Methodology and descriptive analysis

With a view to review the body of research on deteriorating inventory models, the methodology applied in our study is based on the work of Seuring, Müller [31], which discusses the basics on how to conduct a literature review through a structural content analysis. By doing so, the following subsection contains a description of the material collection process as well as of the background of the collected material.
To ensure the quality of selected studies, we confined our searching to only peer-reviewed research papers that were written in English and ranked with a quartile score of Q1 by either ISI or Scopus database. By means of this quality selection rule, material for our review was collected in two phases. In the first phase, we extracted a sample of 150 articles published between 2001 and 2015 from previous related reviews [15, 17]. We felt that 10 papers per year, meeting our above quality selection rule, was good enough to draw additional inferences. In the second phase, we used the Web of Science (WOS) Core Collection database for searching research papers from 2016 to 2018. The search in the WOS platform was conducted in 05/14/2019 by using the expressionTS=((deteriorat* OR perish* OR decay* OR ”shelf life” OR spoil* OR outdate* OR “waste” OR lifetime*) AND “Inventory”) , and then filtering matched records by selecting all the Research Areas of the WOS that generated at least one relevant paper for this review. All selected Research Areas from the WOS database are displayed in Figure 1.
As can been seen in Figure 1, the above searching process yielded 1204 records. In our sample we do not include book chapters and data papers, so we first discarded them. Next, we scanned the title, keywords, and in some cases, the abstract to select all potential articles which develop an inventory model. Here, we were as flexible as possible, and we obtained a preliminary sample of 488 articles. Then, as was done for papers published between 2001 and 2015, we chose all papers ranked with a quartile score of Q1 by either ISI or Scopus database. This resulted in a sample of 325 papers. Last of all, we proceed to classify all the inventory models with the potential of being applied to products which naturally undergo physical degradation. As a result, we obtained a relevant sample of 167 papers published between 2016 and 2018.
Note that when executing a Topic Search in WOS (TS =…), the search engine looks for further matches of the words entered by using an extended keywords (“keywords plus”), which is harvested from the title of indexed articles by WOS. We realized that this “keywords plus”, which is unique to WOS, can change over time. Thus, users may be aware of this when executing the same topic search at different times. It is also worth noticing that we employed all the search terms in [15, 17]. However, as is evident from Figure 1 and Table 1, there is a significant amount of unrelated studies even after limiting the search to specific research areas. In this regard, we had to discard 699 papers by scanning the reference manager files (RIS) exported from WOS database, and most of them coming from records found using the word “waste” (see Table 1).
To overcome this shortcoming in future literature reviews, along with the selected Research Areas from WOS (see Figure 1), we suggest a far better search expression that includes both all the papers selected in our final sample and all the inventory models for deteriorating items that we identified as relevant in a further examination. This search expression generates 493 records instead of 1804, and is provided as follows:
TS=((deteriorat* OR perish* OR decay* OR ”shelf life” OR lifetime$ OR “expiration” OR “evaporating”) NEAR/14 (product$ OR item$ OR produce$ OR “inventory” OR “goods” OR food$ OR “cost” OR “weibull” OR “storage”) AND “inventory” NOT “life cycle assessment”)
In the above expression, the wildcards (*, $) represent unknown characters and are used to find inflected forms of the corresponding words. The asterisk (*) represents any group of characters while the dollar sign ($) represent zero or one character. The quotation mark (“ ”) is used to find exact phrases. And the proximity operator NEAR/14 is used to find only records where the terms joined by the operator are within 14 words of each other. Readers are referred to the WOS core collection help for more details and tips.
Note that we did not recommend to use in the query the keywords spoil*, “waste” and outdate*. For the case of spoil* and outdate*, we found that all the relevant papers provided by these keywords search are also provided by the keywords perish* and “shelf life”. And for the case of the “waste” keyword we found on closer examination that the records solely belonging to this query (15 of the 39 in Table 1) are not actually relevant for a review of deteriorating inventory models.
Table 2 shows the list of the Journals to which most of the selected articles belong, and ranked in descending order of papers published. It can be verified that these journals published 121 (72.5%) of the total number of papers included in our review in the research period (2016-2018). The rest of journals with only one or two paper each are provided in Table 3.
Among all the journals, the International Journal of Production Economics alone accounts for 25 papers (17.5% of all publications). Second and third are the Computers & Industrial Engineering and the European Journal of Industrial Engineering with fifteen and fourteen papers each. There is a dominance of traditional Operations Research & Management Science journals, but in recent years, environmental management-related journals have increasingly been used as a channel for publication.