Frequent acquirers and management compensation

We find positive contemporaneous, short-, and long-run effects of an increase in the acquisition rate on management compensation. A positive bidirectional causality exists between acquisition frequency and management compensation. A higher firm value is likely to associate with higher acquisition frequency. Acquisition rate has a positive impact on the market share. Acquirers with lower market share are more likely to become frequent acquirers. A causal order follows from lower market share to higher acquisition frequency to higher firm value to higher management compensation. The impact of acquisition frequency on management compensation is higher for value-enhancing acquirers relative to value-destroying acquirers.     

Positive versus negative comparative advertising

Two studies examined cognitive responses to comparative advertising that was valenced, i.e., was either negative or positive. Negative comparative advertising featured the advertised brand derogating the comparison brand (I'm OK, you're not OK). Positive comparative advertising claimed superiority over the comparison brand in a nonderogatory manner (You're OK, I'm more OK). Subjects were exposed to either a negative comparative ad or a positive comparative ad. In study 1, the ad featured either a high or low share advertised brand and either a high or low share comparison brand while in study 2, the ad featured advertised and comparison brands with either a strong or a weak reputation. Across both studies, it was found that negative comparative advertising evoked significantly higher counterargumentation and lower claim acceptance than its positive counterpart. Also, when the advertised brand had a high share relative to the comparison brand, counterargumentation was lower and claim acceptance was higher vis-a-vis when the advertised brand had a low share relative to the comparison brand. Findings pertaining to brand reputation were mixed. Managerial and future research implications of the findings are discussed.     

Knowledge Management in Supply Chains: The Role of Explicit and Tacit Knowledge

We theorize, building on the knowledge‐based view and the theoretical distinction between explicit and tacit knowledge, that knowledge management capability across the supply chain manifests itself in explicit and tacit knowledge, which in turn effectuates supply chain performance. The model is tested with survey data from 195 small‐ and medium‐sized enterprises reporting on their primary supply chain. The results indicate that the supply chain's knowledge management capability manifests itself in both explicit and tacit knowledge, with the latter being influenced more strongly. Moreover, it was found that while both explicit and tacit knowledge influence supply chain performance, the latter exerts a significantly greater impact than the former. Exploratory post hoc analyses add robustness to these findings and investigate mechanisms inherent to the transformation of tacit into explicit knowledge. Overall, this research contributes to academic theory development in logistics and supply chain management by the dichotomization of knowledge types and the demonstration of their differential magnitude of effects, and to managerial practice by providing important guidance for logistics managers structuring their knowledge management efforts across supply chains.     

Financial crises and labor market turbulence

Financial crises in emerging markets trigger a significant reallocation of labor as exchange rate depreciations and interest rate increases cause relative prices to change drastically. Household survey data for Mexico reveal that individuals who switched industry or occupation during the 1994–1995 crisis lost about 10% of their hourly earnings on average compared to similar workers who did not move. This suggests that many workers became less productive in the process of migrating to different economic activities. These productivity losses, in turn, can explain about 40% of the observed fall in TFP in Mexico in 1995.     

Farmers' Preference for Farming: Evidence From a Nationally Representative Farm Survey in India

Using data from a nationally representative farm survey in India, we have analyzed Indian farmers' stated preference for farming as a profession. Findings show that more than 40% of farmers dislike farming as a profession because of low profits, high risk, and lack of social status, yet they continue with it owing to a lack of opportunities outside agriculture. Farmers who express a preference for moving out of agriculture are mostly those with small landholdings, poor irrigation facilities, fewer productive assets including livestock, and follow a cereal‐centric cropping pattern. They also have relatively lower access to credit, insurance, and information, and are weakly integrated with social networks such as self‐help groups and farmers' organizations. Importantly, the disinclination for farming, conditional on other covariates, is not significantly differentiated by caste, an important indicator of social status in rural India. Yet, within a caste group, the dislike for farming moderates with larger landholdings.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.     

The Effect of Probability Distribution Functions of Economic Life on Retirement Alternatives

Economic analysis, supported by computer hardware and software, can easily overwhelm a decision maker with data. However, this data can be organized in a readily understandable way using well-designed graphs. Some simple guidelines suggest substantial improvements over available examples from papers and textbooks. Although these graphs and sensitivity analyses are useful in many quantitative problems, the long-range focus of engineering economy and its concomitant uncertainty dramatically increase their value.