Effects of Atmospherics on Revenue Generation in Small Business Restaurants
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Bibliographic record
Abstract
ABSTRACT Atmospheric variables such as interior layout and music stimulate behavioral responses from customers in service settings. This study examined the extent to which these cues affect revenue generation in 153 full-service small business restaurants. The results demonstrate that both interior layout and music are significant predictors of revenue generation and thus they may offer an important collateral strategy to restaurant revenue management. INTRODUCTION An important segment of the economy, full-service restaurants, had sales of $144.6 billion in 2002 (U.S. Census Bureau, 2002). With a continuing rise in American meals being eaten away from home, these sales are expected to grow (National Restaurant Association, 2005). Among restaurants, seven out of ten are single-unit; i.e., independent operations (National Restaurant Association, 2005). Kimes, Chase, Choi, Lee, and Ngonzi (1998) developed a framework for applying revenue management in restaurants. Conceived in the airline industry as yield management, revenue management involves the management of demand and pricing in order to maximize sales revenues (Cross, 1997). It has been shown to increase sales revenue by as much as 7% for airlines (Marraorstein, Rossomme, & Sarel, 2003). Revenue management is now used in a range of industries such as communication, hotels, and shipping (McGill & Van Ryzin, 1999). The restaurant revenue management framework developed by Kimes et al. (1998) suggests demand-managing strategies that present customers with cues to affect revenue generation. Indeed, case study evidence shows that restaurant revenue management, used in conjunction with adjustments to table top mix (e.g., a four-top is a table that seats four), increases sales by 5% (Kimes, 2004). Atmospheric cues are a potential collateral strategy to restaurant revenue management. Based on a stimulus-organism-response (SOR) framework, atmospherics involves the use of stimuli such as interior layout and music to elicit behavioral responses. For example, studies show that atmospheric cues can result in faster shopping traffic flow and an increase in the time and money customers spend in a retail store (Areni & Kim, 1993; Milliman, 1982). Atmospheric stimuli such as interior layout and music help to create ambiance in a restaurant setting. However, there is no large-sample empirical evidence on the effects of these variables on revenue generation in small business restaurants. Evidence of the effects of atmospheric cues would extend the restaurant revenue management literature and contribute to restaurant managers' understanding of collateral revenue management practices. Thus, the purpose of this study was to examine whether the use of atmospheric cues, such as interior layout and music, in small business restaurants has significant effects on revenue generation. In the following section, literatures on restaurant revenue management and atmospherics are reviewed to derive a hypothesis. The hypothesis was tested with a survey of small business restaurant managers. Results are presented, and implications for revenue management in small business restaurants are discussed. LITERATURE REVIEW Revenue management manages demand in order to maximize sales revenues from a business's existing capacity (Cross, 1997; Kimes & Chase, 1998). There are several conditions that facilitate the practice of revenue management in a business. First, the outputs of the business should be perishable (Weigand, 1999). For example, airlines have a perishable product (i.e., a flight on a given date and time to a given destination flies only once). Second, a business should have primarily fixed capacity (Weatherford & Bodily, 1992). For example, airlines have fixed capacity in their investment in a fleet of airplanes. Given fixed capacity, one means that any business can use to seek to improve its profitability is to increase the amount of revenue that is generated from that fixed capacity. …
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it