Adoption Of Emerging Technologies Research Articles

Assessing Virtual Reality in Oil Painting Education: A Perspective from the Technology Acceptance Model

This research assessed the integration of virtual reality (VR) into oil painting education through the lens of the technology acceptance model (TAM). The study, limited to Guangdong Province, China, drew responses largely from educators and learners and modularly evaluated perceived educational value (PEV), perceived technological accessibility (PTA), intention to adopt VR (IAVR), and VR utilisation in education (VRUE). Based on a crosssectional survey of 373 respondents, this study deployed structural equation modelling (SEM) to test five hypotheses. Both PEV and PTA significantly influence IAVR, which subsequently affects VRUE. PTA had a direct interface with VRUE, whereas PEV did not. This suggests that while the educational merits accrued through VR have decreased, user-friendly VR solutions is the more immediate determinant of the actualisation of VR in education. This research enriches the extant literature by extending the TAM to an arts educational environment and underscores the implications for the adoption of emergent technologies for the augmentation of pedagogical practises. This study also provides practical implications for stakeholders in educational technology, as it argues that the key to widespread acceptance of VR in educational settings lies in the availability of user-friendly, comprehensive, and accessible VR solutions.

The impact and adoption of emerging technologies on accounting: perceptions of Canadian companies

PurposeThis study aims to focus on the five most relevant and discursive emerging technologies in accounting (cloud computing, big data and data analytics, blockchain, artificial intelligence (AI) and robotics process automation [RPA]). It investigates the adoption and use of these technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey.Design/methodology/approachThe study investigates the adoption and use of emerging technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey. This study considers the said nature and characteristics of emerging technologies and proposes a model using the factors that have been found to be significant and most commonly investigated by existing prior technology-organization-environment (TOE)-related technology adoption studies. This survey applies the TOE framework and examines the influence of significant and most commonly known factors on Canadian firms’ intention to adopt the said emerging technologies.FindingsStudy results indicate that Canadian accounting professionals’ self-assessed knowledge (about these emerging technologies) is more theoretical than operational. Cloud computing is highly used by Canadian firms, while the use of other technologies, particularly blockchain and RPA, is reportedly low. However, firms’ intention about the future adoption of these technologies seems positive. Study results reveal that only the relative advantage and top management commitment are found to be significant considerations influencing the adoption intention.Research limitations/implicationsStudy findings confirm some results presented in earlier studies but provide additional insights from a new perspective, that of accounting professionals in Canada. The first limitation relates to the respondents. Although accounting professionals provided valuable insights, their responses are personal views and do not necessarily represent the views of other professionals within the same firm or the official position of their accounting departments or firms. Therefore, the exclusion of diverse viewpoints from the same firm might have negatively impacted the results of this study. Second, this study sample is limited to Canada-based firms, which means that the study reflects only the situation in that country. Third, considering the research method and the limit on the number of questions the authors could ask, respondents were only asked to rate the impact of these five technologies on the accounting field and to clarify which technologies are used.Practical implicationsThis study’s findings confirm that the organizational intention to adopt new technology is not primarily based on the characteristics of the technology. In the case of emerging technology adoption, the decision also depends upon other factors related to the internal organization. Furthermore, although this study found no support for the effect of environmental factors, it fills a gap in the literature by including the factor of vendor support, which has received little attention in prior information technology (IT)/ information system (IS) adoption research. Moreover, in contrast to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.Social implicationsThe study findings may serve as a guide for researchers, practitioners, firms and other stakeholders, particularly technology providers, interested in learning about emerging technologies’ adoption and use in Canada and/or in a relevant context. Contrary to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.Originality/valueThe study provides insights into the said technologies’ actual adoption and improves the awareness of firms and stakeholders to the effect of some constructs that influence the adoption of these emerging technologies in accounting.

Navigating Digital Frontiers in Music Education: The MUSENSE Project's Contribution to E-Learning

The integration of digital technologies into music education, particularly through the MUSENSE project, marks a pivotal evolution in teaching and learning practices within this creative domain. This research paper explores the project's innovative approach to leveraging state-of-the-art technologies that include AI (Artificial Intelligence), IOT (Internet of Things), robotic and eXtended (XR)/virtual (VR)/augmented (AR) reality and other emerging technologies to enhance music education and performance. With the advent of the COVID-19 pandemic, traditional music education faced significant challenges, catalyzing the need for alternative, technologically driven pedagogical strategies. MUSENSE addresses this gap by facilitating the digital transformation of music education, aiming to enrich learning experiences and broaden access to music performance education. This is implemented through a mixed-methods research approach that utilises an open repository designed to collect, decompose, present the functions of the basic functional components and elements of appropriate case studies. In addition, through the collection of stakeholder interviews and expert contact information, the project reports on the current state of emerging technology adoption in music education, assesses the educational implications of these technologies, and explores their potential to foster innovative teaching and learning practices. Initial findings suggest a positive impact on music education through immersive learning experiences provided by state-of-the-art technologies, alongside an increasing receptivity among educators and students towards integrating digital tools. However, challenges such as the digital divide and the need for curriculum adaptation emerge as critical considerations. This paper contributes to the discourse on digital innovation in music education by highlighting the opportunities and obstacles presented by integrating digital technologies, offering insights for educators, policymakers, and technology developers in navigating the future of music education in the digital age.

Examining the Impact of Adoption of Emerging Technology and Supply Chain Resilience on Firm Performance: Moderating Role of Absorptive Capacity and Leadership Support

The purpose of this article is to examine the impact of firms’ intellectual capability on adoption of emerging technology (ET), and the influence of supply chain resilience on firm performance (FP). The article also investigates the moderating role of firms’ absorptive capacity on adoption of ET and the moderating impact of leadership support (LS) on the relationship between adoption of ET and FP. With the support from literature review and related theories, a model has been developed conceptually. Then, the model has been validated using the data collected from various firms. The article finds that firms’ intellectual capability, agility, and integration significantly impact the adoption of ET, which in turn positively influences supply chain resilience of the firm along with FP. The article also highlights that there is a positive and significant moderating impact of firms’ absorptive capability on the relationship between firm intellectual capital and adoption of ET. Also, the article shows the moderating impact of LS on the relationship between adoption of ET and FP.

Factors Affecting SMEs Emerging Technologies Adoption in Developing Countries: A Literature Review

Small and Medium Enterprises (SMEs) constitute the most dynamic firms in emerging economies, by driving economic growth and job creation in developing economies. Therefore, it is important to identify factors that hinder SMEs’ growth. The most common factors faced by SMEs are the lack of technical and managerial skills. Furthermore, it is stated that the rapidly changing environment makes innovation more challenging. Thus, SMEs need to remain competitive and drive economic growth. The study objective was therefore to explore factors affecting SMEs’ information technology (IT) adoption in developing countries. The systematic literature review (SLR) methodology was used for the study. The source data was published articles and journals. The Technological-Organizational-Environmental (TOE) framework was used as the lens to explore the factors that affect emerging technology adoption in developing countries. The study results suggest that the main factors affecting SMEs’ emerging technology adoption are lack of finance and digital literacy. The study contributes to the body of knowledge on factors affecting SMEs’ adoption of ICT in developing countries. Small and Medium Enterprises (SMEs) constitute the most dynamic firms in emerging economies, by driving economic growth and job creation in developing economies. Therefore, it is important to identify factors that hinder SMEs’ growth. The most common factors faced by SMEs are the lack of technical and managerial skills. Furthermore, it is stated that the rapidly changing environment makes innovation more challenging. Thus, SMEs need to remain competitive and drive economic growth. The study objective was therefore to explore factors affecting SMEs’ information technology (IT) adoption in developing countries. The systematic literature review (SLR) methodology was used for the study. The source data was published articles and journals. The Technological-Organizational-Environmental (TOE) framework was used as the lens to explore the factors that affect emerging technology adoption in developing countries. The study results suggest that the main factors affecting SMEs’ emerging technology adoption are lack of finance and digital literacy. The study contributes to the body of knowledge on factors affecting SMEs’ adoption of ICT in developing countries.

AI and emerging technology adoption: a research agenda for operations management

Artificial intelligence (AI) is becoming a critical engine that powers a range of technology solutions. It is rapidly playing a vital role in supply chain and operations management. In this paper, we present a research agenda of how researchers and practitioners alike can study the potential adoption of AI-powered tools for benefits in the supply chain. We draw on the unified theory of acceptance and use of technology and suggest directions for research that leverage a mixed-methods research approach. Because these technologies are in a nascent stage and evolving rapidly, a mixed-methods approach will allow for a careful examination of potential features and how their adoption can be fostered, with specific benefits in mind. We present three-specific research directions rooted in the developmental, completeness, and expansion purposes of mixed-methods research.

Information Literacy, Data Literacy, Privacy Literacy, and ChatGPT: Technology Literacies Align with Perspectives on Emerging Technology Adoption within Communities

Information Literacy, Data Literacy, Privacy Literacy, and ChatGPT: Technology Literacies Align with Perspectives on Emerging Technology Adoption within Communities

Estimating the duration of competitive advantage from emerging technology adoption

This paper proposes a method for estimating the expected duration of competitive advantage from emerging technology adoption for the average adopting firm. The proposed method relies on publicly available data (e.g., web search interest, news articles, book titles, and firm disclosures) and integrates elements from diffusion of innovation theory, hype cycles, and resource-based view of competitive advantage. We validate this method by applying it to two mature technologies, namely ERP and cloud computing, for which we come up with estimates consistent with findings from prior studies. Leveraging our method, researchers and professionals can use readily available data to make their own estimations. Such estimates can inform researchers in answering research questions related to duration of competitive advantage from technology adoption. They can inform professionals in making better business decisions such as forecasting the net present value of an investment in an emerging technology.

Technology Adoption and Early Network Infrastructure Provision in the Market for Electric Vehicles

We document non-linear stock effects in the relationship linking emerging technology adoption and network infrastructure increments. We exploit 2010–2017 data covering nascent to mature electric vehicle (EV) markets across 422 Norwegian municipalities together with two complementary identification strategies: control function regressions of EV sales on flexible polynomials in the stock of charging stations and charging points, and synthetic control methods to quantify the impact of initial infrastructure provision in municipalities that previously had none. Our results are consistent with indirect network effects and the behavioral bias called “range anxiety,” and support policies targeting early infrastructure provision to incentivize EV adoption.

The interplay of emerging technologies in pharmaceutical supply chain performance: An empirical investigation for the rise of Pharma 4.0

The impact and the relevance of the emerging technologies on the supply chains have attracted researchers and practitioners alike worldwide. Based on the resource-based view and organizational information processing theory, this study attempts to investigate how emerging technologies influence supply chain performance, particularly pharmaceutical supply chain in regards to the rise of Pharma 4.0. The pharmaceutical supply chain processes are considered as the mediators and the emerging technology adoption barriers are proposed as the moderators. The study is evaluated using a survey of pharmaceutical companies in India. The findings indicate that manufacturing, distribution and consumption processes in the supply chain mediate the effects of emerging technologies on supply chain performance; however, mediating effects are weakened due to the presence of intricate barriers. This study thereby empirically investigates the interplay between emerging technologies in pharmaceutical supply chain performance and provides managerial insights with a proposed research framework on how to incorporate and encourage Pharma 4.0 for achieving sustainability in the supply chains.

Determinants of emerging technologies adoption in the South African financial sector

Purpose: The fourth industrial revolution (4IR) enables firms to leverage various emerging technologies to reduce operating costs, improve business efficiencies and gain competitive advantage. This article uncovers the determinants influencing emerging technology adoption, particularly artificial intelligence (AI), cloud computing and distributed ledger technologies (DLT), in South African (SA) financial services firms.Design/methodology/approach: Seventeen technology experts from the SA banking, insurance, financial technology and financial regulation and compliance sectors were interviewed. A semi-structured interview was used to conduct one-on-one interviews, followed by a focus group interview. Qualitative data were analysed using a thematic network analysis.Findings/results: The results revealed that the determinants – adopter traits, technology usability, industry characteristics, organisational leadership and organisational characteristics – were influential towards technology adoption. It is suggested that the new model could be strengthened further by incorporating a new construct, leadership diversity, which had not been previously proposed in the literature.Practical implications: By understanding the influential adoption determinants, leaders can take bold, calculated risks in adopting AI, cloud computing and DLT. However, the importance, prior to adopting these technologies, of clearly understanding the need for them, and their business benefits is also emphasised.Originality/value: Research on the adoption of AI, cloud computing and DLT in the SA financial sector is limited. This article leverages the models of the diffusion of innovations (DOI), the technology–organisation–environment (TOE) and the technology readiness index (TRI) to propose a new model that illustrates technology adoption in the SA financial sector at individual and firm levels.

Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing

The Industry 4.0 (I4.0) revolution has led to rapid digital transformation, automation of manufacturing processes and efficient decision-making in business operations. Despite the potential benefits of I4.0 technologies in operations management reported in the extant literature, there has been a paucity of empirical research examining the intention to adopt I4.0 technologies for managing risks. Risk management identifies, assesses, and introduces responses for risks to avert crises. This study combines institutional theory, the resource-based view and the technology acceptance model to develop a novel behavioural model examining the adoption of big data, artificial intelligence, cloud computing, and blockchain for risk management from the operations manager's perspective, which has never been examined in the literature. The model was tested for each I4.0 technology using data collected from 117 operations managers in the UK manufacturing industry which were analysed using structural equation modelling. We contribute to the theory on I4.0 in digital manufacturing by showing the impact of digital transformation maturity, market pressure, regulations, and resilience on the perceived usefulness and adoption of these technologies for managing risks in business operations. Based on the findings, we discuss implications for operations managers effectively and efficiently to adopt I4.0 technologies aiming to boost operational productivity.

Smart Water Management Using Intelligent Digital Twins

Providing and distributing fresh water to large communities is a major global concern. In addition to its scarcity as well as to its wastage, this vital resource is being affected by challenging environmental conditions. New approaches are, therefore, urgently needed for an optimized, fair, and efficient use of fresh water. The adoption of emergent technologies is giving high hopes to reach this objective. Among these technologies, digital twin is attracting increasing attention from the academic and industrial committees. This attention is particularly motivated by its expected values to any sector, including process optimization, cost reduction, and time to market shortening. In the specific field of water management, several solutions are being proposed, especially to detect leak detection and test water assets under a variety of working constraints. These solutions are still lacking intelligence and autonomy throughout the loop of data acquisition and processing as well as asset control and service generation and delivery. To this end, we are proposing in this paper a new framework based on multi-agent systems and DT paradigm to close gaps within this loop. Our multi-agent system is responsible of running data analytics mechanisms in order to assess water consumption and generate relevant feedbacks to users using, among others, a rewarding system to select the appropriate pricing policies. It is also responsible of simulating asset operations under specific working constraints for the purpose of failure and/or defect detection.

Identifying the Perception Differences of Emerging Construction-Related Technologies between Industry and Academia to Enable High Levels of Collaboration

Emerging technologies play an essential role in improving overall productivity in the construction industry. However, this field has historically been criticized for the slow adoption of these innovative tools. To promote emerging technology adoption, exchanging knowledge and practices through academia and industry collaboration is essential. This paper analyzes the perception differences between academics and construction industry practitioners with regard to 17 emerging technologies through survey data and identifies potential technologies for high levels of collaboration from an academic perspective. The survey was designed to obtain responses about technological use, interest, maturity, implementations, applications, benefits, and barriers. Three technologies, three-dimensional (3D) printing; artificial intelligence (AI), neural networks (NNs), and deep learning (DL); and smart materials, were identified as having the highest potential for enabling collaboration. The findings from this study will allow academic researchers to strategically develop research directions that align with the needs reported by industry practitioners to sustain research funding and foster the adoption of innovative technologies in the construction fields.

Emerging technologies in Indian mining industry: an exploratory empirical investigation regarding the adoption challenges

PurposeEmerging technologies have been transforming most industries. A wide range of emerging technologies such as blockchain, internet of things (IoT), artificial intelligence (AI), machine learning (ML), robotics and many others have changed the way in which firm value chain activities or processes were executed traditionally. The mining industry has also witnessed the introduction of these emerging technologies in various processes from the exploration stage to the final processing of ores. The purpose of this paper is to understand the pace of adoption of emerging technologies in the Indian mining industry and identify the challenges that managers confront while adopting emerging technologies.Design/methodology/approachThe authors undertook qualitative research. Data collection was done in two stages. Secondary research was conducted to arrive at a repository of use cases of the adoption of emerging technologies in the global mining industry. Primary data collection was also done. The insights on emerging technology adoption and challenges faced in the Indian mining industry were captured by in-depth interviewing of subject matter experts. The authors interviewed 21 mining subject matter experts with a semi-structured open-ended questionnaire. The responses were content analyzed by thematic content analysis. Technological-organizational-environmental (TOE) and diffusion of innovation (DOI) frameworks were applied to segregate different factors affecting the adoption of emerging technologies in the Indian mining industry.FindingsEmerging technologies such as blockchain, IoT, AI, ML, robotics has been applied across various mining engineering value chain activities such as in drilling, blasting, excavation and ore hauling. However, emerging technologies adoption was hindered because of a lack of managerial awareness, cultural inertia, substantive upfront investments and the nature of intangible benefits in the short run.Research limitations/implicationsThe research applied technology adoption frameworks in the mining industry. The authors used TOE and DOI frameworks to understand the challenges faced by Indian mining firms. The research findings, thus added to the conversation of TOE and DOI frameworks in the context of the Indian mining industry.Practical implicationsThe research finding would help mining firm managers to anticipate the challenges with respect to technology adoption. This would allow mining executives to create a proper technology adoption plan and intervene proactively. The research would also provide information about the steps taken by competing firms with respect to emerging technologies adoption. The research would help managers to decide technology implementation steps in drilling, blasting, excavation and ore hauling to be undertaken for successful adoption of emerging technologies. Technology firms could gain insights into the issues faced by mining firms in adopting emerging technologies. This research would help managers to influence organizational technology policy and endorse the addition of pro-technology policies in mining activities. Policymakers involved in the mining sector could also incorporate industry-level policy decisions so as to facilitate the adoption of emerging technologies among mining firms and remove the barriers to the adoption of emerging technologies. This would create an opportunity for technology providers to redesign product offerings, which could be a good fit for Indian mining firms.Originality/valueIndian mining industry contributed significantly to the Indian economy. Despite this, limited focus has been put regarding the adoption of emerging technologies in the mining industry. Mining managers did not have any framework to understand the challenges faced in the adoption of technologies across the mining value chain that is in drilling, blasting, excavation and ore hauling. This study focused on identifying those challenges through the use of technology adoption frameworks. This research was one of the first studies to gain insights on emerging technologies adoption in the context of the mining industry through the theoretical lens of TOE and DOI frameworks.

Alexa, Are You Listening?

Smart voice assistants have expanded from personal use in the home to applications in public services and educational spaces. The library and information science (LIS) trade literature suggests that libraries are part of this trend, however there are few empirical studies that explore how libraries are implementing smart voice assistants in their services, and how these libraries are mitigating the potential patron data privacy issues posed by these technologies. This study fills this gap by reporting on the results of a national survey that documents how libraries are integrating voice assistant technologies (e.g., Amazon Echo, Google Home) into their services, programming, and checkout programs. The survey also surfaces some of the key privacy concerns of library workers in regard to implementing voice assistants in library services. We find that although voice assistant use might not be mainstreamed in library services in high numbers (yet), libraries are clearly experimenting with (and having internal conversations with their staff about) using these technologies. The responses to our survey indicate that library workers have many savvy privacy concerns about the use of voice assistants in library services that are critical to address in advance of library institutions riding the wave of emerging technology adoption. This research has important implications for developing library practices, policies, and education opportunities that place patron privacy as a central part of digital literacy in an information landscape characterized by ubiquitous smart surveillant technologies.

Emerging Technologies To Detect Fraud in Audit Testing: A Perception of Malaysian Big Four Auditors

Fraud surveys performed over the past decade remained at worrying levels in Malaysia. The Malaysian 1MDB scandal has attracted worldwide attention which severely damaged the local auditing profession, worsening the credibility crisis in the sector. The rise of emerging technologies is seen to bridge the expectation gap in strengthening stakeholder confidence in auditors by easing fraud detection. Unfortunately, a past study in Malaysia on task-technology fit between auditor’s knowledge and perceived importance on technology revealed a gap. A report by the Malaysian Institute of Accountants in 2019 highlighted that the lagging factor of emerging technology adoption in Malaysia is due to auditors’ non-realization of its usefulness in fraud detection. Furthermore, to render emerging technology as a useful medium for data extraction and analysis higher levels of scepticism is required. Besides, focus is placed on data quality as the accuracy of testing is heavily reliant on the input. Hence, this study intends to find whether there is a relationship between the perception of Malaysian Big Four external auditors and fraud detection in the audit testing phase. An online questionnaire based on a 5-point Likert scale was distributed and received responses from 108 external auditors where data was coded and input into the SPSS for further analysis. The results show that Malaysian Big Four external auditor’s perception of emerging technology affects the use for fraud detection in audit testing. As this study could not be generalized, further research should consider looking from the time constraints viewpoint or to study auditors from a similar firm for a greater understanding of their perception since firms have different degree of emerging technology adoption.

A fuzzy Delphi-AHP-TOPSIS framework to identify barriers in big data analytics adoption: case of maritime organizations

ABSTRACTBig data analytics has prospered in recent years and has triggered revolutionary changes in various industries. However, its adoption in maritime organizations is relatively lagged and there is no study addressing this phenomenon so far. This paper develops a fuzzy Delphi-AHP-TOPSIS framework to identify barriers in emerging technology adoption. A case study employs this framework to investigate the hurdles for big data analytics to be adopted in the maritime industry. The case study shows that the framework is useful in identifying and ranking barriers. The results unveil the most serious managerial, cultural, and technical barriers that impede the adoption of big data analytics in maritime organizations.

Model of Emerging Technology Adoption (META): Virtual Reality as a Case Study

Although technology acceptance and adoption have been intensively investigated using well-established theories called the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT), this paper claims that Emerging Technology (ET) has particular characteristics that differentiate it from the adoption of traditional technology that has been used for a long time. Therefore, it argues that TAM and IDT are not sufficient to investigate the adoption of ET. Investigating the adoption of ET requires additional, unique, non-traditional factors (constructs). Therefore, this paper aims first to conceptually develop a model of ETs adoption (META). To achieve this objective, TAM and IDT will be reviewed. Then, this paper will use the characteristics of ET as the basis for developing the factors that influence the adoption of ET. Secondly, to validate the model, a case study of an ET (i.e. Virtual Reality) will be analysed in-depth to reveal the factors that influence on its adoption by applying META. A discussion of META applications and implications for future research are also provided.

Interfacing fast-fashion design industries with Semantic Web technologies: The case of Imperial Fashion

With the advent of the fourth industrial revolution, several enterprises worldwide have started to evolve their production processes with new automation and data exchange policies by means of the adoption of emergent technologies, i.e. knowledge graphs, sensor networks, big data, and cloud computing. While several domains have been already involved in this revolution, other parties, such as the fast-fashion industries, have started to move the first steps in that direction since few months. In this article we describe the first outcomes of a project, i.e. Refactoring Imperial Selling Data (RISED), which aims at using Semantic Web technologies so as to simplify the management and the enrichment of a huge set of data that are continuously collected by Imperial Fashion, one of the most important fast-fashion companies in Italy. In particular, we introduce the process adopted for the development of a unifying model (i.e. an OWL 2 DL ontology) for the description of all the Imperial Fashion data and we propose some mechanisms for converting the original data stored in existing databases according to the new ontology. Finally, we introduce some prototypical visual tools that use the converted data for addressing some of the questions that have been raised by Imperial Fashion employees during several informal meetings we had about the project RISED.