• Title/Summary/Keyword: 공적 실험 상황

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Revisiting Effects of Endorsers' Race on Attitudes Toward Ad and Brand (광고 모델의 인종이 광고와 브랜드 태도형성에 미치는 영향에 대한 고찰)

  • Lee, Eunsun;Kim, Yeo Jung;Ahn, Jungsun
    • The Journal of the Korea Contents Association
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    • v.14 no.8
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    • pp.110-121
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    • 2014
  • As the Korean market is becoming increasingly diverse, it is imperative that marketers targeting the Korean market understand the consumers with various racial and cultural backgrounds. The current study investigated the effects of the endorser race (White vs. Black) on the attitudes toward the ad and brand while varying the experimental context (private vs. public) and product type (high involvement-rational vs. low involvement-emotional) with White participants. Impression management was included as a covariate. The results showed that when the endorser was White and the product was an automobile, participants indicated more positive attitudes toward the ad in the private context than in the public context. When the endorser was Black, the context had no significant effects on the attitudes. The implications of these findings for the Korean market are discussed.

The Impact of Voucher Support on Economic Performance for AI Companies: Policy Effectiveness Analysis using PSM-DID Model (AI 중소기업 바우처 지원이 기업성과에 미치는 영향: PSM-DID 결합모형을 활용한 정책효과 분석)

  • SeokWon, Choi;JooYeon, Lee
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.1
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    • pp.57-69
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    • 2023
  • In a situation where digital transformation using artificial intelligence is active around the world, the growth of domestic AI companies or AI industrial ecosystems is slow. Where a large amount of government funds related to AI are being invested to overcome the difficult economic situation, systematic research on the effect is insufficient. So, this study aimed to examine the policy effectiveness of the government artificial intelligence solution voucher support project for small and medium-sized enterprises (SMEs) using Propensity Score Matching (PSM) and Difference-in-Differences (DID) on the financial performance of beneficiary companies. For empirical analysis, PSM-DID analysis was performed using sales performance since 2019 for 461 companies with a history of voucher support among the AI SMEs data released by the National IT Industry Promotion Agency. As a result of the analysis, the beneficiary companies' asset growth, salary, and R&D expenses increased overall after government support, and no significant contribution could be confirmed in terms of profits. This study suggests that the voucher policy business directly contributed to the company's growth in the short term, but it requires a certain period of time to generate profits.