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Who has the final say?: Market power versus price discovery in China's sugar spot and futures markets

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Author Info

  • Ling-Yun He
  • Wen-Si Xe

Abstract

Purpose – The purpose of this paper is to investigate the effects of network strength, transaction-specific investments and inter-personal trust on business relationship satisfaction for small-and-medium-sized enterprises (SMEs) involved in agri-food processing and exporting in China. Design/methodology/approach – Survey data collected from 80 agri-food SMEs in Jiangsu Province were used for empirical testing. The authors applied an ordered logit regression approach for model estimation. Findings – The results demonstrate that strong guanxi networks, high level of transaction-specific investments and inter-personal trust significantly contribute to a high level of relationship satisfaction for agri-food SMEs in China. In addition, inter-personal trust shows a moderating effect on the relationship between transaction-specific investments and relationship satisfaction. Practical implications – Business relationships play a critical role in the modern market environment. Relational arrangements (based on guanxi and inter-personal trust) should be further enhanced in order to yield satisfied business relationships for SMEs in China. Originality/value – The paper extends our understanding of relationship (guanxi) marketing, as well as marketing practices for agri-food SMEs in China. JEL classification: C58, G13

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Bibliographic Info

Article provided by Emerald Group Publishing in its journal China Agricultural Economic Review.

Volume (Year): 4 (2012)
Issue (Month): 3 (October)
Pages: 379-390

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Handle: RePEc:eme:caerpp:v:4:y:2012:i:3:p:379-390

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Related research

Keywords: China; China's sugar markets; Co-integration; Commodity markets; Financial markets; Price discovery; Prices; Pricing power; Sugar;

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References

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  1. Lucia BALDI & Massimo PERI & Daniela VANDONE, 2011. "Spot and future prices of agricultural commodities: fundamentals and speculation," Departmental Working Papers 2011-03, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  2. Lutkepohl, Helmut & Reimers, Hans-Eggert, 1992. "Impulse response analysis of cointegrated systems," Journal of Economic Dynamics and Control, Elsevier, vol. 16(1), pages 53-78, January.
  3. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
  4. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  5. Hasbrouck, Joel, 1991. " Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
  6. Anderson, Edward J. & Hu, Xinmin, 2008. "Forward contracts and market power in an electricity market," International Journal of Industrial Organization, Elsevier, vol. 26(3), pages 679-694, May.
  7. Mattos, Fabio & Garcia, Philip, 2004. "Price Discovery In Thinly Traded Markets: Cash And Futures Relationships In Brazilian Agricultural Futures Markets," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19019, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  8. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
  9. Sugato Chakravarty & Huseyin Gulen & Stewart Mayhew, 2004. "Informed Trading in Stock and Option Markets," Journal of Finance, American Finance Association, vol. 59(3), pages 1235-1258, 06.
  10. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
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Cited by:
  1. Yang, Linghubo & Zhang, Dongxiang, 2013. "Can futures price be a powerful predictor? Frequency domain analysis on Chinese commodity market," Economic Modelling, Elsevier, vol. 35(C), pages 264-271.

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