When a Handshake is Enough

MIT Sloan research found that trust can be a worthy asset for businesses.

Trust plays a big part in people’s everyday relationships. Could it also be an important resource in business relationships?

Two research colleagues and I set out to answer that question in a study of trust in supply chains. By conducting experiments using computer simulations, the researchers found that trust can, indeed, be an effective tool for resolving potential business conflicts.

The message we have for companies is that contracts are not the only way to resolve issues. There are many market conditions in which trust between the parties by itself is a sufficiently powerful way to resolve incentive conflicts.

The subject chosen for the study is one of the most vexing problems in supply chain management: The tendency for manufacturers is to issue overly optimistic forecasts.

Manufacturers want to be sure they have abundant supply to satisfy customers. But inflated forecasts can prompt suppliers to overproduce, which can lead to costly losses. In 2001, the networking equipment supplier Cisco had to write off $2.1 billion in excess inventory because of inflated customer forecasts.

To understand the role of trust in a forecast sharing setting, I and my colleagues, Ozalp Ozer of the University of Texas at Dallas and Kay-Yut Chen of Hewlett-Packard Laboratories, recruited graduate students in business related fields for a computer experiment. The participants all had some familiarity with how manufacturers and suppliers interact. Some of the participants were assigned the role of suppliers and others manufacturers.

With the software, we varied two conditions—the cost of the product the supplier was producing and uncertainty in the market demand. Then we saw how changes in these two conditions affected trust between the parties and whether the changes affected decisions they made in the market.

We found that when the cost of the product was low and the manufacturer’s market was stable, trust was high, and the businesses cooperated. Ink cartridges represent such a market. They are relatively cheap to produce, and the market for them is stable.

When cost was high and the market uncertain, trust was low and cooperation broke down. A real life example can be found in laptop computers, which are costly to produce and face a volatile market. In these cases, parties probably do need to resort to contracts to manage their relationship.

When the cost of a product was low and markets were uncertain, trust remained sufficient for cooperation. An example is DVD movies, which are cheap to produce but are sold in volatile markets.

Our key insight is that the risk entailed by trusting, which is influenced by the product’s cost, has a greater impact than market uncertainty in affecting people’s trust. When that risk is low, companies will naturally cooperate with each other.

To illuminate the experimental findings, we developed a mathematical model that quantifies trust and its close relative, trustworthiness, to show how they jointly affect forecast sharing.

A company that is in a supply chain relationship could use the model for guidance in dealing with the other firm. If the companies have a rough assessment of how much their partner trusts them, they can use this model to figure out how their partner will act and what will be the optimal decision for themselves.

Our findings were published in the June 2011 issue of the journal Management Science, in the article, "Trust in Forecast Information Sharing."

Academic researchers have typically overlooked trust as a factor in supply chain relations. Previous studies have primarily assumed the parties either have complete trust in each other or absolute mistrust. We found that decisions people make fall between these two extremes. Their behavior shows a continuum of trust and trustworthiness.

Yanchong (Karen) Zheng is an assistant professor of operations management at the MIT Sloan School of Management. Her research focuses on studying behavioral and information aspects of supply chains through both analytical modeling and empirical investigation. She can be reached at [email protected].

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