Nicholls State University

About: Nicholls State University is a education organization based out in Thibodaux, Louisiana, United States. It is known for research contribution in the topics: Population & The Internet. The organization has 456 authors who have published 795 publications receiving 20031 citations.

An Exploration of Rule Configuration Effects on the Ethical Decision Processes of Advertising Professionals

Abstract: This study explores the ethical perceptions of advertising professionals regarding two child-oriented television advertising issues: deceptive messages and host selling. Differences in ethical evaluative and decision processes are investigated for both issues, using two evaluative rules. The results indicate that variations in advertisers’ ethical judgments and ethical intentions are affected by the type of rule(s) used during the evaluative process, and by the degree to which the rules are embraced. The article concludes with recommendations for advertising management and implications for future research.

A Novel Bioinspired Multiobjective Optimization Algorithm for Designing Wireless Sensor Networks in the Internet of Things

Abstract: The design of wireless sensor networks (WSNs) in the Internet of Things (IoT) faces many new challenges that must be addressed through an optimization of multiple design objectives. Therefore, multiobjective optimization is an important research topic in this field. In this paper, we develop a new efficient multiobjective optimization algorithm based on the chaotic ant swarm (CAS). Unlike the ant colony optimization (ACO) algorithm, CAS takes advantage of both the chaotic behavior of a single ant and the self-organization behavior of the ant colony. We first describe the CAS and its nonlinear dynamic model and then extend it to a multiobjective optimizer. Specifically, we first adopt the concepts of “nondominated sorting” and “crowding distance” to allow the algorithm to obtain the true or near optimum. Next, we redefine the rule of “neighbor” selection for each individual (ant) to enable the algorithm to converge and to distribute the solutions evenly. Also, we collect the current best individuals within each generation and employ the “archive-based” approach to expedite the convergence of the algorithm. The numerical experiments show that the proposed algorithm outperforms two leading algorithms on most well-known test instances in terms of Generational Distance, Error Ratio, and Spacing.

Pay, productivity and aging in Major League Baseball

Abstract: Using panels of player pay and performance from Major League Baseball (MLB), we examine trends in player productivity and salaries as players age. Pooling players of all ability levels leads to a systematic bias in regression coefficients. After addressing this problem by dividing players into talent quintiles, we find that the best players peak about 2 years later than marginal players, and development and depreciation of performance appear to be more pronounced for players with the highest ability levels. Within-career variation, however, is less pronounced than between-player variation, and the performance level of players within a given quintile will typically remain lower than the talent level for rookies in the next higher quintile. We also find preliminary evidence that free agents are paid proportionately to their production at all ability levels, whereas young players’ salaries are suppressed by similar amounts.

What Drives Consumers to Click on Social Media Ads? The Roles of Content, Media, and Individual Factors

Abstract: Social media has become an ever-expanding realm as more and more consumers are spending tremendous amount of time on it. Businesses are taking advantage of this channel to promote their products and services through social media advertising. In particular, display ads have a prominent presence accompanying social media feeds. This study aims to develop an understanding of the multi-faceted factors that drive consumers to respond to social media advertising. The roles of content, media, and individual factors are examined. A research model is developed and tested using data collected from an online-survey of 613 social media users. Our results show compelling evidence that the effectiveness of display ads on social media is driven by ad content, ad-media congruity, and consumers' individual factors. Practical and theoretical implications are discussed.