Search results

Energy consumption in existing office buildings has been growing in parallel with the rise in occupant energy demand. As a result, many building owners have given smart retrofits (SRs) a higher priority. However, the utilisation of suitable SRs from a range of SRs has become a challenging task. The purpose of this paper is to develop a decision-making model to select the most suitable SRs for conventional office buildings and form a set of benchmarks for assessing the performance of SRs.

A qualitative approach with six case studies was used. Content analysis was carried out using NVivo to explore the factors considered for the selection of SR techniques. A decision-making model for selecting SRs in Sri Lankan office buildings was proposed. SR performance benchmarks were developed by referring to established standards and studies done in tropical office buildings.

Out of 18 identified SRs from literature, fan cycling, ventilation control and LED luminaires have been recognised as commonly used SRs in Sri Lankan office buildings. Analysis showed that HVAC retrofits saved more energy, while lighting retrofits could be easily implemented in existing buildings. The proposed decision-making model can explore further improvements to enhance the performance of SRs.

The selection of SRs is a comprehensive decision-making process. Metrics were established to benchmark the performance of SRs. The proposed model offers a tool for building owners and facility managers to optimise facility operations.

Metro stations have become a crucial aspect of urban rail transportation, integrating facilities, equipment and pedestrians. Impractical physical layout designs and pedestrian psychology impact the effectiveness of an evacuation during a metro fire. Prior research on emergency evacuation has overlooked the complexity of metro stations and failed to adequately consider the physical heterogeneity of stations and pedestrian psychology. Therefore, this study aims to develop a comprehensive evacuation optimization strategy for metro stations by applying the concept of design for safety (DFS) to an emergency evacuation. This approach offers novel insights into the management of complex systems in metro stations during emergencies.

Physical and social factors affecting evacuations are identified. Moreover, the social force model (SFM) is modified by combining the fire dynamics model (FDM) and considering pedestrians' impatience and panic psychology. Based on the Nanjing South Metro Station, a multiagent-based simulation (MABS) model is developed. Finally, based on DFS, optimization strategies for metro stations are suggested.

The most effective evacuation occurs when the width of the stairs is 3 meters and the transfer corridor is 14 meters. Additionally, a luggage disposal area should be set up. The exit strategy of the fewest evacuees is better than the nearest-exit strategy, and the staff in the metro station should guide pedestrians correctly.

Previous studies rarely consider metro stations as sociotechnical systems or apply DFS to proactively reduce evacuation risks. This study provides a new perspective on the evacuation framework of metro stations, which can guide the designers and managers of metro stations.

The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel lockers (MPL) on costs and CO₂ equivalent (CO₂e) emissions in existing LMD networks, which include home delivery and shipments to stationary parcel lockers.

To describe customers’ preferences, we design a multinomial logit model based on recipients’ travel distance to pick-up locations and availability at home. Based on route cost estimation, we define the operating costs for MPLs. We devise a mathematical model with binary decision variables to optimize the location of MPLs.

Our study demonstrates that integrating MPLs leads to additional cost savings of 8.7% and extra CO₂e emissions savings of up to 5.4%. Our analysis of several regional clusters suggests that MPLs yield benefits in highly populous cities but may result in additional emissions in more rural areas where recipients drive longer distances to pick-ups.

This paper designs a suitable operating model for MPLs and demonstrates environmental and economic savings. Moreover, it adds recipients’ availability at home to receive parcels improving the accuracy of stochastic demand. In addition, MPLs are evaluated in the context of several regional clusters ranging from large cities to rural areas. Thus, we provide managerial guidance to logistics service providers how and where to deploy MPLs.

The purpose of this study is to explore beginning teachers’ diverse challenges and how these are related to self-directed professional learning through social media.

The authors conducted a content analysis of 2,445 “New Teacher” tagged posts shared in the r/Teachers subreddit. With 1,246 posts relevant to beginning teachers’ challenges, the authors used a socio-ecological model to analyze and categorize the challenges.

Results showed that posts reflected diverse and complex challenges. Such challenges were found to be interrelated and associated with employment status, highlighting teacher marginalization issues. Results also show that most posts sought resources or advice rather than merely complaining about their situations, meaning that beginning teachers leveraged the anonymity and shared affinity offered by r/Teachers to overcome their challenges as self-directed professional learners.

The current study not only highlights diverse and complex challenges faced by beginning teachers but also sheds light on how they navigate their challenges in social media spaces. This research provides unique insights into how social media, particularly an anonymous affinity space – r/Teachers, can benefit teachers’ professional growth in today’s digital era.

In this research work, the general form of reliability measures, which include availability, mean time to failure (MTTF), and sensitivity analysis, are investigated with their graphical representation, which would help designers and engineers improve the reliability of the system. Along with reliability assessment, a mathematical model is developed and solved to achieve the minimum cost of the system as well as maximum reliability.

In the proposed work, a general model of a solar seed sowing machine is considered for reliability evaluation using the Markov model process. The proposed system is a series-parallel arrangement of components where three components, namely the solar panel, batteries and direct current (DC) motor, are connected in series while all the operators are connected in parallel. The implemented Markov model approach assesses several parameters of reliability, which opens the scope for improvement in reliability and other measures like mean time to failure (MTTF) and sensitivity of the proposed system. So that the machine can deliver the desired output on the field. Also, the particle swarm optimization (PSO) algorithm is applied to optimize the cost of the system with the desired level of reliability.

Implementation of PSO provides the optimal cost for the proposed system with a predetermined level of reliability, which shows the relationship between reliability and cost of the system. Also, the Markov process approach provides the availability function, reliability function, reliability at different time values, MTTF and sensitivity of the proposed system.

This work evaluates the crucial characteristics of reliability for the proposed solar seed sowing machine using the Markov model which is a stochastic model. The assessment of reliability measures such as MTTF, availability and sensitivity plays a vital role in measuring and improving the performance of the machine in the actual environment. Examining the data obtained in this research is of great importance for the manufactures and system designers. Also, the powerful optimization technique PSO is implemented to solve a non-linear mixed-integer programming problem that provides the optimal cost for the system with desired reliability.

This study aims to examine how perceived brand credibility (PBC) moderates the adoption of the Internet of Things (IoT) and identifies the influencing variables that consumers consider while adopting IoT products and services. The study uses the technology acceptance model (TAM) and extends its constructs by investigating the role of PBC to measure the intention to use IoT.

To test the proposed relationships, data was gathered using the survey method, from respondents in India, an emerging market. The data was analyzed using partial least square based structural equation modeling (PLS-SEM). Moreover, the study measured the moderating effect of PBC and evaluated the effect of control variables – gender and degree of exposure to IoT.

The study found that perceived usefulness (PU) and perceived ease of use (PEOU) have a significant influence on customers’ attitudes towards using IoT devices and services. Further, PBC moderates the relationship between attitude and behavioral intention to utilize IoT devices and services. Both components of PBC – brand trustworthiness and trust – have significant moderating effect on the adoption of IoT-based services and devices.

The study tests TAM empirically in a new setting and extends it further. Introducing PBC as a moderating variable improves the understanding of the way consumers adopt IoT technology and hence strengthens the predictive power of TAM. Thus, the study provides rich insights for businesses to effectively position their IoT devices and services among their target users.

Numerous academic institutions have embarked on the pursuit of hybrid learning as an alternative approach, catering to students who opt for replacing a fraction of their conventional in-person meeting schedule with remote teaching. However, these new remote learning patterns have brought forth new stands against students' expectations. The universities have come across immense challenges in devising efficacious strategies that encompass the delivery, effectiveness and acceptability of hybrid courses. Consequently, identifying pivotal determinants related to user acceptance of technology persists as a crucial matter. This study aims to shed light on the adoption of hybrid learning from students' perspectives.

Structural equation modelling (SEM) was employed to scrutinise the proposed research model and hypotheses. A total sample of 444 students responded and partook in the survey. The data were analysed using AMOS software, a powerful tool for statistical analysis in the field of social sciences.

The findings of this study show that perceived service quality positively and significantly impacts the ease of use and usefulness of a hybrid learning system among students. In addition, the results demonstrate that ease of use and usefulness of the system positively and significantly influence students' favourable attitudes toward hybrid learning. Remarkably, the statistical analysis unveils the significant mediating effect of ease of use and usefulness in the relationship between perceived service quality and students' attitudes toward hybrid learning.

The findings suggest that the pervasive dependence on information systems and the quality of service from novel technologies continues to be a vital influence in the learning environment. The study has provided valuable insights into student perseverance learning strategies for higher education institutions.

This study's novelty lies in illuminating the crucial role of ease of use and usefulness as mediators, highlighting their criticality in enhancing students' attitudes towards hybrid learning. Notably, the study underscores that perceived service quality exerts a positive influence on ease of use and usefulness.

This study aims to examine the impact of the COVID-19 pandemic on the relationship between auditors’ work stress and client participation with audit quality (AQ).

This study is a descriptive-survey type and the data were collected through a questionnaire distributed online. The statistical population consisted of auditors working in audit firms in Iran and the sample was selected using a random sampling method. Structural equation modeling was used to analyze the data.

The findings of this study suggest that the COVID-19 pandemic exacerbated the negative relationship between auditors’ work stress and AQ. In addition, the results indicate that client participation in the audit process did not significantly impact AQ during the COVID-19 pandemic.

Given the global and widespread impact of the COVID-19 pandemic on individuals’ lives and work settings, this study provides an opportunity to explore the challenges auditors face concerning health protocols and their well-being during the pandemic, specifically within the context of Iran. The unique circumstances of the pandemic have placed additional pressure on auditors to navigate and address the challenges arising from COVID-19 in their workplaces. Although research on the effects of the pandemic on accounting and auditing is ongoing, this study contributes to the literature by expanding our understanding of the specific implications and circumstances faced by auditors during the COVID-19 outbreak.

The purpose of this study is to examine the influence of perceived risk (perceived susceptibility and perceived severity), self-efficacy and individual differences (personal innovativeness and mobile payment knowledge) on consumers’ intention to use contactless mobile payment services (MPS). Additionally, it also empirically tested the moderating effect of hygiene consciousness in the proposed conceptual model.

The present research developed a conceptual model based on the health belief model (HBM) and diffusion of innovation theory (DOI) to empirically assess whether and how perceived risk, self-efficacy and individual differences influence consumer intention to use contactless MPS. The data was collected using the survey method from 251 smartphone users and analyzed with structural equation modeling. The moderating role of hygiene consciousness was studied in the relationship that self-efficacy and personal innovativeness shares with consumers’ intention toward contactless MPS.

The results of this study disclose that among all precursors of consumers’ intention toward contactless MPS, only perceived severity, self-efficacy, personal innovativeness and mobile payment knowledge positively affect consumers’ intention to use contactless MPS. However, the effect of perceived susceptibility on consumers’ intention toward contactless MPS was found to be non-significant. The results further depict that hygiene consciousness acts as a moderator in driving consumers’ intention toward contactless mobile payment services.

The HBM model and DOI, which incorporate perceived risk, self-efficacy, individual differences and hygiene consciousness, give light on the factors influencing consumer intention to use contactless MPS in a pandemic situation such as COVID-19. The study will provide useful insights to marketers on how to frame their strategies in the aftermath of pandemics, as the contactless mobile payment method may be perceived as a defensive behavior during and after pandemics.

The study will provide useful insights to marketers on how to frame their strategies in the aftermath of pandemics, as the contactless mobile payment method may be perceived as a defensive behavior during and after pandemics.

By uniting perceived risk, self-efficacy and individual differences with consumers’ intention toward contactless MPS in a conceptual model, along with examining the moderating role of hygiene consciousness, this work responds to the calls for upcoming research concerning mobile payment systems as means of future payment. Thus, it offers an understanding of particular consumer motivations that may guide consumers’ intention toward contactless MPS through the theoretical lens of HBM and DOI.

Recently, autonomous vehicles (AV) acceptance has been studied intensively. This paper aims to map and analyze the bibliometric characteristics of AV acceptance literature. Furthermore, this research aims to identify research gaps and propose future research opportunities.

The bibliometric analysis was performed. Scopus database was used as the source of the literature. This study selected and analyzed 297 AV acceptance papers. The performance and science mapping analysis were performed.

The developed countries tended to dominate the topic. The publication outlet tended to be in transportation or technology journals. There were four research themes in existing literature. Technology acceptance model (TAM) and UTAUT2 tended to be used for explaining AV acceptance. AV acceptance studies tended to use two types of psychological concepts for understanding AV acceptance, namely risk related concepts and functional utilitarian benefit related concepts. In the context of research design, quantitative approach tended to be used. Self-driving feature was the most exploited feature of AV in the existing literature. Three research gaps were mapped and future research opportunities were proposed.

This paper provided a comprehensive information that allowed scientists to develop future research on AV acceptance.

There is lack of paper that discussed the bibliometric characteristics of AV acceptance literature. This paper fulfilled the gap.