DETERMINANTS OF RETAIL PRICE AND SALES VOLUME OF CATFISH PRODUCTS IN THE UNITED STATES: AN APPLICATION OF RETAIL SCANNER DATA
Bibliographic record
Abstract
Abstract Catfish market research is important in terms of the viability and sustainability of the catfish aquaculture industry in the U.S. Analysis of market trends, retail level price and sales volume have particular importance in the context of the industry's efforts to promote and market their products. Using retail level scanner data, this study examined the market trends of different catfish product forms. The study also investigated the factors affecting prices and sales for frozen catfish products. The present study is a pioneer in using market/city level retail scanner data to study marketing behavior of catfish products under different product categories (i.e., breaded, unbreaded and entrees). The results of the study highlight a need for a non-price competition strategy for catfish retail market. This includes several activities that attempt to provide added value or incentives to consumers, wholesalers, retailers, or other organizational customers to stimulate immediate sales. Keywords: catfishmarket trendsretail scanner datasales and price response model ACKNOWLEDGMENTS The authors gratefully acknowledge the able research support provided by Mr. Prasanna Surathkal, including his critical help in organizing the data. The findings, opinions, and recommendations expressed are those of the authors and not necessarily those of the Southern Regional Aquaculture Center, the Mississippi Agricultural and Forestry Experiment Station, or the U.S. Department of Agriculture. Notes Note: Figures in parenthesis show % change in prices over 2005–2006. X = represents interaction. ***Significant at 1%, **significant at 5%, *significant at 10%. X = represents interaction. ***Significant at 1%, **significant at 5%, *significant at 10%. ***Significant at 1%, **significant at 5%, *significant at 10%. Note: Elasticities were calculated from significant coefficients of prices of different fish and interaction of prices and region for unbreaded catfish sales model. The term catfish used in this article refers to Ictalurus species, which includes channel catfish and its hybrids. A.C. Nielsen Inc. collects weekly store-level scanner data at the market level (52 markets in the U.S.) and national level. However, national-level data is not an aggregate of the data from the 52 individual markets and includes few more markets than those for which individual market-level data are provided. We used market level data for econometric analysis. But, for brevity in presentation and for space consideration, we have reported the trends at national level only. Wal-Mart has recently started sharing scanner data with A.C. Nielsen Inc in a limited scale for 10 U.S. markets. The sampling framework of the 10 markets where World-Mart participates and that of the 52 markets data we used in this paper are different and are not compatible. A similar approach has also been used at other levels in the seafood supply chain. This includes studies at the harvest level (Carroll et al., Citation2001; McConnell & Strand, Citation2000) and the wholesale level (Asche & Guillen, Citation2012). These studies have found that the attributes and their values differ at different levels in the chain. If the series are integrated of same order, they can be co-integrated. Since dependent variables are price and sales volumes, therefore, we did not test the order of integration and hence co-integration with other variables. The retail price model used in this study shows retailers' pricing behavior and its does not include quantities of seafood sales as explanatory variables. We, therefore, cannot estimate own- and cross-price elasticties directly from the retail price model. In the scanner data a product type is denoted as 'regular' if specific 'type' information is not mentioned in the product description. For example, "CTL BR CTF FLT FZ 12 OZ" is a store brand 12 oz regular catfish frozen fillet; "CTL BR CTF FLT BL SL FZ 32 OZ" is a store brand 32 oz boneless-skinless catfish frozen fillet. Singh et al. (2014) used the geographical disaggregation at the U.S. census division (9 in number) level; whereas this paper uses disaggregation at the U.S. census regions level (4 in number). In the scanner data a product type is denoted as 'regular' if specific 'type' information is not mentioned in the product description. For example, "CTL BR CTF NGT BR 80 OZ" is a store brand 80 oz catfish frozen nugget with regular breading; "CTL BR CTF STR NGT BR 13 OZ" is a store brand 13 oz catfish frozen nugget with cornmeal breading.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".