Final answer:
The department store's implementation of a new application that analyzes spending and popular styles supports a business strategy of customer-oriented merchandising, data-driven decision making, and leveraging big data analytics.
Step-by-step explanation:
To make sure they stock clothes that their customers will purchase, a department store implements a new application that analyzes spending levels and cross-references this data with popular clothing styles. This is an example of using information systems to support a business strategy of customer-oriented merchandising and data-driven decision making. By leveraging big data analytics, the store can align its inventory with customer preferences to maximize sales and minimize leftover stock from unattractive styles.
This approach reflects broader shifts toward efficiency and predictability in the retail sector, often characterized by the term McDonaldization, which emphasizes consistency and control in customer experiences. Moreover, such data-centric strategies resonate with the historical evolution of department stores, where the standardization of products became the norm alongside the proliferation of fixed pricing and branding, leading to the modern consumer culture we are familiar with today.
As highlighted in the Fashion Industry Charter for Climate Action, brands are increasingly considering sustainability within their corporate strategies, perhaps influencing department store stocking decisions. Thus, modern applications that analyze spending trends against popular styles are firmly rooted in the context of evolving consumerism and the strategic objectives of retail businesses to cater to the tastes and values of their customers.