This study aims to investigate individual behavior towards adoption of telemedicine application based on wireless sensor network applications (WSN) during COVID-19 pandemic. Therefore, the research model extends the unified theory of acceptance and use of technology with the task technology fit model, awareness and self-efficacy to determine user intention to adopt wireless sensor network application for medical assistance. A research survey was conducted towards Saudi citizens in voluntary setting. In response, 348 valid responses were retrieved. Sample size was computed with prior-power analysis using G-power software. The research model is empirically tested with latest statistical approach namely structural equation modeling (SEM). Findings of the structural model indicate that wireless sensor network application was jointly predicted by performance expectancy, social influence, effort expectancy, facilitating condition, task technology fit, awareness and self-efficacy and explained substantial variance R2 79.5% in individual behavior to adopt wireless sensor network application. The effect size analysis (f2) revealed that task technology fit and facilitating condition were the most important factors to determine user intention to adopt wireless sensor network application. The current study contributes to theory by extending the unified theory of acceptance and use of technology with task technology fit model, self-efficacy and awareness and enrich information system literature in the context of user intention to adopt wireless sensor network application. Practically, this study suggest that health consultant should focus on technology fitness including wireless devices and the number of facilities to operate wireless sensor network which in turn boost user confidence towards adoption of wireless sensor network application for health consultation. This study develops a unique research model that inspects user behavior towards adoption of wireless sensor network technology for better health care system. The findings of this study answer how to monitor COVID-19 while using of wireless sensor network applications. Moreover, this study is useful for clinical management through virtual environment and guides health advisors, software developers and physicians to design user friendly telemedicine application by using wireless sensor network technology.

The aim of this research was to investigate factors that influence logistics firms’ supply chain agility and supply chain resilience. Therefore, an integrated research model based on strategic human resource management and artificial intelligence was developed to determine the agility and resilience of logistics firms. Empirical data were collected from 221 employees working in manufacturing firms in Saudi Arabia. For the data analysis, a structural equation modeling approach was used. The results indicated that joint leadership, employee skills, organizational culture, competitive intensity, human capital development, and artificial intelligence had substantial explained variance $R^2$ of 80% for supply chain agility. Similarly, an importance performance analysis revealed that, within the integrated research model of supply chain agility, the factors of leadership, human capital development, and organizational flexibility had greater importance in determining supply chain resilience. Practically, this research shows that factors like leadership, employee skills, organizational culture, competitive intensity, human capital development, and artificial intelligence are positively associated with supply chain agility and, hence, require policymakers’ attention. The value of this research lies in its integration of artificial intelligence, organizational flexibility, and strategic human resource management to explore supply chain agility and its examination of the impact of these factors on supply chain resilience.

The COVID-19 pandemic has disrupted supply chain operations globally. Nevertheless, resilient firms have the capacity to combat an unprecedented situation with the right strategic approach. The current research has developed an integrated research model that combines factors such as supply chain intelligence, supply chain communication, leadership commitment, risk management orientation, supply chain capability and network complexity to investigate supply chain resilience. The research model of this study was empirically tested with 309 responses collected from supply chain managers. Results revealed that supply chain resilience is measured with supply chain intelligence, supply chain communication, leadership commitment, risk management orientation, supply chain capability and network complexity and demonstrated a substantial variance $R^2$ of 0.548% towards supply chain resilience. Practically, this study suggests that supply chain managers should focus on factors such as big data analytics, risk management orientation,1 supply chain communication and leadership commitment to enhance supply chain resilience and sustainable supply chain performance.

The quick response (QR) code-enabled mobile payment has gained large attention from academicians and policymakers due to its fast, convenience, and usefulness. However, acceptance of this technology among consumers is limited and rare in a few cases. Therefore, current research attempts to gain insight into factors that influence consumer behavior to adopt QR code-enabled mobile payment. This research has developed an integrated research framework that combines the technology acceptance model, theory of reasoned action, transaction speed, convenience, and innovativeness to investigate consumer behavior to adopt QR code mobile payment. In addition to that moderating effect of transaction speed is tested between consumer attitude and intention to adopt QR code-driven mobile payment. This study empirically investigates consumer attitudes and intention to adopt the QR mobile payment system with 216 responses. Findings of the statistical analysis have revealed that perceived usefulness, perceived ease of use, convenience, subjective norms, and innovativeness explained a substantial variance $${R}^{2}$$R 2 52.3% in measuring user attitude to adopt QR code-enabled mobile payment. Practically, this study suggests that policymakers should pay attention to perceived convenience, transaction speed, subjective norm, and perceived usefulness to boost consumer attitude and intention to adopt QR-enabled mobile payment. This study is unique as it integrates the technology acceptance model and theory of reasoned action to investigate consumer behavior towards the adoption of QR code mobile payment. This study is also valuable as it examines the moderating effect of transaction speed between consumer attitude to accept QR code and their intention to adopt QR code-driven mobile payment and adds a new dimension to information system literature.

This study sets out to investigate the influence of organisational innovation (innovation speed, innovation quality and innovation quantity), extrinsic rewards, and intrinsic motivation on employee creativity and firm performance. We advance the body of knowledge on this subject and examined the moderating role of knowledge sharing between employee creativity and employee performance. Data was collected from employees working in Saudi public sector. For empirical findings structural equation modelling (SEM) was applied. The results show that employee creativity was jointly predicted by organisational innovation, extrinsic rewards and intrinsic rewards and explained