Automated Negotiation: Can Machines Replace Human Negotiators?
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The document discusses the potential for machines to replace human negotiators in both B2C and B2B contexts, highlighting that machines can perform negotiation tasks more efficiently and without emotional bias. While automated bidding systems like eBay's demonstrate this potential in B2C scenarios, B2B negotiations remain largely human-driven despite the feasibility of automation for various negotiation variables. It explores the development, benefits, and challenges of implementing automated negotiation in B2B transactions.
Automated Negotiation: Can Machines Replace Human Negotiators?
- 1. Can machines replace human negotiators? Negotiators exchange messages, process and evaluate data, make concessions, impose conditions, make tradeoffs, accept or reject proposals, make counter-proposals, decide whether to close a deal or walk away. Machines can perform all of these tasks better than human agents. Computers are not prone to misunderstanding and do not lie, bluff, threaten or lose their tempers. Take e-bay’s automated bidding system. Bidder A can bid $10 for an item and set a maximum amount he is ready to pay, say $50. As other bidders make higher offers, the system will trump them incrementally up to the maximum set by Bidder A, who will either get the item at the optimal price (one increment above the highest competing bid) or abandon the bidding process once the maximum amount is reached. Such efficiency would be impossible in a traditional auction, where emotion might prompt a bidder to pay more for an item than originally intended or back off in the face of an aggressive competitor. While e-commerce, albeit of a primitive kind (the sole variable is price) has become widespread in B2C and C2C transactions, it does not appear to have made the same inroads in B2B negotiations as in other aspects of business (catalogue, inventory and procurement management) although it is technically possible to automate B2B negotiations for variables other than price, such as discount, delivery time, incoterms, payment terms, warranty and maintenance. There are only two differences between our e-bay example and a B2B scenario: in the former, there is one variable (price) and only one party makes concessions (the bidder). In automated B2B negotiations, both sides need to make concessions and there are multiple variables. If we compare human and automated B2B negotiations, the main differences are that the former use natural language, include messages that are ambiguous or irrelevant to the object of the negotiation and rely on subjective evaluations and partial decisions, whereas the latter use machine language, focus exclusively on the variables at hand and make objective evaluations and impartial decisions. Academics and others who write about negotiation tend to deal only with human negotiation and steer clear of automated negotiation, which is the preserve of mathematicians, experts in artificial intelligence and game theory. An Amazon search (June 2013) gives 88 results for “B2B Negotiation” and 2 results for “Automated B2B Negotiation”. While much work has been done on the subject of automated negotiation, it is often abstract, inaccessible to the layman and not directly applicable in terms of deployment of the technology in B2B negotiations. Despite the existence of a global e-commerce infrastructure that could support automated negotiation, most B2B negotiations are still conducted by human agents in the same way they have been for centuries: through face-to-face discussions. This paper describes what automated negotiation is, gives an overview of its development, explores the benefits it can bring to B2B transactions and examines the challenges and limitations involved in replacing human negotiators by machines.