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Behavioral finance literature has long claimed that internet stock message boards can move markets. In this chapter, the authors study more than 2,000 internet board messages posted across finance message boards in India (Chittorgarh, etc.) for 110 companies that went for initial public offering (IPO) in the last one year. This study has multi-fold objectives. First, the authors try to identify the factors which lead to a discussion on an IPO stock in the message board. Second, the authors identify the factors which differentiate a widely discussed stock from the less discussed one. Next, the authors apply advanced machine learning technique to identify the topics which are discussed in the message board through automatic topic modeling. The methodology used includes a logistic regression model for identifying firm characteristics which leads to a probability of getting stakeholders’ attention and hence more discussion. The authors also use advanced topic modeling techniques to identify topics of discussion on the message boards through machine learning. The authors find that larger sized firms, younger firms, firms with low leverage, and non-manufacturing firms get discussed more and the topics of discussion relate to their financial statements, trading strategies, stock behavior, and performance.

This research presents a study on the supply chain process of an Indian apparel industry considering various parameters involved. The study aims to identify the main parameters to improve the supply chain process and develop a comprehensive structural relationship to rank them to streamline the apparel supply chain process and business environment.

The team of five experts from this apparel industry was made to give scores to multiple parameters. The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) technique is used to develop the model for eleven key parameters and then rank them.

Based on the data analysis the planning, customer and warehouse storage have emerged as top three key parameters while the non-replenishment approach, push and pull strategy and manufacturing of the product are identified as the bottom three parameters from a hierarchy level. These parameters have been ranked based on their contributing attributes in this apparel supply chain process.

The study provides an overall ranking of parameters and the implications are in the direction of helping the industry to improve its supply chain performances rather than focus only on productivity. Further, the key parameters are identified as critical inputs and show that the firms are being more proactive and well prepared comprised of the industry.

The study indicates that the key parameters are identified by this apparel brand to improve its supply chain process. The key supply chain process involves planning, manufacturing, distribution, end customer and returns logistics of the goods, etc. So, this research also provides the focused parameters on the supply chain performance received by end customer from the supplier and rank them for effectiveness and improve their overall organizational performance. It also provides a critical observation of their supply chain process improvement which includes different brand uses, strategies and approaches.