The market that operates effectively will contribute to actors’ profit and welfare in the coffee value chain conversely if the market is affected by imperfect problems. Suppose the value chain lacks market news, short-term storage, information for product and processing, quality check, and market power. In that case, implied chain actors’ profit and welfare will not be reached. A new method can estimate market power by Lerner index through the stochastic cost frontier once the inputs data price is unavailable and the existence or non-existence of constant returns to scale. So this approach is applied to evaluate farmers’ market power in the value chain of Arabica coffee in Lam Dong Province, Vietnam. Primary data were collected through interviews with 200 farmers Da Lat, Lac Duong, Lam Ha, and Don Duong of Lam Dong Province. The estimated results of the market power and Lerner rate are 0.001. This index indicates that the local coffee market is perfect competition. So the coffee growers do not have market power. The RTS index of 0.56 (less than one) illustrates that farmers’ Return To Scale (RTS) is decreased. Therefore, coffee farmers should link together to establish cooperative that increases market power in price negotiation and coffee consumption.

Value chain analysis has a central role in determining the distribution of benefits of the participants to upgrade solutions to the value chain. This paper is based on an integrated approach of methods and results of research on agricultural product value chain analysis. Research focuses on analyzing value chain approaches commodity chain analysis, Porter’s value chain model, Global value chain and GTZ organization, the number of actors in the value chain, profit distribution among actors participating in the chain, some popular tools in value chain analysis, and solutions to upgrade the chain. On that basis, the paper also points out the gaps in the current agricultural value chain research: 1) There is no combination of SCP analysis framework with other approaches; 2) Researchers have not analyzed the causes of the markup through the actors or the market power of the actors; 3) There are few studies combine all three models: Porter’s five forces, PEST and SWOT to have a complete basis for proposing solutions to upgrade the value chain.

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Value chain analysis has a central role in determining the distribution of benefits of the participants to upgrade solutions to the value chain. This paper is based on an integrated approach of methods and results of research on agricultural product value chain analysis. Research focuses on analyzing value chain approaches commodity chain analysis, Porter’s value chain model, Global value chain and GTZ organization, the number of actors in the value chain, profit distribution among actors participating in the chain, some popular tools in value chain analysis, and solutions to upgrade the chain. On that basis, the paper also points out the gaps in the current agricultural value chain research: 1) There is no combination of SCP analysis framework with other approaches; 2) Researchers have not analyzed the causes of the markup through the actors or the market power of the actors; 3) There are few studies combine all three models: Porter’s five forces, PEST and SWOT to have a complete basis for proposing solutions to upgrade the value chain.

Although some studies have assessed the market power of advanced degrees in Vietnam’s agricultural sector, this research only focuses on analyzing the level of market concentration through CR4 or HHI indexes. The stochastic cost frontier can estimate market power using the Lerner ratio when input price data are not available and with or without constant returns to scale. Thus, the stochastic cost frontier with a maximum likelihood approach of Kumbhakar et al. (2012) is used to assess the market power of traders in the coffee value chain in Lam Dong province, Vietnam. The estimated market power and Lerner rate results are 0.0001. This index shows that the local coffee market is a market with perfect competition. So the traders do not have market power. Thus, there is no collusion between coffee traders to lower the purchase price for farmers or increase the price for processors and exporters. An RTS ratio of 0.96 (less than one) shows that the return to scale for traders is decreasing. This number proves that the degree of competition in the local coffee market among traders is very high.