Mar 24, 2008
An informatics approach to pricing petrochemical products has been devised by scientists at the Market Research Department of the Research Institute of Petroleum Industry (RIPI) in Tehran, Iran. Their model puts a price on “know-how”, which is the most complicated activity of the commercialization stage.
Writing in the International Journal of Technology, Policy and Management, (2008, 8, 279-297), Reza Bandarian, Ahmad Mousaei, Abbasali Ghadirian and Maham Tabatabaei explain their approach. “The RIPI has a mission to bring ideas to market in terms of developing new technologies and new products,” they say, “Commercialization is one of the critical stages in this process.” Their model examines three pricing scenarios – optimistic, pessimistic and actual – for selling technology and was validate against historical data of various RIPI petrochemical products.
There are increasing demands on companies, not just in the petrochemicals sector but across the commercial spectrum. The marketplace needs better, faster and cheaper technology and products, while intellectual property, once simply seen as an expense has become an important source of revenue. Indeed, many of the problems seen in modern business hinge purely on IP rather than solid, hands-on extracted or manufactured resources. IP provides a critical competitive advantage for the firms that hold it but a serious disadvantage for those that do not.
Bandarian and colleagues point out that companies can no longer rely on the incremental innovation, i.e., improving on what has already been done, to compete and survive. Today it seems that “radical innovation” and “breakthrough products” are essential to long-term commercial sustenance. Even governments are beginning to recognize this in their wealth creation programs. The US National Science Foundation (NSF), which funds a huge amount of academic research in the USA not only demands that research projects are interesting, good quality and important scientifically, but that they also demonstrate the solution to a societal need or goal, which might be in constant flux.
The bottom line is that: “What customers want today, they will not want tomorrow, says the team. They point out that almost half the major corporations that existed in 1975 no longer trade. This is probably best explained by the fact that those corporations failing to grasp this simple tenet.
“One of the explanations for this dismal record is that companies are still trying to link emerging technologies with existing markets when they should be linking emerging technologies with emerging markets.”
In Iran and other countries of the Middle East, the researchers explain electronics, medicines and chemicals are major imports, while Iran’s national income comes essentially from oil production. Unfortunately, this resource has been used for wealth creation rather than technology creation. “Traditionally, the oil industry has improved in engineering maintenance while based on technology limitation; we have been kept behind that of developed countries, and the gap has increased.
This is perhaps the most important reason why Iran is the market leader in basic petrochemical products, but in high-value products, we have lost the market against developed countries,” the researchers add. They present a model that could allow innovation to seep, if not surge, through, by using know-how to evaluate and price innovative products, it is based on the low-cost and speed of current pricing models -experiential and mathematical – and side-steps their disadvantages of being untimely, requiring too much pre-market testing, and being highly skills dependent.
The researchers incorporate various factors into their model – the life cycle of know-how, annual market size, raw material and total production cost, selling price, net profit, earned income during investment, risk-free rate of return, know-how investment required, know-how return in its life cycle, know-how annual return in its life cycle, present value of know-how return in its life cycle.
Other factors can be fed into the model depending on the specific characteristics of the product in question. Indeed, “Our comprehensive framework of the commercialization of new technologies in the petroleum industry that can be used with some modification for other industries,” the researchers say. They tested their model retrospectively against RIPI product data and demonstrated an accuracy of around 97%.