Analyzing enterprise asset structure and profitability using cloud computing and strategic management accounting.

Area of Science:

• Business and Management
• Strategic Management Accounting
• Financial Analysis

Background:

• Enterprise profitability is influenced by asset structure.
• Understanding the relationship between asset allocation and sustained profits is crucial for businesses.
• The express industry presents a unique case for studying asset structure and profitability.

Purpose of the Study:

• To explore the role of asset structure in enterprise profitability within the express industry.
• To analyze the detailed relationship between asset structure and profitability.
• To compare the effectiveness of edge computing versus big data processing for this analysis.

Main Methods:

• Utilized strategic management accounting principles.
• Employed edge computing and related analysis tools.
• Compared financial and non-financial indicators of express enterprises.
• Developed an analysis framework to assess asset structure and profitability.

Main Results:

• Enterprises with heavy assets, like SF, showed increased profit margins.
• Other express companies with smaller assets experienced sharp revenue drops.
• SF demonstrated strong asset management and net asset growth, supported by the capital market.
• The edge computing method proved superior in local data processing and overall framework performance compared to big data methods.

Conclusions:

• Heavy assets can positively impact enterprise profitability in the express sector.
• Effective asset management and capital market support are key to net asset growth.
• Edge computing offers a more efficient analytical approach for asset structure and profitability evaluation in this industry.