Applying the Theory of Planned Behavior (TPB), this study provided an enhanced understanding of the intentions, motivations, and beliefs about blood donation among the young generation in the U.S. An online quantitative Qualtrics survey was administered at a large public university to collect data from the campus community, with participants aged 18 to 39 (N = 954). Data were collected via an adapted questionnaire on the TPB constructs: attitudes towards blood donation, subjective norms of peers and loved ones, perceived control of behavior, and intention to donate blood. Univariate, bivariate and multivariate analysis were employed to explore the associations of these constructs. Primary findings revealed that the intention to donate blood regularly was positively associated with social norms. Secondary findings suggested that a hierarchical multiple regression analysis provided strong support for the role of social media apps as a major determinant of motivations for donating blood, with TPB constructs accounting for 34% of the variance. Tertiary findings from this study derived Cronbach’s $\alpha$ = 0.555, indicating a poor level of internal consistency. The generalizability of the results in this study could be verified by increasing the number of questions in each construct and conducting future studies at larger universities and blood centers.

Recently, the food industry has faced numerous challenges such as rising demand, climate change, and the imperative to improve the quality and safety of food products. This research investigated the role of Artificial intelligence (AI) and the Internet of Things (IoT) in managing food supply and distribution projects. The main objective of this study was to analyze how these technologies could be implemented to optimize the process of supply chain and enhance the efficiency and effectiveness in food distribution. Successful cases of technological implementation in the food industry highlighted the associated benefits and challenges of adopting AI and IoT. Ten critical factors influencing the roles of AI and IoT in food supply and distribution were identified and considered in the current study. Following a systematic coding process through meta-synthesis, concepts related to each factor were extracted from previous studies. Finally, expert opinions were gathered by a questionnaire survey whereas the Kappa index was calculated using SPSS software. The obtained value of 0.78 indicated a desirable agreement in the perspectives between researchers and experts. By leveraging AI, organizations are able to analyze big data, predict demand, optimize inventory, and reduce resource waste. Likewise, IoT, through connecting devices and sensors to the network, enables the collection of real-time data, which assists managers in making better decisions regarding the timing and location of food distribution.