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1.
IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2022 ; 664 IFIP:486-493, 2022.
Article in English | Scopus | ID: covidwho-2059724

ABSTRACT

Digital transformation is a process encompassing all organizations, requiring a proactive attitude and willingness to change. The Covid-19 pandemic highlighted the relevance of digitization through an increased awareness and implementation of digital tools for working life. The next wave of successful innovation in industry demands high-pitched adoption of technologies for production and workplace learning systems. Organizations are trying to understand which technologies to invest in, based on usability measures, cost effectiveness, and sustainability. It can be hard to predict which technology is best suited for specific tasks. This implies a growing risk regarding investments in technology. This paper describes the spontaneous use of technology for augmented reality (AR, Microsoft HoloLens 2) in a Norwegian manufacturing company during Covid-19. The case illustrates how AR technology can be used in assembling, installation and acceptance testing of machinery for selective soldering in the production of circuit boards. Data were collected through case study research and a qualitative research design, through observation and interviews with the participants. The results show that Microsoft HoloLens 2 is easy to adopt and could contribute to immediate and real value creation in industrial production companies. We believe that the spontaneous usage of AR technology in such extraordinary circumstances as a pandemic could motivate and guide other businesses facing important decisions related to technology implementation. The original value of this article is a contribution to the discussion on the Technology Acceptance Model, which is chosen as a theoretical framework for the paper. © 2022, IFIP International Federation for Information Processing.

2.
7th IEEE International conference for Convergence in Technology, I2CT 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1992592

ABSTRACT

In-class teaching not only concentrates on lecture content delivery but also on maintaining strong mutuality between lecturer-students and student-student. Online lectures are gaining popularity due to the Covid-19 pandemic. However, the learning-teaching process has become ineffective because existing video conferencing solutions are not intended for academic purposes. This research was conducted to identify the pain points of online education and develop an enhanced software solution. A user survey confirmed that an isolated environment tends to diminish attentiveness during online lectures. Also, it is difficult for teachers to observe the attentiveness of all the students. As a solution, student attentiveness was measured using their facial expressions and collected data shown to lecturers through a virtual student behavioural environment. The physical separation causes students to feel isolated during lectures, which can negatively affect their academic development and social and psychological development. The developed application also provides a virtual group study environment as a feature. According to the results gathered in the user acceptance testing phase, it was found that the attention detection feature helps students keep their attention at a significant level. Further, 9 out of 10 teachers who participated in the testing acknowledged that the simulated student behavioural view could provide a more immersive experience. 71% of students preferred the new collaborative virtual environment, and students further elaborated that the virtual environment was more likely the physical group studies. 72% of students mentioned that the collaborative group study tool helped eliminate isolation during group studies. © 2022 IEEE.

3.
Built Environment Project and Asset Management ; 12(5):754-774, 2022.
Article in English | ProQuest Central | ID: covidwho-1985238

ABSTRACT

Purpose>Factory acceptance testing (FAT) in the construction industry has been severely hampered due to restrictions in cross-border travel resulting from the COVID-19 pandemic. Consequently, virtual FAT (vFAT) became a popular substitute for physical FAT. However, the credibility of vFAT is being questioned because it was adopted without much scrutiny. Hence, this study is aimed at investigating vFATs and re-engineering the FAT process to suit an effective vFAT environment.Design/methodology/approach>A comprehensive literature search on FAT procedures was followed by two stages of expert interviews with eight leading subject experts and a case study. The findings were analysed using code-based content analysis on NVivo software.Findings>Strengths of vFATs include “reduction in cost and time consumed”, “flexibility for more participants” and “faster orders”. Most emphasized weaknesses include “lack of reliability” and “lack of technology transfer”. vFAT has mostly increased test reliability by “improving accessibility” and has decreased reliability by “restricting physical touch and feel observation of the equipment”. A four-step vFAT process was developed with a noteworthy additional step called “Pre-FAT Meeting”.Research limitations/implications>The scope of this study is limited to the Sri Lankan construction industry. Expansion of the geographical area of focus is recommended for future studies.Originality/value>The findings of this study unveil a vFAT process, which is timely and beneficial for construction practitioners to optimize and enhance the effectiveness of vFATs which are currently conducted in a disarranged manner.

4.
International Journal of Information Management ; 64:1, 2022.
Article in English | ProQuest Central | ID: covidwho-1959608

ABSTRACT

We propose a conceptual model of acceptance of contact tracing apps based on the privacy calculus perspective. Moving beyond the duality of personal benefits and privacy risks, we theorize that users hold social considerations (i.e., social benefits and risks) that underlie their acceptance decisions. To test our propositions, we chose the context of COVID-19 contact tracing apps and conducted a qualitative pre-study and longitudinal quantitative main study with 589 participants from Germany and Switzerland. Our findings confirm the prominence of individual privacy calculus in explaining intention to use and actual behavior. While privacy risks are a significant determinant of intention to use, social risks (operationalized as fear of mass surveillance) have a notably stronger impact. Our mediation analysis suggests that social risks represent the underlying mechanism behind the observed negative link between individual privacy risks and contact tracing apps' acceptance. Furthermore, we find a substantial intention–behavior gap.

5.
37th ACM/SIGAPP Symposium on Applied Computing, SAC 2022 ; : 1327-1336, 2022.
Article in English | Scopus | ID: covidwho-1874701

ABSTRACT

Soft requirements (such as human values, motivations, and personal attitudes) can strongly influence technology acceptance. As such, we need to understand, model and predict decisions made by end users regarding the adoption and utilization of software products, where soft requirements need to be taken into account. Therefore, we address this need by using a novel Bayesian network approach that allows the prediction of end users' decisions and ranks soft requirements' importance when making these decisions. The approach offers insights that help requirements engineers better understand which soft requirements are essential for particular software to be accepted by its target users. We have implemented a Bayesian network to model hidden states and their relationships to the dynamics of technology acceptance. The model has been applied to the healthcare domain using the NHS COVID-19 Test and Trace app (COVID-19 app). Our findings show that soft requirements such as Responsibility and Trust (e.g. Trust in the supplier/brand) are relevant for the COVID-19 app acceptance. However, the importance of soft requirements is also contextual and time-dependent. For example, Fear of infection was an essential soft requirement, but its relevance decreased over time. The results are reported as part of a two stage-validation of the model. © 2022 ACM.

6.
2021 Abu Dhabi International Petroleum Exhibition and Conference, ADIP 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1789284

ABSTRACT

Many of the well-established practices and procedures those were followed in the execution of Oil & Gas Industry Projects were seeing a shift towards digital transformation in recent years, which got accelerated due to the Covid-19 pandemic. Digital transformation is the adoption of digital technologies whereby the existing business processes are modified or new ones are created. This process of redefining the conventional procedures, culture and customer experience to meet the changing requirements benefit the overall business function. Redefining the process of business in the digital age is digital transformation. Digital transformation in Oil & Gas Industry is embracing of technology to reshape how oil and gas companies manage and operate their assets. The digitally-enabled and data-centric approach leads to improved productivity, higher efficiency and increased cost savings. One of the Process Transformation example in Oil & Gas sector is to conduct the Factory Inspection and Acceptance Tests remotely utilizing various digital tools available in this digital age instead of the conventional way of physical participation in the testing. Many industries were already exploring the possibilities of non-conventional work practices such as Work from Home (remotely, away from office), conducting virtual meetings with remotely located participants. These practices were still not accepted in all the industries prior to 2020. However the outbreak of Covid-19 pandemic worldwide created a need to accept these non-conventional practices of remote or virtual work. Post Covid (2020), these are widely accepted in most of the industries including Oil & Gas sector. The concept of Virtual Remote Factory Acceptance Test (FAT) is explored to overcome the unforeseen situation arose due to worldwide Covid-19 outbreak. Travel restrictions were imposed worldwide to curb the covid-19 spread, which made a halt to the normal work practices followed till then. Virtual Remote FAT is a successful alternative to the conventional way of conducting the FAT and was utilized during Covid-19 outbreak. Virtual remote FAT is successfully completed in some of the recently executed projects and this can be pursued even after the Covid crisis. © Copyright 2021, Society of Petroleum Engineers

7.
4th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2021 ; : 550-555, 2021.
Article in English | Scopus | ID: covidwho-1769645

ABSTRACT

There has been a steep rise of contactless payment during COVID-19. The rapid improvements of miniaturized sensors and biometric recognition systems for face identification, fingerprint, iris, and voice are conducive and fit during this rise of COVID-19. Thus, non-contact interactions are the most effective way to fight against the spread of the virus and any other diseases. One of the most used is iris scanners and speech recognition. The study promotes contactless payments to address the accompanying issues in cash aid distribution particularly in the DSWD 4Ps, where it has a two-Tier biometric security system which is iris recognition and speech recognition. This can provide the same type of service and securities as a normal ATM while removing the worry of getting different kinds of viruses and diseases. Testing the iris recognition system, a False acceptance ratio of 13% and 3% of False Rejection rates were achieved. While for the testing of speech recognition (security questions), a False Acceptance Ratio of 0% and False Rejection Ratio of 12.12% were achieved. Lastly, testing of speech recognition (navigation)a False Acceptance Ratio of 0% and False Rejection Ratio of 3.62% were achieved. Giving the system an 84% accuracy for the iris recognition, 87.88% for the security questions, and 96.36% for the navigation. © 2021 IEEE.

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