A TOPSIS model for understanding the authors choice of journal selection

Subsequent to preparation of an article, authors start to look for a suitable journal to submit. Authors are assumed to select the journals by considering their future expectations regarding the maximization of prospective impact of the study, increasing the probability of acceptance and minimizing the total time consumed until the paper is published. Furthermore, the scope of a candidate journal should be in line with paper's content. Currently, it is possible to find these journal related facts (such as average waiting times, acceptance rates, impact factor and etc.) on the web pages of the journals. However, the exact effect of these factors, and how to incorporate them into modeling, are yet unclear; further research is required to explore them. On the other hand, we know that Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) can be a useful approach to rank the journal alternatives. We require corresponding weights of factors to obtain a complete decision making model. If the correct weights of these factors for such a TOPSIS model can be estimated, we can understand the magnitude of their corresponding effects. Thereby, we can explain the journal selection decision by using an analytical approach. Therefore, the main purpose of this paper is to find appropriate weights of these factors that can explain why already published papers were submitted to their current journals. To the authors' knowledge, this paper is the first to search for weight of factors in TOPSIS, where the actual decisions are known a priori. For testing purposes, we create our data set by collecting the already published papers (in year 2019) which has the environmental risk term at the title/abstract or keywords. We test different TOPSIS models (with different random weights) for each of the papers and the rank the journal alternatives. If the first, second and the third journal alternative is the actual journal that published the paper, we assume that the model predicts accurately. As a conclusion, the TOPSIS model which predicts the journal for the published papers much more accurately is accepted as the valid decision making model. Inevitably, we have certain assumptions regarding to this model. We assume that the authors are informed about the journal facts and make rational decisions about journal selection.

Automated summary

Authors consider various factors when selecting journals, such as prospective impact, acceptance probability, and publication time. While journal-related information can be found on journal websites, further research is needed to understand how to incorporate these factors into modeling. TOPSIS method can be useful in ranking journal alternatives, but finding the correct weights for factors is crucial in establishing a decision-making model.