Academic literature on the topic 'Insights from GNH'

This article investigates the relationships among social network sites (SNSs) and social apps (SAPs) on consumers' online purchase attitude (OPA) with moderating effect of gender (GND). Structural equation modeling using SPSS and supporting tools was employed to represent the correlations among adopted constructs. To this end, the questionnaires were distributed to online shoppers from September 2017 and November 2017. The findings revealed the positive relationships of SNSs, i.e., Facebook, LinkedIn, Twitter, YouTube, and Pinterest on consumers' OPA. Second, it is found that SAPs, i.e., Whatsapp, Facebook messenger, Wechat, Instagram, and Snapchat have positive relationships on consumers' OPA. In addition, it is found that GND did not moderate the relationships among SNSs, SAPs, and consumers' OPA. This study furnishes insights how strategic managers can utilize such social media tools in marketing communications to empower consumers' OPA in today's era. Aside, study provides future studies for academicians and professionals.

The inference of gene networks from gene expression data is known as “reverse engineering.” Elucidating genetic networks from high-throughput microarray data in seed maturation and embryo formation in plants is crucial for storage and production of cereals for human beings. Delayed seed maturation and abnormal embryo formation during storage of cereal crops degrade the quality and quantity of food grains. In this chapter, the authors perform comparative gene analysis of results of different microarray experiments in different stages of embryogenesis in Arabidopsis thaliana, and to reconstruct Gene Networks (GNs) related to various stages of plant seed maturation using reverse engineering technique. They also biologically validate the results for developing embryogenesis network on Arabidopsis thaliana with GO and pathway enrichment analysis. The biological analysis shows that different genes are over-expressed during embryogenesis related with several KEGG metabolic pathways. The large-scale microarray datasets of Arabidopsis thaliana for these genes involved in embryogenesis have been analysed in seed biology. The chapter also reveals new insight into the gene functional modules obtained from the Arabidopsis gene correlation networks in this dataset.

This chapter develops an elaborated Pragmatic Act Model (ePAM) and applies it to humorous interactions in students' text chats in a Nigerian university. The model draws insights from Giora's Graded Salience Hypothesis (GSH), Mey's Pragmatic Act theory and incorporates current issues in pragmatic theorising such as the dialectics between a priori and co-constructed, emergent intention. The data for the study is got from three departmental chat room interactions in Federal University of Technology, Akure. Four humour types are analysed: canned jokes, punning/wordplay, question and answer jokes, and hyperbole/overstatement. Similarly, five pragmatic acts are performed in the identified humour types, namely, satirising, eliciting laughter, electioneering, teasing and overstating. In each of the humour types, the pragmatic mechanism drawn upon to comprehend the joke and to perform the pragmatic acts is indicated. Overall, the chapter argues that the effective appreciation of any humour act would require a pragmatically and culturally enriched context.

Abstract The emerging sharing mobility systems are gaining increasing popularity because of the significant economical and environmental benefits. To facilitate the operation of sharing mobility systems, many studies are conducted to analyze and predict users’ travel behaviors. However, most research focuses on investigating every station’s usage and demand; therefore, insight into the user behavior and travel demand between stations from origin to destination is little known. Aiming to better understand the factors that would influence origin-destination travel demand, we present a complex ne