Comparative Advertising Wars: An Historical Analysis of Their Causes and Consequences

This historical study contributes to the extensive literature on comparative advertising by examining the causes and consequences of comparative advertising wars; that is, when one advertiser responds to a direct or implied attack by another advertiser. Primary and secondary sources consist of articles published in historic and contemporary marketing and advertising trade journals, such as Printers’ Ink, Advertising & Selling, and Advertising Age. The findings reveal that well-publicized advertising wars occurred frequently between major U.S. advertisers throughout the twentieth century and into the twenty-first, and that they most often occurred in product and service markets characterized by intense competition. Many, if not most, advertisers’ principal motive for responding to a comparative advertising attack has been emotional rather than rational. The findings also reveal that advertising wars often became increasingly hostile, leading to negative consequences for all combatants, as well as a broad and negative social consequence in the form of potentially misleading advertising.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost