The Role of Financial Services Advertising on Investors\u27 Decision-Making

The present study assesses the effect of financial services advertising on investors’ decision-making by adopting a two-sided approach: a stimulus-side analysis to document the nature and prevalence of advertising strategies and advertising disclosures being used and a response-side investigation to examine the investors’ processing of and receptiveness to financial services advertising. By performing a content analysis of recently published financial services magazine advertisements, this study provides a contemporary look at whether and how financial services companies inform, persuade, and communicate with average investors. Results from this content analysis method is also used as a foundation to help design realistic test ads in the subsequent experimental design as a response-side approach. Combined with stimulus-side data, a between-group experimental design allows an empirical test of how the interaction between investors’ exposures to different advertising practices (i.e., advertising strategies and advertising disclosures) and individual regulatory focus might affect the ways investors perceive and evaluate the advertised financial product. In this stage, the likely processing and persuasive differences between advertising strategies and advertising disclosures and the potential moderating role of investors’ regulatory focus form the basis of the response-side approach to complement the content analysis phase. Results from the content analysis show that financial services companies increased informational advertising strategies and presented more advertising information during the three-year (2007-2009) period of interest. Findings indicate that financial services companies might play a role in enhancing the role of communication, information, and advertising in the marketplace for financial literacy. However, in order to adequately evaluate the range of investor’s response to advertising strategies and advertising disclosures, this study employs a two advertising strategies (information versus transformational) x two advertising disclosures (complete disclosure versus non-disclosure) x two regulatory focus (promotion-focused versus prevention-focused) between-subject, randomized, experimental design. Findings from the experimental design reveal that investors’ financial decision-making may be affected by internal characteristics (i.e., regulatory focus) as well as external information (i.e., advertising strategies and advertising disclosures). Especially, regulatory focus was found to be function as a moderating variable that can influence the direction and strength of relationship between different financial services advertising practices and the outcome variables of financial decision-making such as risk perceptions, product attitudes, and purchase intentions. Finally, theoretical, managerial, and policy implications are discussed and opportunities for the future research are identified

Human Facial Expression Recognition Using Fisher Independent Component Analysis and Hidden Markov Model

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The effects of citizen knowledge on the effectiveness of government communications on nuclear energy policy in south korea

By analyzing survey data on nuclear energy policy in South Korea, this study examined the influence of citizens’ knowledge on the perceptions of and attitudes to government communication initiatives that are characterized by symmetry and transparency, and their effects in developing institutional legitimacy and policy acceptance. The findings indicate that symmetrical and transparent communication are involved in forming institutional legitimacy and policy acceptance of government decisions on the controversial topic of nuclear energy, but the process differs de-pending on citizens’ knowledge of the topic. Well-informed citizens who used reasoning were more likely than others to respond positively to symmetrical and transparent communication, which shaped their support for institutional legitimacy and policy acceptance on nuclear energy policy issues. These findings provide some of the first empirical evidence of the effectiveness of government communication.1

Unsupervised Text Embedding Space Generation Using Generative Adversarial Networks for Text Synthesis

Generative Adversarial Networks (GAN) is a model for data synthesis, which creates plausible data through the competition of generator and discriminator. Although GAN application to image synthesis is extensively studied, it has inherent limitations to natural language generation. Because natural language is composed of discrete tokens, a generator has difficulty updating its gradient through backpropagation; therefore, most text-GAN studies generate sentences starting with a random token based on a reward system. Thus, the generators of previous studies are pre-trained in an autoregressive way before adversarial training, causing data memorization that synthesized sentences reproduce the training data. In this paper, we synthesize sentences using a framework similar to the original GAN. More specifically, we propose Text Embedding Space Generative Adversarial Networks (TESGAN) which generate continuous text embedding spaces instead of discrete tokens to solve the gradient backpropagation problem. Furthermore, TESGAN conducts unsupervised learning which does not directly refer to the text of the training data to overcome the data memorization issue. By adopting this novel method, TESGAN can synthesize new sentences, showing the potential of unsupervised learning for text synthesis. We expect to see extended research combining Large Language Models with a new perspective of viewing text as an continuous space