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DIGITAL ECONOMY ECOSYSTEMS

Published by admin at November 30, 2022
Categories
  • Business
Tags
  • DIGITAL ECONOMY ECOSYSTEMS

1. SELECTION OF INDIVIDUAL CASE (ENTERPRISE): The students will decide on an enterprise ecosystem that they will examine for the whole semester.
2. INDIVIDUAL REPORT: The students will select a specific topic * and will decide on a paper which builds on this topic, by making research in the academic business literature. Each student will write a report that addresses the questions concerning the selected paper and cases.
• Brief synopsis of the basics of the paper: theoretical argument, major propositions/hypotheses, research methods (if empirical), main empirical results, theoretical and empirical implications of the study. (25 pts)
• Student’s assessment of strengths and weaknesses of the paper (25 pts)
• Definition of student’s selected topic and the relevance of this paper to student’s selected topic (25 pts)
• Definition of student’s selected enterprise ecosystem case (components, frames, stakeholders and the relationship between them) and the relevance of this paper to student’s selected case (25 pts)

 

 

 

 

Sample Solution

The paper chosen for this individual report is “Exploring the Effects of Network Centrality on Firm Performance: An Analysis of the Chinese Automobile Industry”. This study explores how network centrality affects firm performance in the Chinese automobile industry. Specifically, the authors examine whether a higher level of centrality—measured by betweenness and closeness centralities—leads to better financial results, higher market share, and greater sales growth for firms operating within the industry.

To conduct this research, the authors used data obtained from an online database providing information on over 200 companies operating in China’s automobile industry between 2004 and 2016. They then created an adjacency matrix that recorded all relationships among these companies and utilized it to calculate each company’s degree of closeness/betweenness centrality. The authors then analyzed correlations between these factors and financial performance measures such as net profit margin (NPM), return on assets (ROA), total asset turnover ratio (TATR) and gross operating margin (GOM). Furthermore, they conducted regression models to investigate if there was a statistically significant relationship between network centrality indicators and firm performance measure.

The findings suggest that higher levels of closeness/betweenness lead to better financial outcomes for firms operating within China’s automotive sector. Additionally, regression results indicate that firms with higher levels of betweenness were associated with higher GOM rate while those with lower levels experienced greater TATR values than their counterparts. Those possessing a high level of closeness were also associated with larger NPM ratings compared to their counterparts with lower ratings suggesting that overall being positioned more centrally in an interconnected web was beneficial both financially and competitively.. These findings are important because they demonstrate how influential related entities can be on a firm’s overall success in terms of its reputation and profitability even when located outside its direct control realm or immediate sphere influence..

In conclusion, this study provides evidence demonstrating how important strategic positioning within corporate networks can be for improving performance outcomes such as increasing profits as well as gaining market advantage over competitors who lack similarly advantageous connections.. As such I believe practitioners should take note when constructing business plans so ensure resources allocated properly maximize potential linkages available thereby reaping rewards under certain conditions whilst accounting any potential risks developing unintended alliances which could have adverse effects desired objectives.

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