Prediction of Share of Visual Inventory Using Store Display, Channel, and Product Variables

Avil Terrance Saldanha; Rajendra Desai; Rekha Aranha

doi:10.32890/ijms2022.29.1.6

Authors

Avil Terrance Saldanha St. Joseph's Institute of Management, Bangalore, India
Rajendra Desai International School of Management Excellence, Bangalore, India
Rekha Aranha, Dr. School of Business and Management Christ (Deemed to be University), Bangalore, India

DOI:

https://doi.org/10.32890/ijms2022.29.1.6

Keywords:

Share of Visual Inventory, Inventory, Sales, Store Display

Abstract

The purpose of this study is to predict the share of visual inventory (SOVI), which is defined as the number of stock-keeping units (SKUs) of a company’s products, calculated as a percentage of the total SKUs on the display of all products. Research studies in the past have focused mainly on the impact of inventory, which includes back end and visual inventory, on sales but less attention has been given to the impact of SOVI on sales. To address this research gap, this study attempted to create an analytics model to predict SOVI at the category of soft drinks level using four predictor variables namely point of purchase display, channel/sub-channel, package group, product category, and derived variable gross national income (GNI). The results were encouraging confirming the effectiveness of such a model. The researchers utilized a data set collected over a period of 18 months (February 2016 to July 2017) by a soft drink firm headquartered in the United States. Based on the findings, it is suggested that this prediction model can be utilized by other researchers and practitioners to predict SOVI of other soft drinks, fast-moving consumer goods (FMCG), and food and beverage companies.

Downloads

Download data is not yet available.

References

Abratt, R., & Goodey, S. D. (1990). Unplanned buying and in-store stimuli in supermarkets. Managerial and Decision Economics, 11(2), 111-121.

Arcese, G., Flammini, S., Lucchetti, M. C., & Martucci, O. (2015). Evidence and experience of open sustainability innovation practices in the food sector. Sustainability, 7(7), 8067–8090.

Baker, R. A., & Urban, T. L. (1988). A deterministic inventory system with an inventory-level-dependent demand rate. Journal of the Operational Research Society, 39(9), 823–831.

Balakrishnan, A., Pangburn, M. S., & Stavrulaki, E. (2004). “Stack them high, let’em fly”: Lot-sizing policies when inventories stimulate demand. Management Science, 50(5), 630–644.

Bemmaor, A. C., & Mouchoux, D. (1991). Measuring the short-term effect of in-store promotion and retail advertising on brand sales: A factorial experiment. Journal of Marketing Research, 28(2), 202–214.

Bettman, J. R. (1979). An Information processing theory of consumer choice. Addison-Wesley Pub. Co.

Blackman, C. (2005). A healthy future for Europe’s food and drink sector? Foresight, 7(6), 8–23.

Cachon, G., & Terwiesch, C. (2008). Matching supply with demand (2nd ed.). McGraw-Hill Publishing.

Coelho, F. U. (2003). A sociedade limitada no novo Código Civil. Editora Saraiva.

Corsten, D., & Gruen, T. (2005). On shelf availability: An examination of the extent, the causes, and the efforts to address retail out-of-stocks. In Consumer Driven Electronic Transformation (pp. 131–149). Springer.

Dagnoli, J. (1987). Impulse governs shoppers. Advertising Age, 93.

Deichert, M., Ellenbecker, M., Pesarchick, L., Klehr, E., & Ziegler, K. (2006). Industry analysis: Soft drinks. Global Business Leadership Student Work. 2.

Deliya, M. M. M., & Parmar, M. B. J. (2012). Role of Packaging on Consumer Buying Behavior-Patan District. Global Journal of Management and Business Research, 12(10).

DiClemente, D. F., & Hantula, D. A. (2003). Applied behavioral economics and consumer choice. Journal of Economic Psychology, 24(5), 589–602.

Dr. Wieselhuber & Partner GmbH Unternehmensberatung. (2011). https://www.wieselhuber.de.

Dubé, J. P. (2004). Multiple discreteness and product differentiation: Demand for carbonated soft drinks. Marketing Science, 23(1), 66–81.

Dubelaar, C., Chow, G., & Larson, P. D. (2001). Relationships between inventory, sales and service in a retail chain store operation. International Journal of Physical Distribution & Logistics Management, 31(2), 96–108.

Ehrenthal, J. C., & Stölzle, W. (2013). An examination of the causes for retail stockouts. International Journal of Physical Distribution & Logistics Management, 43(1), 54–69.

Ettouzani, Y., Yates, N., & Mena, C. (2012). Examining retail on shelf availability: Promotional impact and a call for research. International Journal of Physical Distribution & Logistics Management, 42(3), 213–243.

Falcone, G., De Luca, A. I., Stillitano, T., Strano, A., Romeo, G., & Gulisano, G. (2016). Assessment of environmental and economic impacts of vine-growing combining life cycle assessment, life cycle costing and multicriterial analysis. Sustainability, 8(8), 793.

Fernie, J., & Grant, D. B. (2008). On-shelf availability: The case of a UK grocery retailer. The International Journal of Logistics Management, 19(3), 293–308.

Grover, R., & Srinivasan, V. (1992). Evaluating the multiple effects of retail promotions on brand loyal and brand switching segments. Journal of Marketing Research, 29(1), 76–89.

Gruen, T. W., & Corsten, D. (2007). A comprehensive guide to retail out-of-stock reduction in the fast moving consumer goods industry. Grocery Manufacturers Association (GMA), Food Marketing Institute (FMI), National Association of Chain Drug Stores (NACDS), The Procter & Gamble Company (P&G), the University of Colorado at Colorado Springs.

Halim, W. Z. W., & Good, L. K. (2005). Influence of store attributes on shopping intentions in factory outlet malls. International Journal of Management Studies, 12(2), 73–97.

Hise, R. T., Kelly, J. P., Gable, M., & McDonald, J. B. (1983). Factors affecting the performance of individual chain store units: An empirical analysis. Journal of Retailing, 59(2), 22–39.

Hsieh, C. C., Chang, Y. L., & Wu, C. H. (2014). Competitive pricing and ordering decisions in a multiple-channel supply chain. International Journal of Production Economics, 154, 156–165.

Hübner, A., & Schaal, K. (2017). Effect of replenishment and backroom on retail shelf-space planning. Business Research, 10(1), 123–156.

Ho, J. (2017, August 8). Red Ocean Solutions Retail Case: Why Share of Visual Inventory (SOVI) really matters for Sparkling Soft Drinks in Taiwan - Red Ocean Solutions. http://www.red-ocean.com/retail-case-why-share-of-visual-inventory-sovi-really-matters-to-you-here-it-is/

Inman, J. J., McAlister, L., & Hoyer, W. D. (1990). Promotion signal: Proxy for a price cut? Journal of consumer research, 17(1), 74–81. Retail Case: Why share of visual inventory (SOVI) really matters for sparkling soft drinks in Taiwan. Red Ocean Solutions. http://www.red-ocean.com/retail-case-why-share-of-visual-inventory-sovi-really-matters-to-you-here-it-is/

Koschat, M. A. (2008). Store inventory can affect demand: Empirical evidence from magazine retailing. Journal of Retailing, 84(2), 165–179.

Kuvykaite, R., Dovaliene, A., & Navickiene, L. (2009). Impact of package elements on consumer’s purchase decision. Economics and Management, (14), 441–447.

Larson, P. D., & DeMarais, R. A. (1999). Psychic stock: An independent variable category of inventory. International Journal of Physical Distribution & Logistics Management, 29(7-8), 495–507.

Levin, P. I., McLaughlin, C. P., Lamone, R. P., & Kottas, J. F. (1972). Contemporary policy for managing operating system. Production Operations Management, McGraw-Hill: New York, 373.

Mahalik, N. P., & Nambiar, A. N. (2010). Trends in food packaging and manufacturing systems and technology. Trends in Food Science & Technology, 21(3), 117–128.

Mandal, B. A., & Phaujdar, S. (1989). An inventory model for deteriorating items and stock-dependent consumption rate. Journal of the Operational Research Society, 40(5), 483–488.

Massoud, M. A., Fayad, R., El-Fadel, M., & Kamleh, R. (2010). Drivers, barriers and incentives to implementing environmental management systems in the food industry: A case of Lebanon. Journal of Cleaner Production, 18(3), 200–209.

Metzger, C., Meyer, J., Fleisch, E., & Tröster, G. (2007). Weight-Sensitive Foam to Monitor Product Availability on Retail Shelves. Lecture Notes in Computer Science, 268–279. https://doi.org/10.1007/978-3-540-72037-9_16

Musalem, A., Olivares, M., Bradlow, E. T., Terwiesch, C., & Corsten, D. (2010). Structural estimation of the effect of out-of-stocks. Management Science, 56(7), 1180–1197.

Orenstein, D. (1999). Sales data helps 7-Eleven maximize space, selection. Computerworld, 33(27), 38–39.

Padmanabhan, G., & Vrat, P. (1995). EOQ models for perishable items under stock dependent selling rate. European Journal of Operational Research, 86(2), 281–292.

Papakiriakopoulos, D., & Doukidis, G. (2011). Classification Performance for Making Decisions about Products Missing from the Shelf. Advances in Decision Sciences, 2011, 1–13. https://doi.org/10.1155/2011/515978

Papakiriakopoulos, D., Pramatari, K., & Doukidis, G. (2009). A decision support system for detecting products missing from the shelf based on heuristic rules. Decision Support Systems, 46(3), 685–694.

POPAI Europe. (1998). The POPAI Europe consumer buying habits study. Point-of-Purchase Advertising Institute. Co-ordination by Retail Marketing In-Store Services Limited. POPAI Europe.

Rubini, L., Motta, L., & Di Tommaso, M. R. (2013). Quality-based excellence and product-country image: Case studies on Italy and China in the beverage sector. Measuring Business Excellence, 17(2), 35–47.

Rus, E. C. R. (2009). ECR ePoS Step-by-Step Manual for FMCG Supplier. Russia: ECR Rus.

Sabir, L. B., & Farooquie, J. A. (2018). Effect of different dimensions of inventory management of fruits and vegetables on profitability of retail stores: An empirical study. Global Business Review, 19(1), 99–110.

Schary, P. B., & Becker, B. W. (1972). Distribution and final demand: The influence of availability. Review of Financial Economics, 8(1), 17.

Shruthi, G., Rao, B. D., & Devi, Y. L. (2016). Consumers perception towards Karimnagar Milk Producing Company Limited Milk and milk products. Research Journal of Agricultural Sciences, 7(4/5), 771–773.

Silayoi, P., & Speece, M. (2004). Packaging and purchase decisions: An exploratory study on the impact of involvement level and time pressure. British Food Journal, 106(8), 607–628.

Silver, E. A., & Peterson, R. (1985). Decision systems for inventory management and production planning (Vol. 18). John Wiley & Sons.

Ton, Z., & Raman, A. (2010). The effect of product variety and inventory levels on retail store sales: A longitudinal study. Production and Operations Management, 19(5), 546–560.

Urban, T. L. (1998). An inventory-theoretic approach to product assortment and shelf-space allocation. Journal of Retailing, 74(1), 15–35.

Van Woensel, T., van Donselaar, K., Broekmeulen, R., & Fransoo, J. (2007). Consumer responses to shelf out-of-tocks of perishable products. International Journal of Physical Distribution & Logistics Management, 37(9), 704–718.

Wansink, B. (1996). Can package size accelerate usage volume? Journal of Marketing, 60(3), 1–14.

Woodside, A. G., & Waddle, G. L. (1975). Sales effects of in-store advertising. Journal of Advertising Research, 15(3), 29–33.

Zinn, W., & Liu, P. C. (2008). A comparison of actual and intended consumer behavior in response to retail stockouts. Journal of Business Logistics, 29(2), 141–159.