Porter’s Five Forces

Bargaining Power of Buyers

According to Wikipedia:

The bargaining power of customers is also described as the market of outputs: the ability of customers to put the firm under pressure, which also affects the customer’s sensitivity to price changes. Firms can take measures to reduce buyer power, such as implementing a loyalty program. Buyers’ power is high if buyers have many alternatives. It is low if they have few choices.

Potential factors impacting the Bargaining Power of Buyers include:

  • Concentration of Buyers relative to the Suppliers
  • Buyer Price Sensitivity
  • Buyer Switching Costs
  • Availability of Information about Sellers

This Case Study provides a high-level overview of the workflow without detailed explanation. It assumes you are already somewhat familiar with KNIME and Market Simulation. If not, start by reviewing the Building Blocks and Community Nodes.

Case Study

The Bargaining Power of Buyers reflects their ability to put pressure on the Sellers by either driving down the price or by driving up the cost-to-serve. Power increases when Buyers are price sensitive and have low switching costs. These same factors tend to also reduce the Buyer’s own Product Differentiation, driving consolidation within the Buyer’s own industry.

The industrial Buyers of Bulk Chemicals originally offered downstream customers differentiated products as those Buyers discovered new solutions and opened up new markets. However, over time, industry practices were standardized and Buyers’ products became increasingly commoditized. As the Buyer’s industry consolidated, and the size of the Buyers increased, the pressure they could exert on the Bulk Chemical Sellers also increased.

Shifting Market

In this Market Simulation, the market for the Sellers of Bulk Chemicals is shifting. Over time, the diversity in the perceived value Buyers have for Bulk Chemicals decreases as the products that Buyers sell downstream to end-customers commoditize. This causes Buyers to exit or merge, and the industry to consolidate.

Buyers who place very similar values on the upstream Bulk Chemicals are the ones who tend to merge. Their downstream Products increasingly compete on price. This, in turn, puts pressure on those Buyers to decrease their costs.

Hence the Profit Maximizing Price of the Sellers’ of Bulk Chemicals decreases as there is less and less diversity in the Buyers’ value for their Bulk Chemical products.

Buyer Diversity

The diversity in the value Buyers have for Bulk Chemicals decreases over time as their own industries consolidated.

Changing WTP

The average Willingness To Pay (WTP) of Buyers remains steady (here $1000 per barrel). It is just the diversity or the standard deviation that is decreasing (Parameter B). Diversity starts wide at $200 per barrel. But after 35 loop iterations, the standard deviation in WTP drops to $30 per barrel.

Buyer Clusters

It is assumed that the number of individual contract proposals do not decrease. But the bigger merged Buyers (the ‘Clusters’) buy more and more of the contracts.

Profit Maximizing Price

The highlighted ‘Price War‘ node calculates the Profit Maximizing Price of the Bulk Chemical Sellers each iteration as the diversity in the Buyers WTP decreases. As a result, the Sellers Profit Margins drop from $185 per barrel down to $77 per barrel.

The ‘DBSCAN‘ node estimates the decreasing number of Bulk Chemical Buyers each iteration. Buyers who place very similar values on the upstream Bulk Chemicals tend to merge as their their own downstream Products are commoditized. In this Market Simulation, the number of Buyers drops from 1,157 to 106.


The Profit Magin of the Sellers’ decreases as the Buyer’s Industry consolidates and there are fewer, but larger, Buyers.