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Financial inclusion remains one of the most promising avenues to bring about development for the poorest segments of society. A substantial body of work has looked into financial inclusion, especially in terms of microfinance, but much of it has been anecdotal and case-based. There is little scholarship that broadly investigates how microfinance-funded businesses choose to use the loans, especially given the ever-present competition for resources that such businesses face regarding which investment priority to pursue. In addition, the efficacy of these investments in terms of subsequent profitability remains unexplored, and so too does the influence of the entrepreneur’s embeddedness in the local community. The paper aims to discuss these issues.

This study reports the results from a field investigation of 927 women entrepreneurs who received a microfinance loan from a leading Indian microfinance institution. Logit and OLS regression models are employed in a moderation analysis by way of hierarchical regression.

Results indicate that access to microfinance increases the likelihood that the enterprise invests in marketing infrastructure and operational scale. In addition, structural embeddedness has a weakening effect on this relationship for operational scale while having a strengthening effect on the relationship for marketing infrastructure. Finally, operational scale is related to enterprise profitability, while marketing infrastructure is not. These findings suggest that embeddedness in the community is associated with the entrepreneur making sub-optimal choices regarding microfinance utilization.

To our knowledge, this is the first study to investigate the simultaneous marketing and operational impacts of microfinance access. It is also the first study to relate these measures to the profitability of the enterprise, especially in the context of structural embeddedness in the network.

The network capacity deployed to manage the busy hour (or peak-hour) traffic remains underused during the nonbusy (off-peak) hours. Transferring some traffic from peak-hour to off-peak hours is likely to improve the utilization of network resources during the off-peak hours. This paper aims to examine whether diverting traffic from peak-hour to off-peak hours is possible by adopting the differential pricing policy.

The peak-load pricing theory suggests that the policy of differential pricing is socially optimal when there is peak demand for a particular duration and then there is off-peak demand. In this study, hourly traffic data from both peak and off-peak periods were collected from the Indian telecom service provider, “Aircel.” The paper analyzed the disparity in traffic between peak and off-peak hours using the nonparametric Tukey’s test. An experiment was also conducted to analyze whether a significant shift in telecom traffic occurs from the peak to the off-peak period when a price discount is applied during the off-peak period.

Statistically significant differences were observed in network traffic between peak-hour and off-peak hours. The network utilization of the telecom service provider Aircel was notably lower, particularly during the off-peak hours. The experiment demonstrated a high degree of price sensitivity among telecom service subscribers. Telecom Regulatory Authority of India (TRAI) has not considered network utilization of telecom service providers as a key performance indicator. Based on the outcomes of the study, this paper recommends that TRAI should adopt a more proactive approach by encouraging telecom service providers to follow the policy of differential pricing to enhance utilization of their network capacity.

To the best of the authors’ knowledge, this is the first paper to explore the issue of pricing as a tool for bringing about more uniform movement of telecom traffic, thereby enhancing network utilization within India’s telecommunications sector.