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The purpose of this paper is to provide a comprehensive initial evaluation of the Super Bowl Indicator (SBI) from 1966 to 2015.

The authors evaluate the predictive ability of the SBI over two different time periods on four stock market indexes. Also, the authors compare the SBI predictive ability with other alternative indicators based on Super Bowl results as well as that of the January barometer (JB). As a robustness check, the authors examine whether the JB can predict Super Bowl outcomes. The authors use Granger causality to reduce the threat of spurious correlation.

The SBI surpasses the competition in both time periods, but it is evident that its predictive powers have waned since 1989. The authors find that the pre-Super Bowl January performance of the New York Stock Exchange is an impressive predictor of whether a team from the original National Football Conference won the big game between 1967 and 1988. Also, for the 1989-2016 period, the authors observe that the JB is a significant predictor whether the pre-game favorite wins or loses.

This study makes several contributions to the literature. The authors examine the SBI against four market indexes (Dow Jones Industrial Average, Standard and Poor’s 500 Index, and NASDAQ) with raw and point spread-adjusted scores. Testing a corollary to the SBI, this study is the first to examine the influence of the JB (sometimes called the January effect) on Super Bowl results.

The present paper aims to understand the underpinnings of the variations in brand level direct‐to‐consumer (DTC) advertising through a two‐part study. First, it seeks to examine the various influences on advertising intensity (operationalized by advertising to sales ratios) in the context of DTC advertising. Second, it aims to analyze how changes in share of voice impact changes in market share.

Data on brand level advertising as well as sales were collected from different government and industry sources. This is used to compute the ratio of DTC advertising to sales as well as changes in share of voice, market share and average drug prices. A log‐log model is used to find parameter estimates based on OLS regression.

Market share has a negative influence on the ratio of advertising to sales. Drugs which have a greater degree of innovation (as judged by the FDA) appear to spend more on DTC advertising relative to sales. The paper also finds that an increase in share of voice is not associated with increased average drug prices, but is related to a growth of market share because of a change in the share of total prescriptions dispensed.

The paper is one of the few to examine the factors influencing advertising to sales ratios in the context of DTC advertising. It is also one of the first to investigate the relationship of changes in the share of voice with changes in market share.

Although the PGA Tour provides a wide array of statistics, no single measure has successfully been able to predict a player's success during the season, either in terms of earnings per tournament or weighted average scores. The purpose of this paper is to present a metric that attempts to predict annual player rankings based on these two criteria.

The metric is computed from available statistics and attempts to encapsulate a player's unique strengths and weaknesses in a single number.

Deviations in rankings based on the metric are compared to those based on earnings per event and adjusted scoring averages. The results suggest that in addition to the average annual performance on the greens, the mix of tournaments played and the incidence of heroics or consistency have an important impact on the chances of success on the Tour.

The metric's predictions can be negatively affected if a golfer makes a large proportion of double eagles or double bogies.

The KCS (Key Criterion of Success) metric provides a quick route to succinctly summarizing a golfer's unique strengths and weaknesses in a single number.

Previous literature has mentioned the gap between statistics and success in golf. For the first time, possible reasons behind this divergence are identified in this paper.

The paper summarizes predictions about the use of franchising as an expansion strategy and examines them through an empirical investigation of a sample of restaurant franchisors. The restaurant industry is an appropriate field for such an investigation as franchising is extensively used in this sector. The subject of growth is also important from the consumer’s perspective because of the increased desire for convenience and uniformity. The results suggest that franchising is an effective strategy for store expansion. However, larger chains have a lower need to use franchising as a growth strategy, apparently because they have their own resources. The paper also shows that the chain’s mix of company owned and franchised outlets is likely to be influenced by its past growth pattern. The results indicate that a significant increase in the proportion of franchised outlets is unlikely for chains that already have a relatively high percentage of franchised outlets. This is ostensibly because synergistic benefits are achieved through having both company owned and franchised stores.