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Christine Eckert

Abstract

Price differentiation has long been recognized as a strategy that companies can use to increase profits when consumers’ tastes and valuations of a good price vary. Companies engaging in price differentiation have the opportunity to increase profits considerably compared to those which use a uniform pricing strategy. Accordingly, it should be beneficial for companies to exploit the possibility of charging different prices in online and offline channels as they offer different shopping benefits and are differently valued by consumers. nevertheless, it can be observed that some multi-channel retailers prefer to charge uniform prices in online and offline channels. They argue for consistent prices across distribution channels to maintain a strong brand - and because varying prices may lead to customers’ confusion, anger, irritation and perceptions of price unfairness.

Open access

Ede Lázár

References Akerlof, G. A. (1970). The market for ‘lemons’: qualitative uncertainty and the market mechanism. Quarterly Journal of Economics 84 (3): 488-500. Berry, S.; J. Levinsohn; A. Pakes (1995). Automobile prices in market equilibrium. Econometrica 63 (4): 841-890. Berry, S.; J. Levinsohn; A. Pakes (1999). Voluntary export restraints on automobiles: evaluating a strategic trade policy. American Economic Review 89 (3): 400-430. Chatterjee S.; Y. S. Kang; D. P. Mishra (2005). Market signals and

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Iwona Dittmann

Macroeconomic Perspective , Springer Berlin Heidelberg B ełej M., 2012, Dynamika zmian cen nieruchomości w aspekcie teorii przejść nieciągłych (Dynamics of Changes in Property Prices in Aspects of Discountionous Chane Theory) , Studia i Materiały Towarzystwa Naukowego Nieruchomości, vol. 20, nr 1, Olsztyn, pp.17-28 B ełej M., 2013, Catastrophe Theory in Explaining Price Dynamics on the Real Estate Market , Real Estate Management and Valuation, Volume 21, Issue 3, Pages 51-61, DOI 10.2478/remav-2013-0026 B ełej M., K ulesza S., 2014, Similarities in

Open access

Justyna Tanaś

References BOURASSA, S.C., HOESLI, M., SUN, J., 2006, A Simple Alternative House Price Index Method , Journal of Housing Economics, vol. 15, s. 80-97. CASE, B., WACHTER, S., 2005, Residential Real Estate Price Indices as Financial Soundness Indicators: Methodological Issues , BIS Paper, no 21, s. 197-211. GAWRON, H., 2012, Wpływ cech fizycznych działek na ceny gruntów budowlanych w aglomeracji miejskiej (na przykładzie aglomeracji poznańskiej ), in: ŹRÓBEK, S., (red.), Studia i materiały Towarzystwa

Open access

Iwona Foryś

References Aczel, A. A. (2006). Statystyka w zarządzaniu , Warszawa: PWN. Bailey, M. J., Muth, R.F, Nurse, H. O. (1963). A Regression Method for Real Estate Price Index Construction. Journal of American Statistical Association , No. 58. Case, K. E., Shiller, R. J. (1990). Forecasting Prices and Excess Returns in The Housng Market. National Bureau of Economic Research, Working Paper No. 3368, Cambrige. Crone, T.M, Voith, R. P. (1992). Estimating House

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Jacek Zyga

PAS Report, Warszawa. S kowron A., 1990, The rough sets theory and evidence theory , Fundamenta Informaticae, pp. 245-262. Rejestr Cen i Wartości prowadzony przez Urząd Miasta w Lublinie (Register of Real Estate Prices and Values kept by the Lublin City Office).

Open access

Ioan Lucian Grigorescu

Abstract

Competitive advantage is a difference in relative prices or the relative costs and it results from differences in their work done. These differences may occur in two different ways, namely either the organization performs better the same types of activities, or it chooses different types of activities. To establish whether between an organization and other competitors in the same industry there are differences in terms of relative prices and relative costs, it is recommended to make use of Porter's value chain, the more so as these differences are determined by the activities of the organization. Value chain plays an important role in the diagnosis of an organization's competitive advantage because through it we can get an insight into the mode of action of costs and the influences they have on the strategy that the organization has taken. Also, through the value chain there can be identified the potential sources of differentiation of products or services offered by the organization.

Open access

Abdullah A. Aldousari and Ismail M. Elsayed

of Retailing and Consumer Services, Vol. 38, pp. 12-23. Meyer-Waarden, L. (2008), “The Influence of Loyalty Programme Membership on Customer Purchase Behavior”, European Journal of Marketing, Vol. 42, No. 1-2, pp. 87-114. Minnema, A., Bijmolt, T.H.A. and Non, M.C. (2017), “The Impact of Instant Reward\program and Bonus Premiums on Consumer Purchase Behavior”, International Journal of Research in Marketing, Vol. 34, No. 1, pp. 194-211. Moore, M. and Carpenter, J. (2006), “The Effect of Price as a Marketplace Cue on Retail Patronage”, Journal of

Open access

Arkadiusz Gendek and Tomasz Nurek

Abstract

The main aim of the work is to assess physical parameters of forest woodchips and their impact on the prices achieved by the supplier in transactions with a power plant. During fragmentation of logging residue, high content of green matter and contaminants negatively impacts the quality parameters that serve as basis for settlements. The analysis concerns data on the main parameters - water content, fuel value, sulphur and ash content - from 252 days of deliveries of forest chips to a power plant. The deliveries were realised from forested areas on an average about 340 km from the plant. Average water content and the resultant fuel value of forest chips was within 27-47% and 8.7-12.9 GJ×Mg-1 (appropriately), respectively. They depend on the month in which they are delivered to the power plant. The threshold values for the above-mentioned parameters are set by the plant at a real level and the suppliers have no problems with meeting them. The parameter that is most frequently exceeded is ash content (11.5% of cases). The settlement system does not differentiate on the basis of the transport distance but gives possibility to lower the settlement price when the quality parameters are not met but provides no reward for deliveries with parameters better than the average ones. On the basis of results obtained, it was calculated that average annual settlement price is lower than the contract price by about 0.20 PLN×GJ-1, which in case of the analysed company may translate into an average daily loss of about 700 PLN.