Harman Preet Singh

This study empirically examines the impact of Internet of Things (IoT)-based Customer relationship management (CRM) on the satisfaction and loyalty of Saudi airline customers. Utilizing the Resource-based view (RBV) as a theoretical lens, the study posits that service quality and network linkages are twin capabilities of IoT-based CRM that enable airlines to satisfy customers and earn their loyalty. Based on the partial least squares structural equation modeling (PLS-SEM) analysis of survey data from 461 customers, the research finds that five service quality features of user-friendliness, personalized services, reliability, security, and information quality positively impact customer satisfaction, whereas accessibility did not. The results also indicate that airlines’ linkages with partner airlines and airports significantly affect consumer satisfaction, whereas their alliances with banks and hotels do not. Moreover, satisfied customers are likely to be loyal. Therefore, Saudi Airlines should focus on the five service quality features and two linkage features to succeed and thrive in the current competitive environment. This will allow them to contribute to Saudi Vision 2030 by promoting tourism and leveraging digital transformation.

This study examines one of the most underexplored segments of e-commerce: online shopping for health, beauty, and wellness products. Using secondary data from official sources, we examine the influence of economic, demographic, technological, geographic, and health factors on the rise of online shopping for healthy, beauty, and wellness products in 83 regions of Russia. Multi-level linear regression was used for data analysis, enabling the nesting of regions in federal geographic districts. The findings are mostly mixed. The results show that internet speed (not access), economic performance, and the number of doctors within a region positively and significantly influence online shopping for these products within the region, whereas other factors were either negative or statistically insignificant. These results highlight the significance of macro-level factors, such as regional wealth, reliable internet infrastructure, and skilled healthcare professionals, in promoting online shopping for health, beauty, and wellness products. The research highlights the significance of regional factors in fostering equitable digital wellness access in Russia. Policymakers and industry stakeholders can utilize the study insights to promote online shopping initiatives in this specialized segment.

COVID-19 significantly disrupted the progress of the SDGs globally, including in Saudi Arabia. This study explores the progression of SDGs in Saudi Arabia during and after COVID-19, focusing on four dimensions: financial, socioeconomic, health, and environmental. A qualitative approach was employed, involving 19 semi-structured interviews conducted in two rounds (during and post COVID-19). Thematic analysis, conducted using NVivo 14.0, identified four main themes and 16 subthemes, which align with the SDG dimensions. The study revealed significant disruptions across four SDG dimensions during the pandemic. These included economic downturns, increased poverty, strained healthcare systems, and environmental changes. Guided by systems theory as an analytical lens, the study findings indicate that while COVID-19 caused disruptions across SDGs, it also acted as a catalyst for transformational shifts across interconnected SDG domains. The post-pandemic period has shown recovery, including economic growth, enhanced gender equality, improved mental health services, and a renewed focus on sustainability. Six cross-thematic themes emerged: (1) economic recovery and employment, (2) gender equity and education, (3) mental health and healthcare, (4) poverty reduction and food security, (5) environmental sustainability, and (6) digital transformation resilience. Based on these insights, the study provides recommendations for Saudi policymakers to align SDG progress with Saudi Vision 2030 in line with pragmatic sustainability.

In recent times, Artificial Intelligence (AI) has been increasingly adopted in the educational domain. Intelligent learning assistants (ILAs) have emerged as a transformative AI tool enabling autonomous, personalized, and collaborative learning among students and enhancing their learning ability. However, prior research has not examined the impact of ILAs on enhancing student creativity. This research uses self-determination theory (SDT) as a theoretical lens to examine the impact of ILAs-enabled autonomy, competence, and relatedness on student creativity. The empirical analysis of 304 surveys of university students in Saudi Arabia indicates that ILAs-enabled autonomy, competence, and relatedness positively impact students’ creativity. This study enriches the literature by informing the potential of ILAs-enabled autonomy, competence, and relatedness to enhance student creativity. The study contributes to the theory by extending applications of SDT in the AI-based educational domain. The study has important implications for higher education institutions to leverage AI tools (like ILAs) to enhance student creativity. Policymakers can utilize the study findings to promote an enabling environment for effectively utilizing AI tools (like ILAs) in the education sector to increase student creativity. Nonetheless, meticulous implementation of ILAs is essential to prevent inadvertent infringement on student autonomy, competence, or relational engagement.

The principal objectives of this study were to determine how government spending on human capital, specifically on education and healthcare, impacts Saudi Arabia’s economic growth and its policy implications for sustained economic growth and development. Given the above objectives, this study examined the short-term dynamics and long-term relationships between government spending on human capital, measured by per capita education and healthcare expenditures, and its impact on Saudi Arabia’s economic growth, measured by per capita real GDP, from 1985 to 2021. The Non-linear Auto-regressive Distributed Lag (NARDL) models were used to estimate and examine the relationships. The study concluded that per capita GDP is negatively correlated with per capita government spending on healthcare and positively correlated with per capita spending on education in Saudi Arabia. Per capita GDP is also positively related to exports per capita. The results of the coefficient symmetry test show that per capita spending on healthcare and education causes long-term, asymmetric effects on Saudi Arabia’s per capita GDP, that is, the decline in per capita GDP resulting from a decrease in education spending per capita is larger than the increase in per capita GDP resulting from an increase in education spending per capita. However, the decline in per capita GDP resulting from an increase in healthcare spending per capita is larger than the increase in per capita GDP resulting from a decrease in healthcare spending per capita. The study also found unidirectional causality from per capita spending on healthcare, education, and exports to per capita GDP. Therefore, this study infers that increases in government healthcare spending reduce economic growth, whereas increases in spending on education contribute to it. Saudi Arabia’s economy also experiences export-led economic growth. The results of this study provide the government and policymakers with valuable insights with respect to the efficient allocation of scarce government resources to education and healthcare for sustained economic growth and development.

Senior citizens are the fastest growing demographic in the world. Amid an intensification of digitalisation across every sector, evidence suggests older people are slow to adopt and use many online tools and services. Moreover, despite studies showing differences in the online behaviour of older people compared to the rest of the population, established models specifically dedicated to explaining their behaviour have remained limited. Therefore, based on components of UTAUT, we propose a new conceptual model that specifically focuses on senior citizens. We introduce four new constructs: health needs, place of settlement (rural/urban), perceived trust, and perceived risk. Data were collected from 320 seniors in Russia and a structural equation modelling was used for data analysis. With a cumulative variance of 86%, the test and validation results demonstrate that our proposed model provides a better explanation of older people’s online shopping behaviour than the original UTAUT model. This model provides an important framework for future studies on the digital shopping behaviours of seniors.

Student dropout and its economic and social consequences are significant issues in developing countries. Students who drop out experience reduced employment prospects and encounter social stigma. While early dropout prediction can assist in mitigating the consequences, it remains a considerable challenge. The present research employed a data mining approach to predict dropout of public health master-level students in Saudi Arabia, a developing nation that has invested considerable resources to promote higher education. The research model focused on three fundamental determinants of students’ dropout: individual, institutional, and academic. The study analysis on a dataset of 150 students revealed that all three determinants predicted student dropout. The results indicated that students with low academic performance who received an academic warning were likelier to drop out. Freshmen with poor academic achievement were particularly at risk of dropping out of college. Students between 31 and 36 years old who attended technical courses as a subject specialization could also dropout. The research contributes to the literature by suggesting that universities should consider these individual, institutional, and academic determinants to develop their dropout prevention strategies. This study has ramifications for university administrators in developing nations, such as Saudi Arabia, who can establish dropout prevention programs based on the determinants revealed in this study.

Online grocery shopping has grown rapidly in recent years. It has been promoted as a way to overcome the systemic inequalities in food access and increase sustainable food practices. A growing body of studies has highlighted the impact of income, food prices, and internet access/connection on shaping people’s behavior in buying groceries online. However, there is a dearth of prior studies that have examined the impact of these three factors at the macro/meso level. Therefore, this paper presents an analysis of these factors from a sample of 16 Russian regions with a combined population size of more than 44 million people. We used a fixed effects linear regression model to analyze panel data on median income, mobile internet connection, food price index, and online grocery sales. Our results show the significant impact of income and imply that while online grocery shopping holds huge promise for overcoming unequal access to food and achieving sustainability, entrenched challenges such as poverty and income inequality might be difficult to shake off.