This research scrutinizes the synergism of virtual reality, the Internet, and television on credibility, memory, attitude, presence, and purchase intention. Respondents are randomly assigned to view two advertisements on the same or different media. This present study parses outs the relationship between immersive media and extant media in cross-media advertising.

Since more and more consumers rely on online consumer reviews in their purchase decision making, we have observed the emergence of empirical studies on online reviews in different contexts. Such studies look at various dimensions surrounding online reviews; nevertheless, none of them actually gives a more comprehensive picture as to the rating differences across online rating platforms and/or across time, let alone explains such differences. This study aims to address these understudied but managerially relevant issues. In our empirical study, we focus on hotel ratings across platforms and across time (i.e., across identified change point in time), and explain such differences by review text associating with the ratings. We investigated San Francisco hotels that were rated on both Tripadvisor and Expedia, and utilized the General Inquirer dictionary to identify the categories of words in a review. Regressions analyses were then conducted for the explanation of rating differences. We found that rating differences, in both the cross-platform and the longitudinal cases, are substantially associated with the number of words (in a negative relationship). Furthermore, word tags identified from the review text associated with ratings also explain the rating differences. To conclude, the research reveals that for a specific service provider, online ratings may vary significantly in both the cross-platform and the longitudinal senses. It demonstrates that adopting a systematic approach and utilizing an established semantic dictionary, information extracted from review text can substantially explain such differences.

The concept of „Sustainability‟ has become as major concern and it used by consumers and corporations to convey the concept of taking care of the environment. Environmental concern has led to sustainable consumption in a variety of product categories, such as electricity, textiles, apparel, food, and grocery products (Chan, 2001; Harrison, Newholm, & Shaw, 2005; Vermeir & Verbeke, 2006a, 2006b). Interest of the negative environmental impacts are rapidly increasing in present fashion business and consumer behavior has become a rising concern of the consumption and fashion supply chain to apply sustainable consumption (Birtwistle & Moore, 2007; Fineman, 2001). The environmental and social concern recognized in fashion industry from 1990‟s. However, the complexity of conceptual definition of sustainability and ecologically responsible consumer generates different and mistaken perception to consumer. In addition, in fashion industry, the terms of „eco-fashion‟, „environmentally friendly fashion‟,„green fashion‟, „ethical fashion‟, and „sustainable fashion‟ are frequently used interchangeably to describe the same concept. These interchangeable terminology is leading to confusion of the readers by the non-unified terminology (Choi et al., 2012). Also, consumers seem to have narrow scope and little understanding of sustainable fashion. In general, consumers focuses on environmental aspect not the wide-range of complexity of environment, social, and economical concern (Cervellon, Hjerth, Ricard, & Carey, 2010). The growing number of fashion brands are leveraging on green branding initiatives. Green marketing is increasing rapidly in corporate aspects and for a consumer perspective, global consumers are recognizing a personal accountability to take responsibility for social and environmental issues. Despite the fact many of individuals‟ willingness to purchase green products has increased in the last few years, however, there is limited studies suggest that purchase of green or sustainable products. Consumer research on sustainable fashion has mainly focused on consumer behaviors towards sustainable fashion products (SFPs); however, relevant studies that examined the whole process of the predicting proenvironmental behavior cross nationally value and the eWOM are still scarce. The purposes of research model are 1) to identify the determinants of eWOM intention on consumers' purchase intentions, 2) to examine the information adoption process as precursors of purchase intention of sustainable fashion, and 3) to testify different message types effects to information adoption process.

Genetic markers are tools that can facilitate molecular breeding, even in species lacking genomic resources. An important class of genetic markers is those based on orthologous genes, because they can guide hypotheses about conserved gene function. For under-studied species a key bottleneck in gene-based marker development is the need to develop molecular tools that reliably access genes with orthology to the genomes of well-characterized reference species. Here we report an efficient platform for designing cross-species gene-derived markers in legumes. The automated platform, named CSGM Designer (URL: http://tgil.donga.ac.kr/CSGMdesigner), facilitates rapid and systematic design of cross-species genic markers. The underlying database is composed of genome data from five legume species whose genomes are substantially characterized. Use of CSGM designer is enhanced by graphical displays of query results, which we describe as “circular viewer” and “search-within-results” functions. CSGM platform provides a virtual PCR representation, called eHT-PCR, that predicts the specificity of each primer pair simultaneously in multiple genomes. CSGM Designer output was experimentally validated for the amplification of orthologous genes using 16 genotypes representing 12 crop and model legume species, distributed among the galegoid and phaseoloid clades. Successful cross-species amplification was obtained for 85.3% of PCR primer combinations. CSGM Designer spans the divide between well-characterized crop and model legume species and their less well-characterized relatives. The outcome is PCR primers that target highly conserved genes for polymorphism discovery, enabling functional inferences and ultimately facilitating trait-associated molecular breeding.