: 3 January 2022


2022 ◽  
pp. 92-114
Author(s):  
Shailja Dixit

Disruptive technologies such as IoT, big data analytics, blockchain, and AI have changed the ways businesses operate, with AI holding immense marketing transformation potential. AI is influencing marketing strategies, business models, sales processes, customer service options, and customer behaviors. AI-CRM's improving ability to predict customer lifetime value will generate an inevitable rise in implementing adapted treatment of customers, leading to greater customer prioritization and service discrimination in markets. CSPs are working through the challenging process of digital transformation, driven by the need to compete with fast-moving OTT and consumer tech players. CSPs need to move quickly and can advance digital transformation with solutions that leverage AI which can drive value across the business from network optimization and data analytics through to customer care and marketing engagement. The chapter tries to identify how AI is impacting the CRM in the telecom industry and leveraging the benefits of this technology for better customer management and growth.


2022 ◽  
pp. 213-229
Author(s):  
Sana Moid

The COVID-19 pandemic has shaken the roots of every economy and completely transformed the way every industry functions including the education sector. The education sector completely adopted the remote teaching concept thereby connecting educators and students through technology. The present study aims at understanding that how Education 4.0 has helped in creating an intelligent learning space aligned with disruptive technologies for developing and enhancing education with learners at the center and further how this has facilitated remote teaching during the COVID-19 pandemic. For the purpose of study, secondary sources of data including research papers and news articles based on the similar themes were referred. Education 4.0 has completely transformed the way the education sector functions by putting the learner at the center and making the entire process student-centric where the learner will decide what they want to study rather than putting a predefined syllabus in front of them. The intelligent learning space is created through the application of emerging technologies.


2022 ◽  
Vol 174 ◽  
pp. 121232
Author(s):  
Victor Chang ◽  
Gary Wills ◽  
Patricia Baudier

2022 ◽  
pp. 243-254
Author(s):  
Munyaradzi Zhou ◽  
Cyncia Matsika ◽  
Tinashe Gwendolyn Zhou ◽  
Wilfreda I. Chawarura

COVID-19 and future pandemics drastically change the way of life globally. Research has predominantly focused on the use and integration of disruptive technologies in industry and commerce. Little of the recent studies focused on the implementation of artificial intelligence and blockchain technologies in educational applications. The chapter focuses on how these can be implemented, from development, deployment, use, and maintenance of applications. A computer program's lifespan is usually spent during its use. The qualitative case study was administered using a digital learning platform that provides interactive learning for primary and secondary learners. The disruptive technologies inform new teaching methodologies and the development of student-centered algorithms for learning. Further research includes privacy issues in the implementation of disruptive technologies and data-sharing governance issues and evaluating the effectiveness of artificial intelligence and blockchain-based learning platforms.


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