In grey incidence decision-making models, the development tendency of each indicator value for the evaluated object is rarely considered, and the degree of discrimination between evaluation values is not high enough sometimes. In view of this, a novel grey incidence decision-making method embodying development tendency is proposed, which can guide the evaluated objects to a better direction in the future and can also distinguish the evaluation results to the greatest extent. Firstly, the development factor is defined, which can exert an effect on the development tendency of each indicator value over time. Secondly, guided by an exponential function, the weighted degree of grey incidence based on exponential function is constructed by combining the maximizing deviation and grey entropy in assigning weights to the indicators. Thirdly, the weights of the time series are delivered by the combined weighting method based on level difference maximization. Hence, the dynamic evaluation values are produced for ranking the evaluated objects. Finally, a practical example of the transformation and upgrading of the manufacturing industry in the Yangtze River Delta (YRD) demonstrates the effectiveness and application of the proposed model.