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on Industrial Organization |
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Issue of 2014‒06‒28
two papers chosen by |
| By: | Li, Chenguang; Volpe, Richard |
| Abstract: | This study explores the strategic pricing behaviors across retail chains for produce products. We adopt a Panel-VAR model to identify the driving factors of retail price variation and find that retail price history, competition, product cost are among the key drivers of retail price change. Forecast Error Variance Decomposition (FEVD) is used to quantify the relative impact of driving factors to retail price changes and show how they affect prices differently across retail chains. We also find that higher responsiveness to competition may indicate superior management ability in price setting that associates with better profitability in practice. |
| Keywords: | Retail Pricing Strategy, Price Driver, Panel-VAR, Retail Competition, Demand and Price Analysis, Production Economics, Research Methods/ Statistical Methods, Q11, Q13, |
| Date: | 2014–04 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aesc14:169730&r=ind |
| By: | Takayuki Mizuno (National Institute of Informatics, Graduate School of Economics, University of Tokyo, The Canon Institute for Global Studies); Wataru Souma (College of Science and Technology, Nihon University); Tsutomu Watanabe (Graduate School of Economics, University of Tokyo, The Canon Institute for Global Studies) |
| Abstract: | In this paper, we investigate the structure and evolution of customer-supplier networks in Japan using a unique dataset that contains information on customer and supplier linkages for more than 500,000 incorporated non-financial firms for the five years from 2008 to 2012. We find, first, that the number of customer links is unequal across firms; the customer link distribution has a power-law tail with an exponent of unity (i.e., it follows Zipf’s law). We interpret this as implying that competition among firms to acquire new customers yields winners with a large number of customers, as well as losers with fewer customers. We also show that the shortest path length for any pair of firms is, on average, 4.3 links. Second, we find that link switching is relatively rare. Our estimates indicate that the survival rate per year for customer links is 92 percent and for supplier links 93 percent. Third and finally, we find that firm growth rates tend to be more highly correlated the closer two firms are to each other in a customer-supplier network (i.e., the smaller is the shortest path length for the two firms). This suggests that a non-negligible portion of fluctuations in firm growth stems from the propagation of microeconomic shocks – shocks affecting only a particular firm – through customer-supplier chains. |
| Keywords: | buyer-supplier networks; supply chains; input-output analysis; power-law distributions; firm dynamics |
| JEL: | L11 L14 C67 |
| Date: | 2014–01 |
| URL: | http://d.repec.org/n?u=RePEc:upd:utppwp:019&r=ind |