Technology Addictions and Technostress: An Examination of Hong Kong and the U.S.

In today’s technology-centric world, people are becoming increasingly dependent on the Internet. The most common use of the Internet is through social media, which are used to communicate, share, collaborate, and connect. However, continued usage of a hedonic system can be linked with compulsion or addiction. Since problematic usage/behaviors can lead to negative outcomes, this manuscript aims to determine differential effects of Internet and social media addictions on social media-related technostress. This is examined in two different cultures: the U.S. and Hong Kong. The results support the association between Internet and social media addictions with increases in social media-related technostress. Additionally, these effects are moderated by culture. Implications for research and practice are discussed along with future directions for this stream

The role of memorable experience and emotional intelligence in senior customer loyalty to geriatric hotels

Drawing on service encounters and experiential marketing theories, this study examined the relationship between geriatric service, memorable experience, emotional intelligence, and senior customers\u27 attitudinal and behavioural responses. The research was conducted at geriatric hotels in Portugal. The results showed that, compared to impersonal encounters, employee service has a significantly greater effect on customer satisfaction, memorable experience, and customer loyalty. In addition, customers\u27 memorable experiences mediated the relationship between different service encounters and organisational outcomes. However, customers’ emotional intelligence had minimal effects on these relationships. The discussion and implications of these findings are offered to researchers and practitioners

Benchmarked approaches for reconstruction of in vitro cell lineages and in silico models of C. elegans and M. musculus developmental trees.

The recent advent of CRISPR and other molecular tools enabled the reconstruction of cell lineages based on induced DNA mutations and promises to solve the ones of more complex organisms. To date, no lineage reconstruction algorithms have been rigorously examined for their performance and robustness across dataset types and number of cells. To benchmark such methods, we decided to organize a DREAM challenge using in vitro experimental intMEMOIR recordings and in silico data for a C. elegans lineage tree of about 1,000 cells and a Mus musculus tree of 10,000 cells. Some of the 22 approaches submitted had excellent performance, but structural features of the trees prevented optimal reconstructions. Using smaller sub-trees as training sets proved to be a good approach for tuning algorithms to reconstruct larger trees. The simulation and reconstruction methods here generated delineate a potential way forward for solving larger cell lineage trees such as in mouse