Talking Your Way into Entrepreneurial Support: An Analysis of Satisfaction Drivers in Entrepreneur Mutual Aid Groups

The role of organized peer networks in entrepreneurial support systems has been surprisingly neglected in the literature, despite their undisputed effectiveness in numerous areas outside the entrepreneurship realm. This study explores the efficacy of mutual aid groups for entrepreneurial support, as theoretically distinct from other group‐based mechanisms (such as peer group mentoring and many to one group mentoring). Drawing from respondent data of small, local mutual aid groups within the global entrepreneurship support organization (2,869 responses from members of 540 groups worldwide), we investigate the factors determining the entrepreneurs' satisfaction with the entrepreneur mutual aid groups. Understanding the antecedents of members' subjective satisfaction with the group serves an essential first step toward developing the models explaining the objective effectiveness of these organizations (e.g., performance, survival, and growth), in that the former is an essential, necessary condition for continuing participation in the voluntary mutual aid groups. Our analysis reveals that group climate and leadership are important drivers of group satisfaction.     

The investment decision with technological and market uncertainties

This paper examines how technological uncertainty affects current investment; specifically, what is the impact on a firm’s investment in an existing technology when an improved technology might arrive in the future. The firm can invest in the current technology and upgrade to the new technology after its arrival (sequential investing), or it can bypass the current technology and invest directly in the new technology (leapfrogging). The main result is that, in the presence of market risk, future technological uncertainty has a non-monotonic effect on investment, with the investment trigger being a U-shaped function of the expected speed of arrival of the new technology. In this U-shaped relationship, the investment trigger starts rising later if the new technology is more attractive and also when volatility and interest rate are high and growth rate low; thus, technological uncertainty is more likely to have a positive effect on investment under these conditions. Finally, we apply the model to the sequential versus leapfrog investment decision, and find that leapfrogging becomes more attractive relative to sequential investment when interest rate and new technology earnings enhancement are higher, and when market volatility, growth rate and new technology investment cost are lower.     

Agency cost of debt overhang with optimal investment timing and size

The concept of debt overhang (that is, an equity‐maximizing levered firm will under‐invest relative to a firm‐value‐maximizing firm) is well established in the literature. A number of papers have demonstrated it as delayed investment (when investment size is specified) or smaller investment (when investment time is specified). However, there is no work on the underinvestment effect when the firm chooses both size and timing of investment, as it usually does in real life. This is what our paper focuses on. When the firm has the flexibility to choose both size and time, the effect is complicated by the fact that delayed investment results in larger investment, which suggests that the underinvestment problem might be mitigated. We find, however, that the effect depends on how underinvestment is measured. When measured by the expected present value of investment, flexibility can mitigate or exacerbate the underinvestment problem, depending on the cost of installing capacity. But when measured by the agency cost, flexibility always exacerbates the underinvestment problem. It is shown numerically that, at the optimal leverage ratio, the agency cost with plausible parameter values can be economically significant. Thus, with the flexibility of choosing both time and size of investment, the debt overhang problem can be of significant practical relevance in corporate investment decisions.     

IMPACT OF THE NORTH AMERICAN FREE TRADE AGREEMENT ON THE U.S. TRADE WITH MEXICO

The North American Free Trade Agreement (NAFTA) took effect on January 1, 1994. The agreement is designed to reduce trade restrictions and enhance trade among Mexico, Canada, and the United States. The primary objective of this article is to examine and estimate the impact of NAFTA on the trade between Mexico and the United States. The data from 1989 to 1998 were used to estimate the overall trade as well as trade in three important products. The trade statistics were divided into two time periods: 1989-1993, before NAFTA, and 1994-1998, after NAFTA. The regression analysis and statistical t-test were employed to determine whether there were significant differences in the dollar volume of trade between the two time periods. The analysis of the data demonstrates that the trade between the United States and Mexico was significantly larger after NAFTA, which could not be attributed to other factors. However, the effects of other factors were analyzed. The success of the NAFTA model may have future policy implications in forging a Free Trade Area of the Americas (FTAA) in the near future.     

Market structure and bid-ask spreads: IBIS vs Nasdaq

A comparison is made between the bid-ask spreads of 30 high volume German stocks traded on IBIS and 30 high volume US stocks traded on Nasdaq. IBIS and Nasdaq are best described as agency and dealer auction markets, respectively. On average, the market spread for these IBIS and Nasdaq stocks is the same, but for the 10 most active stocks in each market, IBIS spreads are considerably lower. For these latter stocks, IBIS spreads change in a predictable manner throughout the day. Nasdaq spreads do not. The critical factor appears to be the unrestricted access of suppliers of immediacy that is distinctive for agency auction markets.     

ESTIMATING PERSON‐CENTERED TREATMENT (PeT) EFFECTS USING INSTRUMENTAL VARIABLES: AN APPLICATION TO EVALUATING PROSTATE CANCER TREATMENTS

This paper builds on the methods of local instrumental variables developed by Heckman and Vytlacil (1999, 2001, 2005) to estimate person‐centered treatment (PeT) effects that are conditioned on the person's observed characteristics and averaged over the potential conditional distribution of unobserved characteristics that lead them to their observed treatment choices. PeT effects are more individualized than conditional treatment effects from a randomized setting with the same observed characteristics. PeT effects can be easily aggregated to construct any of the mean treatment effect parameters and, more importantly, are well suited to comprehend individual‐level treatment effect heterogeneity. The paper presents the theory behind PeT effects, and applies it to study the variation in individual‐level comparative effects of prostate cancer treatments on overall survival and costs. Copyright © 2013 John Wiley & Sons, Ltd.     

A real‐option rationale for investing in excess capacity

Excess capacity is expensive, yet persistent excess capacity is widely observed in the corporate sector. Using a real‐option approach to capacity planning, this paper shows that under certain conditions it is optimal to invest in long‐term (even permanent) excess capacity. This results from the asymmetric nature of operating flexibility resulting from excess capacity—the ability to increase output under favorable demand shocks. The model is used to identify conditions under which excess capacity is more likely to be optimal. The implications are generally consistent with existing empirical evidence from studies on excess capacity and capacity utilization. Copyright © 2008 John Wiley & Sons, Ltd.     

A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology

There are many opportunities and challenges in area of Indian technical education due to liberalization and globalization of economy. One of these challenges is how to assess performance of technical institutions based on multiple criteria. This paper is focused on performance evaluation and ranking of seven Indian Institute of Technology (IITs) in respect to stakeholders’ preference using an integrated model consisting of fuzzy AHP and COPRAS. Findings based on 2007–2008 data show that performance of two IITs need considerable improvement. To the best of our knowledge it is one of few studies that evaluates performance of technical institutions in India.