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.