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The purpose of this study is to examine faculty perceptions of the aim/structure of the United Arab Emirate's Qualifications Framework (QF Emirates) and its impact on academic practices in order to support policymakers on how to better implement the framework.

The study applied a mixed-methods approach to obtain quantitative and qualitative feedback from faculty members from two of the largest higher education institutions in the United Arab Emirates (UAE), namely the UAE University (UAEU) and the Higher Colleges of Technology (HCT). A questionnaire was used to capture broad insight from a sample of 788 faculty members from both institutions. In addition, semistructured interviews were conducted with 20 faculty members to offer more in-depth analysis of how to improve QF Emirates strategies in light of the current challenges and future aspirations.

The study revealed that faculty members have an overall “average” to “high” perceptions of the general aim/structure of the QF Emirates and its impact on teaching, learning and assessment. Moreover, the study revealed that faculty from the HCT have a significantly higher perception of the QF Emirates implementation compared to faculty from the UAEU. The study concluded with proposing a number of solutions to support in improving the QF Emirates implementation, including raising awareness across stakeholders, identifying and communicating faculty roles in the process, and developing polices, guidelines and systems to support consistent integration of QF Emirates into academic practices.

The outcomes of this study would add to the existing body of knowledge pertaining to the role of stakeholders (e.g. faculty members) in the implementation of the national qualifications framework. It addition, it can drive future professional development activities and add to the discourse around the conceptual framework of NQFs. Outcomes of the study could also provide additional information on the use of the QF Emirates as a supporting instrument. Last but not least, this work could provide insight to policymakers in regard to institutional support that would promote effective adoption of the QF Emirates.

Smart banking services (SBS) are critical for developing countries to achieve developmental goals. The success of SBS is dependent on the considerable perceived customer experience of provided services. Based on technology adoption studies, this study aims to model smart customer experience (SCE) outcomes by investigating the relationships between SCE, customer gratitude, continuance intentions and positive word-of-mouth (P-WOM).

The current research included 384 bank clients as participants. The data were analyzed using partial least squares structural equation modeling (PLS-SEM).

According to the findings, SCE directly increases customer gratitude, continuance intention to adopt smart services and P-WOM. Customer gratitude enhances continuance intentions and P-WOM. Additionally, customer gratitude mediates the relationship between SCE, continuance intention and P-WOM. Finally, the findings revealed that customer innovativeness and optimism play a substantial moderating impact among the variables studied.

This is the first research to include all of these variables. Furthermore, to the best of the authors' knowledge, this is the first empirical study of these linkages in the banking sector of emerging nations.

The main intention of this paper is to understand humanistic leadership through an eminent leader representing the United Arab Emirates (UAE) culture. The authors identified a prominent humanistic leader of a well-known private university in Dubai as an example, analyzing his leadership approach from a humanistic lens and demonstrating humanistic leadership characteristics linked to the cultural roots.

This paper is designed as a single case to examine how humanistic leadership behaviors and practices are applied in an organization and how they are connected to the UAE culture. The leader and his seven followers are interviewed by using semi-structured forms, and inductive conventional content analysis was utilized to identify common themes and concepts related to humanistic leadership traits in the UAE.

The paper highlights ten themes named humility, respect, care, fairness, transparency, well-being orientation, generosity, family focus and will with humanistic determination. These themes coincide with the various well-accepted humanistic literature theories and are also aligned with salient Islamic values and the existing humanistic leadership theories. A humanistic leadership description is provided to show the implications to the UAE context.

This study only focuses on a single higher education institution, and further studies need to be conducted to reach a generalization.

The paper offers an alternative humanistic leadership for government departments, semi private and private companies to create an organizational culture where those values are flourished and creating an awareness in youth leadership programs to include humanistic leadership principles that will eventually increase social welfare.

This study provides an insight into humanistic leadership phenomenon by giving a contextual example from the UAE. As there has been no attempt to link humanistic leadership to the UAE culture, the findings of this paper will contribute to cross-cultural leadership research.

This study aims to examine the impact of cultural values [power distance (PD), uncertainty avoidance (UC), individualism vs collectivism (IC) and time orientation] and users’ perceptions on the adoption of big data analytics (BDA) within the context of the United Arab Emirates (UAE) health-care sector. It uses the unified theory of acceptance and use of technology (UTAUT) model as its theoretical foundation.

A cross-sectional survey involving 256 health-care organization users in major hospitals across the UAE was conducted. Smart partial least squares (PLS) structural equation modeling was used to assess users’ behavioral intentions (BI) to use BDA in the health-care context.

Results indicate that performance expectancy, social influence, facilitating conditions and perceived trust significantly predicted respondents’ BI to use BDA. However, effort expectancy, perceived security and time orientation were found to have insignificant impacts on BI. Interestingly, the remaining cultural values (PD, UC and IC) did not significantly affect the relationship between social influence and BI in the context of BDA adoption in health care.

This study contributes to the literature by examining the role of cultural dimensions in BDA adoption within health-care organizations, particularly in the underrepresented UAE health-care context. Moreover, it extends the application of the UTAUT model to the BDA adoption in health care, providing insights into the factors affecting users’ BIs to use the technology.

This study aims to assess the effectiveness of a scale measuring artificial intelligence capabilities by using the resource-based theory. It seeks to examine the impact of these capabilities on the organizational-level resources of dynamic capabilities and organizational creativity, ultimately influencing the overall performance of government organizations.

The calibration of artificial intelligence capabilities scale was conducted using a combination of qualitative and quantitative analysis tools. A set of 26 initial items was formed in the qualitative study. In the quantitative study, self-reported data obtained from 344 public managers was used for the purposes of refining and validating the scale. Hypothesis testing is carried out to examine the relationship between theoretical constructs for the purpose of nomological testing.

Results provide empirical evidence that the presence of artificial intelligence capabilities positively and significantly impacts dynamic capabilities, organizational creativity and performance. Dynamic capabilities also found to partially mediate artificial intelligence capabilities relationship with organizational creativity and performance, and organizational creativity partially mediates dynamic capabilities – organizational creativity link.

The application of artificial intelligence holds promise for improving decision-making and problem-solving processes, thereby increasing the perceived value of public service. This can be achieved through the implementation of regulatory frameworks that serve as a blueprint for enhancing value and performance.

There are a limited number of studies on artificial intelligence capabilities conducted in the government sector, and these studies often present conflicting and inconclusive findings. Moreover, these studies indicate literature has not adequately explored the significance of organizational-level complementarity resources in facilitating the development of unique capabilities within government organizations. This paper presents a framework that can be used by government organizations to assess their artificial intelligence capabilities-organizational performance relation, drawing on the resource-based theory.

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

The COVID-19 pandemic has impacted 222 countries across the globe, with millions of people losing their lives. The threat from the virus may be assessed from the fact that most countries across the world have been forced to order partial or complete shutdown of their economies for a period of time to contain the spread of the virus. The fallout of this action manifested in loss of livelihood, migration of the labor force and severe impact on mental health due to the long duration of confinement to homes or residences.

The current study identifies the focus areas of the research conducted on the COVID-19 pandemic. Abstracts of papers on the subject were collated from the SCOPUS database for the period December 2019 to June 2020. The collected sample data (after preprocessing) was analyzed using Topic Modeling with Latent Dirichlet Allocation.

Based on the research papers published within the mentioned timeframe, the study identifies the 10 most prominent topics that formed the area of interest for the COVID-19 pandemic research.

While similar studies exist, no other work has used topic modeling to comprehensively analyze the COVID-19 literature by considering diverse fields and domains.