Digital disruption has been the most used and discussed topic in the last 6 years and has been a trending topic on the Google trends, only second to the remote working searched on Google search engines. Most business continuities have been put at risk due to significant reasons like COVID-19, Social distancing norms, and technology disruption to name a few. Businesses especially in UAE higher education sector need to take a holistic view that considers potential threats to an organization and look at providing a resilience framework to respond effectively to safeguard the key stakeholder’s interests. The research study looks at combining the business continuity maturity model and the digital disruption models and suggests a framework that business managers and owners can consider mitigating the risks and enhancing the resilience of their organization for the future. The organization might be able to enhance its brand value and look at creating more value in its services. This study can help managers and top management look at the factors that can improve performance after the disruption. The participants can be trained to work during disruption to mitigate the risk or crisis, reducing major losses in business.

Machine learning (ML) has seen a substantial increase in its role in improving operations for staff and customers in different industries. However, there appears to be a somewhat limited adoption of ML by farm businesses, highlighted by a review of the literature investigating innovative behaviors by rural businesses. A review of the literature identified a dearth of studies investigating ML adoption by farm businesses in rural regions of the United Arab Emirates (UAE), especially in the context of family-owned farms. Therefore, this paper aims to investigate the drivers and barriers to ML adoption by family/non-family-owned farms in rural UAE. The key research questions are (1) what are the drivers and barriers for rural UAE farms adopting ML? As well as (2) is there a difference in the drivers and barriers between family and non-family-owned farms? Twenty semi-structured interviews were conducted with farm businesses across several rural regions in the UAE. Then, through a Template Analysis (TA), drivers and barriers for rural UAE-based farm owners adopting ML were identified. Interview findings highlighted that farms could benefit from adopting ML in daily operations to save costs and improve efficiency. However, 16 of 20 farms were unaware of the benefits related to ML due to access issues (highlighted by 12 farms) in incorporating ML operations, where they felt that incorporating ML into their operations was costly (identified by 8 farms). It was also identified that non-family-owned farms were more likely to take up ML, which was attributed to local culture influencing family farms (11 farms identified culture as a barrier). This study makes a theoretical contribution by proposing the Machine Learning Adoption Framework (MLAF). In terms of practical implications, this study proposes an ML program specifically targeting the needs of farm owners in rural UAE. Policy-based implications are addressed by the findings aligning with the United Nations’ Sustainability Development Goals 9 (Industry, Innovation, and Infrastructure) and 11 (Sustainable Cities and Communities).

Generally and in the UAE, businesses worldwide are particularly affected by the COVID-19 pandemic. The SME companies in Dubai UAE faced a very tough challenge to deal with the new circumstances of lockdown and curfews in running the international business. The purpose of the current study was to analyze the effect of the COVID-19 pandemic on Business Performance. The theoretical frameworks for this study are Process Theory of Internationalization (PTI), Uppsala-model (the U-model), and internalization theories and the link with IB theories applications nowadays. The quantitative study applied a nonexperimental, deductive approach and explanatory correlation design, and Snowball sampling was used to select stakeholders of integrated remote site management (IRSM) services in Dubai, UAE. Data was collected at a single phase using a cross-sectional survey instrument and analyzed using inferential statistics with the aid of SPSS. The survey results revealed that the COVID-19 pandemic did not significantly change the efficiency performance of the IRSM stakeholders. Stakeholders' confidence in their strategic leaders did not decrease while working under the constraints of the COVID-19 pandemic. The study did not account for any changes in employee or leaders’ behavior over time.  This Empirical study findings add value to the limited literature on the correlation between the COVID-19 pandemic and the strategic leadership of international businesses. The paper’s practical implications would be further study on strategic leadership in IB and efficiency performances during global pandemics.

This study is about time observance and productive performance among employees in the selected city governments in the Philippines. Principally, it attempts to determine if performance of employees is influenced by time observance. Specifically, it is concerned with the level of productive performance among civil servant respondents (n=1,142) as gauged by the attainment of targets and performance rating, the influence of time observance to productive performance, the time-related problems encountered by the civil servant respondents; and lastly, the suggested solution to the time related problems encountered by the respondents. This study utilized the qualitative, descriptive method that employed primary data. A structured questionnaire has been used to explore the set of variables proposed in this study as they apply to local situations. The present study explored the Filipino concept and utilization of official time and how this bears on the performance of their official function. The results of the study concur that in dealing with employees, one must consider individual's idiosyncrasy. In the case of the small minority of sampled employees whose time observance had been marked by tardiness and absenteeism, supervisors must make it their responsibility to observe them individually so that appropriate solutions can be applied. The 90 percent of the sample who were punctual among the respondents does not pose as a problem insofar as punctuality is concerned. To reinforce the positive behavior of this group and to provide encouragement of the small minority who came to the office either tardy or absent, inculcation on the benefits of wise use of mandated time must be done.

For UAE end-users, consumer behavior and purchasing power faced many swings period after Covid 19 pandemic. Recently, changes in sales capacity and customers' preferences for eco-friendly products highlighted the industrial gap for producers before and after the pandemic. Green marketing practices aim to improve customer knowledge to increase consumer loyalty, preserve wealth, and reduce global environmental degradation. The research examines the relationship between changes in consumer purchasing behavior and green marketing strategies following the COVID-19 pandemic in the UAE's oil and gas lubricants industry. It also assesses the efficacy of green marketing in improving the dynamic of organization performance. Stakeholders and three bottom lines theories formed the theoretical background for this research. The paper's methodology is quantitative with deductive approaches and inferential statistical analysis, while the sampling strategy is a snowball, with 162 respondents, through quantitative methods, most notably surveys. The primary findings of this study established a substantial positive correlation between both study variables and consumer attitudes toward green marketing initiatives. Consumer opinion differs according to geographical ages when developing and advertising environmentally friendly products. Meanwhile, the article examined how consumers’ behavior of economic themes changed prior to and following the Covid-19 pandemic epidemic.