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The purpose of this study is to test and validate a scale for measuring project resilience in the construction sector within the built environment. By identifying relevant indicators and items, the study aims to enhance the resilience of construction projects and minimize losses and failures resulting from disruptive events such as societal, technological, biological and environmental hazards (e.g. Covid-19, war in Ukraine, shortage of resources, etc.).

The study uses a quantitative approach, specifically exploratory factor analysis and confirmatory factor analysis, to evaluate the suitability, dimensionality and reliability of the proposed indicators and items for measuring project resilience in the construction sector.

The study found that 9 indicators and 34 items were suitable for measuring project resilience in the construction sector, and the proposed model showed good fit for the two dimensions of project resilience, which may have practical implications for project managers in the construction sector within the built environment.

The study proposes a new scale for measuring project resilience in the construction sector, which is a novel contribution to the field of project management. The study identifies specific indicators and items that are relevant to this industry, which may have practical implications for project managers in this sector. The study also highlights the need for further research to make the project resilience scale more robust and reliable.

This paper explores the impact of multiple team membership (MTM) on the productivity of team members in engineering consulting firms. MTM refers to employees participating concurrently in multiple teams, a concept closely linked to projectification. Despite the fact that this concept can enhance collaboration, it also introduces coordination challenges that may negatively affect productivity.

Through an inductive approach involving 12 semi-structured interviews with engineering consulting professionals specializing in water and energy infrastructure projects, this paper examines the factors affecting team member productivity in an MTM setting. Following the interviews, a Delphi technique was employed, engaging 16 experts to rank the factors and sub-factors identified from the interview data. This two-stage approach ensured a comprehensive and validated assessment of productivity factors.

This study develops 8 factors process model grounded in structuration theory to explain the socio-technical mechanisms by which multiple team membership shapes productivity outcomes in engineering consulting firms specialized in water and energy infrastructure projects. Key findings surface micro-foundations, tensions in technology provisions, planning processes, and career development that inform theoretical advances and practical improvements.

This research contributes empirically insights into managing MTM in expert service contexts. Applying Giddens' structuration theory, this study reveals how agency and structures shape productivity across organizational, team, and individual levels. In practice, this study provides recommendations for improving productivity within projectified environments, mainly for team members working in an MTM environment in engineering consulting firms specializing in water and energy infrastructure projects.

As part of the scale development process, this paper aims to test a scale to measure organizational resilience for the oil and gas industry. The objective is to provide stakeholders with a set of indicators to evaluate their organizations and prepare them to cope with the negative consequences of disruptions (e.g. Covid-19, shortage of resources, etc.).

The paper conducts exploratory and confirmatory factor analysis to test the suitability, dimensionality and reliability of specific indicators and their items under examination. Therefore, the goal is not to validate hypotheses by testing an organizational resilience scale in the oil and gas industry.

The study tests and proposes a scale to effectively measure organizational resilience within the oil and gas industry. A comprehensive set of ten indicators and 40 items are identified through this process. The findings of this research provide stakeholders in this sector with a rigorous set of indicators to evaluate the strengths and weaknesses of their organizations and better prepare them to handle disruptions.

This paper fills the gap in existing research by testing and proposing a scale to measure organizational resilience specifically for the oil and gas industry. It highlights the importance of organizational resilience for survival in a sector that is especially susceptible to disruptions.

This study examines the social acceptance and potential for residential solar integration in Abu Dhabi to support sustainable urban innovation and prosperity. A survey of 216 Abu Dhabi residents analyzed four scenarios for incentivizing household solar panel adoption. Results demonstrate high interest and preference for governmental financial support mechanisms to spur solar integration. This research contributes an assessment framework and citizen engagement insights that could inform smart city development strategies focused on renewable energy transformation across the Gulf region. As urban centers like Abu Dhabi strive to enact their visions for economic diversification and environmental sustainability, understanding citizen perspectives on innovations like distributed solar will be critical to align technology advancement with societal needs and values. The methodology and findings of this Abu Dhabi case study provide a model to catalyze stakeholder buy-in for new energy solutions, with potential applications for other Gulf cities aiming to transition their energy systems and build integrative renewables infrastructure to power next-generation smart development. This solar integration acceptance research lays the groundwork for continued scholarly discourse and policymaker collaboration around smart cities in the Gulf that realize multidimensional progress for society, economy, and environment.

M-wallets have emerged as one of the most important financial innovations of the 21st century, enabling users to carry digital cash by securely storing payment methods on their mobile devices. However, the continued use of m-wallets varies among people for several reasons. This study used the technology continuation theory (TCT), gamification and trust factors to examine the variables affecting consumers' intentions to continue using mobile wallets.

The SmartPLS partial least squares software was used to analyze data from 431 m-wallet users in Vietnam using the structural equation modeling technique.

The data revealed that the research model can predict users' intentions to continue using mobile wallets. TCT constructs demonstrated strong exploratory power in explaining consumer satisfaction and attitudes towards m-wallets. Furthermore, the study confirmed the direct effect of the perceived effectiveness of gamification on perceived ease of use and attitude, as well as its indirect effect on consumers' continued use intentions of mobile wallets via attitude. In addition, the trust negatively influenced consumers' intentions to continue using m-wallets.

The findings of this study can help researchers, practitioners and policymakers improve m-wallet design, development and adoption, as well as advance financial technology and define the future of digital payments in terms of consumer attraction, engagement and financial inclusion.

Based on TCT theory, this study enriches m-wallet research by examining two important factors, gamification and trust, and thus provides insights into how to improve consumers’ intentions to continue using m-wallets in developing countries. This study offers timely insights into theory and practice regarding these factors. It therefore paves the way for researchers and practitioners to learn how easy, enjoyable and secure the end-user experience should be to keep users engaged with m-wallets.

This study aims to investigate consumer brand loyalty toward halal cosmetics using the theory of planned behavior through repurchase intention, which is primarily relying on the consumer’s attitude toward halal cosmetics. Important predictors such as trust on halal cosmetics, quality of halal cosmetics and religious beliefs of millennial Muslim female consumers shape consumer attitude.

The present study used the quantitative research design and deductive approach to collect the data from 275 halal cosmetics users in Pakistan by using a judgmental sampling approach.

Findings of the study provide useful insights for both theory and practice. The results support product quality, religious belief and trust on halal cosmetics as predictors of consumer’s attitude toward halal cosmetics that further develop consumers’ repurchase intention, which in turn enhances their overall brand loyalty. Besides, the findings also show that consumer repurchase intention has a mediating effect between consumer attitude toward halal cosmetics and consumer brand loyalty.

The current study helps in advancing practitioners’ understanding of female consumers’ brand loyalty in the halal cosmetics context. This study is considered to be greatly helpful for managers to gain knowledge about how repurchase intention and brand loyalty of millennial Muslim female consumers can be developed in the halal cosmetics segment, especially in the case of Pakistan.

Brand loyalty has been investigated by previous studies through different predictors and antecedents. This study contributes to the literature of brand loyalty by empirically examining and validating the different antecedents of consumer attitude that are accountable for creating consumer brand loyalty in the domain of halal cosmetics within the Pakistani cultural context. The current study also enhances the previous scholarly understanding on halal cosmetics by investigating the mediating role of consumer repurchase intention of halal cosmetics that further extends the discussion for both theory and practice.

Artificial intelligence (AI) customer service has grown rapidly in recent years due to the emergence of COVID-19 and the growth of the e-commerce industry. Therefore, this study employs the integration of the stimuli–organism–response (SOR) and the task-technology fit (TTF) frameworks to understand the factors that affect individuals’ intentions towards AI customer service adoption in Malaysia.

The study utilised a survey-based research approach to investigate the factors that affect individuals’ intentions towards AI customer service adoption in Malaysia. The data were collected by conducting an online survey targeting individuals aged 18 or above who had prior customer service interaction experience with human service agents but had not yet adopted AI customer service. A sample of 339 respondents was used to evaluate the hypotheses, adopting partial least squares structural equation modelling as a symmetric analytic technique.

The PLS-SEM analysis revealed that social influence and anthropomorphism have a positive direct relationship with emotional trust. Furthermore, communicative competence, technology characteristics and perceived intelligence were positively correlated with TTF. Moreover, emotional trust significantly impacts AI customer service adoption. In addition, AI readiness positively moderates the association between task technology fit and AI customer service adoption.

The study provides insights to individuals, organisations, the government and educational institutions to improve the features of AI customer service and its development in Malaysia.

The originality of this study is found in its adoption of the SOR theory and TTF to understand the factors affecting AI customer service adoption. Additionally, it incorporates moderating variables during the analysis, adding depth to the findings. This approach introduces a new perspective on the factors that impact the adoption of AI customer service and offers valuable insights for practitioners seeking to formulate effective strategies to promote its adoption.

This study aims to analyze a conspicuous corpus of literature related to the field of technology-based intensive care research and to develop an architecture model of the future smart intensive care unit (ICU).

Papers related to the topics of electronic health record (EHR), big data, data flow and clinical decision support in ICUs were investigated. These concepts have been analyzed in combination with secondary use of data, prediction models, data standardization and interoperability challenges. Based on the findings, an architecture model evaluated using MIMIC III is proposed.

Research identified issues regarding implementation of systems, data sources, interoperability, management of big data and free text produced in ICUs and lack of accuracy of prediction models. ICU should be treated as part of a greater system, able to intercommunicate with other entities.

The research examines the current needs of ICUs in interoperability and data management. As environment changes dynamically, continuous assessment and evaluation of the model with other ICU databases is required.

The proposed model improves ICUs interoperability in national health system, ICU staff intercommunication, remote access and decision support. Its modular approach ensures that ICUs can have their own particularities and specialisms while ICU functions provide ongoing expertise and training to upgrade its staff.