The article “Analysis of Product Complexity considering Disruption Cost in Fast Fashion Supply Chain” comes from the engineering and mathematics journal Mathematical Problems in Engineering, published in the United Kingdom and Northern Ireland. It focuses on the issue of complexity in the fast fashion supply chain and the financial impact on the producers of the good. Through quantitative experiments, the two authors mathematically analyze the impact of disruptions within the supply chain and propose solutions. The 16-page article also includes various informational tables, a large conceptual map, and different mathematical equations representing average costs and the total cost of supply chain disruption. This article does not address the ethical dilemmas regarding fast fashion, nor does it mention the environmental impact; instead, it mainly focuses on the resource chain that supplies fast fashion companies. It refers to fast fashion as “the concept of shortening the lead time . . . and offering new products to the market as fast as possible” (Sardar and Hae Lee 2). Because this is an incredibly detailed and meticulous article, I will be focusing on the general structure and analyzing the introduction and conclusion.

Within this article, the vocabulary used is highly academic in relation to mathematics. However, a key pattern I noticed in the introduction was the usage of multiple words or phrases relating to a systematic course of events. For example, the word “chain” or the phrases “synchronization of various activities” or “traveling through a pipeline” all convey the idea of following a strict path (Sardar and Hae Lee 1). There was also the paradoxical situation where I discovered words within both the categories of uneven distribution and connection. Some phrases relating to uneven distribution are “dependent portion of global chains is ineffective”, “disrupted”, and “global outsourcing environment” (Sardar and Hae Lee 1). In contrast, phrases like “vertical integration” and “correlation” create a sense of connection. It is interesting to consider the relationship between these two categories and how they function appropriately within the context of this article.

Structure:

The article is broken down into seven sections: Introduction, Related Literature and Conceptual Framework, Estimation of Disruption Cost as a Function of Product Complexity, Numerical Experiments, Adjusting the Level of Product Complexity across the Supply Chain, Insights for Practitioners, and Conclusions and Future Work. This somewhat follows the classic IMRAD structure of most scientific articles; however, it more closely resembles the scientific method: observation, research, hypothesis, experimentation, and conclusions from observed data. The second section (Related Literature and Conceptual Framework) is a review of literature and can be associated with observation and research. By reading previous articles and work regarding the fast fashion supply chain, the authors observe what has already been researched as well as gain information on their topic of interest. The third section (Estimation of Disruption Cost as a Function of Product Complexity) generates an estimation of all possible average disruption costs. It uses copious amounts of variables to represent the different costs within fast fashion; the variables are then used to create mathematical equations estimating averages. This estimation can also be called a hypothesis; a hypothesis is an educated guess backed up by previous research and observations, just like the equations and results of the third section. The fourth section is labeled Numerical Experiments, and contains data generated from the proposed equations used in three different scenarios. This is directly linked to the experimentation step in the scientific method. This calculated data is then adjusted in section five and discussed in section six. The final section (Conclusions and Future Work) includes the final findings derived from the experiment and lists possible directions for future research.

One major aspect of this article that I initially noticed was that the topic of each section was straightforwardly stated at the start of the section. Phrases like “Our focus is to . . .”  and “The key objective of this section is to . . .” demonstrate to the reader a clear idea of what each section will contain (Sardar and Hae Lee 2, 10) . There are also a variety of tables and graphs displaying the data resulting from the experiment and the estimation. This allows for a large amount of detailed information to be reported and summarized in a clear way for more readers to understand. Another aspect is the visual tools incorporated in the flow chart on page 6, labeled “Conceptual model to estimate disruption cost as a function of product complexity.” These visuals allow for a broader audience to understand the experiment.

As previously mentioned, this article uses a contrasting relationship between words referencing one-sidedness and words referencing connections. Through analysis of the data presented in the rhetoric, I have concluded that this relationship is present to further emphasize the need for this mathematical experiment to take place. The purpose of this article was to analyze the fast fashion supply chain and to propose possible solutions to disruption costs within the chain. This category of inconsistency is stressed mainly in the introduction of the article to highlight the importance and necessity of the experiment within the context of the fast fashion market. Furthermore, the category of connection is also present in the introduction to show the readers an outcome for the experiment. The issues surrounding the supply chain are all related to uneven distribution, so by introducing the category of cohesion, the authors familiarize the audience with what they are hoping the outcome of the experiment will do.