Potential diffusion of expert systems in forecasting

We drew upon findings from the diffusion literature to assess the prospects for the diffusion of expert systems in forecasting. Forecasters judged pot ential adoption of expert systems in relation to two techniques that had be en widely adopted in the past, Box-Jenkins and scenarios. They also rated e ach technique on seven innovation characteristics: relative advantage, comp atibility, divisibility, communicability, complexity: product risks, and ps ychological risks. Thr respondents were classified hv four forecaster roles : researcher, educator, practitioner, and decision maker. In general, the e xpected probabilities of adoption for expert systems were slightly higher t han for the two other techniques. Additionally, the respondents rated exper t systems nearly equivalent to Box-Jenkins and scenarios on relative advant age and communicability. In relating the probabilities of adoption to the c haracteristic ratings, the groups perceived significant negative psychologi cal and product risks with expert systems. However the experts, especially practitioners and decision makers. rated expert systems positive on compati bility, divisibility, and communicability, so it map be desirable to ensure that these positive traits are stressed with potential adopters, especiall y researchers and educators. (C) 2001 Elsevier Science Inc.