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The extant literature on international new ventures (INVs) has primarily focused on the emergence of INVs, leaving a research gap regarding their performance consequences. INVs face challenges associated with foreignness and newness but also benefit from the learning advantages of newness, enabling them to adapt and perform better in new markets. Only a handful of studies probed the performance consequence of early internationalization by INVs, and empirical evidence has yielded inconclusive results. Existing literature also points out that emerging market firms encounter an additional hurdle due to their country of origin, but prior INV literature is mostly from advanced economies. Therefore, this study investigates whether early internationalization of emerging market INVs positively or negatively impacts their overall financial performance. Our findings, derived from the Indian context, reveal a nonlinear S-shaped relationship, whereby INVs initially experience a performance decline, followed by improvement, and ultimately a negative impact with excessive internationalization. Furthermore, we explore the contingent effect of the industry sector (manufacturing versus services) on performance and find that the S-shaped relationship is more accentuated for service sector INVs. In summary, this study contributes to our understanding of the internationalization-performance relationship for emerging market INVs, sheds light on the concept of learning advantages of newness, and examines the moderating effect of the industry sector.

We investigate in the Indian context how developing-economy business groups make capital structure choices during economic reforms. Using eighteen years of panel data, we find a general trend towards deleveraging, reduced access to deficit financing, and higher costs of debt financing for group-affiliated firms. We further find that the first two of these trends are more pronounced for firms affiliated with large business groups. Our findings contribute to resource-dependence theory by demonstrating that the size of business groups is positively related to their ability to better manage environmental interdependence and uncertainty during economic reforms.

Supply chain management (SCM) is a complex network of multiple entities ranging from business partners to end consumers. These stakeholders frequently use social media platforms, such as Twitter and Facebook, to voice their opinions and concerns. AI-based applications, such as sentiment analysis, allow us to extract relevant information from these deliberations. We argue that the context-specific application of AI, compared to generic approaches, is more efficient in retrieving meaningful insights from social media data for SCM. We present a conceptual overview of prevalent techniques and available resources for information extraction. Subsequently, we have identified specific areas of SCM where context-aware sentiment analysis can enhance the overall efficiency.

Prior review papers on corporate diversification have mostly explored the diversification-performance linkage but not the effects of diversification on various financing aspects of firms. By addressing this gap in the extant literature, our review aims to support entrepreneurs/managers in decision-making related to diversification, organizational form, and structuring. For investors, it highlights potential risks that diversification could expose them to. To this end, we propose an integrated framework that considers both conglomerates and business groups (BG) as diversifying organizational forms. We find that diversification impacts financing through two channels: financial synergies and internal capital markets (ICM). Broadly, financial synergies reduce the probability of default on a firm’s debt, thereby increasing its capital-raising ability. However, diversification can also lead to risk contamination and loss of limited liability benefits. ICMs relax financial constraints, facilitate propping of distressed business lines, and provide resilience during economic downturns. Unlike conglomerates, BG affiliated firms are often controlled through pyramidal structures. Pyramidal structures create divergences between control rights and cash-flow rights, thereby enabling expropriation of minority shareholders. However, such structures can also facilitate financing of growth opportunities from within the group. Finally, we propose certain avenues for future research.

Predicting the popularity of news article is a challenging task. Existing literature mostly focused on article contents and polarity to predict popularity. However, existing research has not considered the users' preference towards a particular article. Understanding users' preference is an important aspect for predicting the popularity of news articles. Hence, we consider the social media data, from the Twitter platform, to address this research gap. In our proposed model, we have considered the users' involvement as well as the users' reaction towards an article to predict the popularity of the article. In short, we are predicting tomorrow's headline by probing today's Twitter discussion. We have considered 300 political news article from the New York Post, and our proposed approach has outperformed other baseline models.

Aligning with Market Expectations (A): Innovation for the sake of innovation may not create value. [...]aligning innovative pursuits with market expectations is essential for gaining a competitive advantage. Efficient Execution (E): In continuation of the above point, before going to the market with a new product or idea, a neutral and impartial evaluation of the concept is crucial where a distant observer can play the role of the devil’s advocate. [...]managing the process of innovation is a challenging task, but failure to do so is a journey towards stagnation, if not death. [...]successfully managing innovation, encouraging creativity and retaining the talent pool is the only way to enjoy sustainable competitive advantage.