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There are two basic theoretical views of how advertising affects competition. One school of thought suggests that advertising decreases competition. Kaldor (1950) argued that through economies of scale in advertising, advertising increases market concentration. Also, Bain (1956) suggested that advertising causes strong product differentiation and brand loyalty, which are barriers to entry and will lead to higher concentration.

The specific problem this research addresses is whether cultural differences, national or organizational, impact how effectively the continuous improvement process is received within the supply chain in order to improve supplier performance. The paper aims to discuss these issues.

The research design used a mixed methods approach, combining quantitative and qualitative research.

The research found that Canada was most receptive to continuous improvement, with China being the least receptive. The study found that organizational culture was more influential than national culture. Isomorphism and benchmarking is driving continuous-improvement language and methods to be more universally known within business. Business and management practices appear to take precedence in driving change within organizations.

The sample size and countries involved was very small and limited to key medium sized distributed power company (MSDPC) suppliers. This limited diversity and may have introduced supplier selection bias, as well as survey response bias.

This research concludes that organizational culture is more dominant over national culture and the influence of leadership within the organization drives the impact of continuous improvement.

With isomorphism and the fact that businesses want to be successful, continuous improvement language and methods are becoming more universally known. Business and management practices are now taking precedence in driving change within organizations. Organizational culture is now more influential than national culture.

The goal of the study is to examine the effects of news sentiment and topics dominating in the news field prior to the initial public offering (IPO) on the IPO underpricing.

The authors’ approach has several steps. The first is textual analysis. To detect the dominating topics in the news, the authors use Latent Dirichlet allocation. The authors use bidirectional encoder representations from transformers (BERT) pretrained on financial news corpus to evaluate the tonality of articles. The second is evaluation of feature importance. To this end, a linear regression with robust estimators and Classification and Regression Tree and Random Forest are used. The third is data. The text data consists of 345,731 news articles from Thomson Reuters related to the USA in the date range from 1 January 2011 to 31 May 2018. The data contains all the possible topics from the website, excluding anything related to sports. The sample of 386 initial public offerings completed in the USA from 1 January 2011 to 31 May 2018 was collected from Bloomberg Database.

The authors found that sentiment of the media regarding the companies going public influences IPO underpricing. Some topics, namely, the climate change and environmental policies and the trade war between the US and China, have influence on IPO underpricing if they appear in the media prior to the IPO day.

The puzzle of IPO underpricing is studied from the point of Narrative Economics theory for the first time. While most of the works cover only some specific news segment, we use Thomson Reuters news aggregator, which uses such sources The New York Post, CNN, Fox, Atlantic, The Washington Post ? Buzzfeed. To evaluate the sentiment of the articles, a state-of-the-art approach BERT is used. The hypothesis that some common narratives or topics in the public discussion may impose influence on such example of biased behaviour like IPO underpricing has also found confirmation.