Technological Diversification, Coherence, and Performance of Firms

Technological diversification at the firm level (i.e., the expansion of a firm's technology base into a wide range of technology fields) is found to be a prevailing phenomenon in all three major industrialized regions,—the United States, Europe, and Japan—prompting the term multitechnology corporation. Whereas previous studies have provided insights into the composition of technology portfolios of multitechnology firms, little is known about the relationship between technological diversification and firms' technological performance. Against a backdrop of the technology and innovation management literature, the present article investigates the relationship between technological diversification and technological performance, taking into account the moderating role of technological coherence in firms' technology portfolios. Hereby, technological coherence is defined as the degree to which technologies in a technology portfolio are technologically related. To measure the technological coherence of portfolios, a measure of technological relatedness of technology fields is constructed based on patent citation patterns found in 450,000 European Patent Office (EPO) patent grants. Two hypotheses are presented here: (1) Technological diversification has an inverted U‐shaped relationship with technological performance; and (2) technological coherence moderates the relationship between technological diversification and technological performance positively. These hypotheses are tested empirically using a panel data set (1995–2003) on patent portfolios pertaining to 184 U.S., European, and Japanese firms. The firms selected are the largest research and development (R&D) actors in five industries: pharmaceuticals and biotechnology; chemicals; engineering and general machinery; information technology (IT) hardware (i.e., computers and communication equipment); and electronics and electrical machinery. Empirical results, obtained by fixed‐effects negative binomial regressions, support both hypotheses in the present article. Technological diversification has an inverted U‐shaped relationship with technological performance. Technological diversification offers opportunities for cross‐fertilization and technology fusion, but high levels of diversification may yield few marginal benefits as firms risk lacking sufficient levels of scale to benefit from wide‐ranging technological diversification, and firms may encounter high levels of coordination and integration costs. Further, the results show that the net benefits of technological diversification are higher in technologically coherent technology portfolios. If firms build up a technologically coherent diversified portfolio, the presence of sufficient levels of scale is ensured and coordination costs are limited. At the same time, technologically coherent diversification puts firms in a better position to benefit form cross‐fertilization between technologies. The present article clearly identifies the important role of technological coherence in technology diversification strategies of firms.     

The Gilt-Equity Yield Ratio and the Predictability of UK and US Equity Returns

A number of financial variables have been shown to be effective in explaining the time-series of aggregate equity returns in both the UK and the US. These include, inter alia , the equity dividend yield, the spread between the yields on long and short government bonds, and the lagged equity return. Recently, however, the ratio between the long government bond yield and the equity dividend yield – the gilt-equity yield ratio – has emerged as a variable that has considerable explanatory power for UK equity returns. This paper compares the predictive ability of the gilt-equity yield ratio with these other variables for UK and US equity returns, providing evidence on both in-sample and out-of-sample performance. For UK monthly returns, it is shown that while the dividend yield has substantial in-sample explanatory power, this is not matched by out-of sample forecast accuracy. The gilt-equity yield ratio, in contrast, performs well both in-sample and out-of-sample. Although the predictability of US monthly equity returns is much lower than for the UK, a similar result emerges, with the gilt-equity yield ratio dominating the other variables in terms of both in-sample explanatory power and out-of-sample forecast performance. The gilt-equity yield ratio is also shown to have substantial predictive ability for long horizon returns.     

Calibrating DRASTIC using field measurements,sensitivity analysis and statistical methods to assess groundwater vulnerability

The objective of this research is to indicate how the vulnerability potential to pollution may be assessed more accurately by correcting both the ratings and weights of the parameters used in the popular EPA DRASTIC method. In order to demonstrate the applicability of the proposed method, the Astaneh Aquifer located in northern Iran was selected. Nitrate concentrations were used to correlate the pollution potential in the aquifer to the DRASTIC index. The results indicated that the modified DRASTIC was significantly superior to the original method.     

Inflation and Economic Growth: Evidence from the Southern African Development Community

In this paper, we investigate the role of inflation rates in determining economic growth in 15 sub‐Saharan African countries, which are all members of the Southern African Development Community, between 1980 and 2009. The results, based on panel time‐series data and analysis (we use the fixed effects and fixed effects with instrumental variables estimators to account for heterogeneity and endogeneity in thin panels), suggest that inflation has had a detrimental effect to growth in the community. We highlight that inflation has offset the Mundell–Tobin effect and consequently reduced the much needed economic activity in the community, and also the importance of an institutional framework conducive to a stable macroeconomic environment as a precondition for development and prosperity in the community.     

The Difference a Smile Makes: Effective Use of Imagery by Children’s Nonprofit Organizations

ABSTRACT

Which emotions are most appealing to donors in nonprofit outreach materials? Previous studies have shown that in print and television materials, images depicting negative emotions lead to increases in donor response. In this study, we examined whether images of negative affect in children in social media appeals lead to increased information sharing compared to positive or neutral images of children. We analyzed Facebook posts from 2016 from 2 large children’s nongovernmental organizations, UNICEF USA and Save the Children US, and examined the relationship between the type of emotion in the image and the number of likes, comments, and shares that the post received. We found differences in the responses according to the organization sending the message and the affect of the children depicted. For Save the Children US, negative images, specifically sad and fearful images, generated significantly more likes, shares, and comments. For UNICEF USA, there was no difference in information sharing for positive, neutral, or negative images. Findings from this study demonstrate that negative emotional imagery of children can affect social media engagement with nongovernmental organizations, but this effect appears to be inconsistent.     

Applications of the behavioural homogeneity evaluation framework: The predictive ability of consumer involvement for international food market segmentation

Abstract

This article proposes a framework of alternative international marketing strategies, based on the evaluation of intra- and inter-cultural behavioural homogeneity for market segmentation. The framework developed in this study provides a generic structure to behavioural homogeneity, proposing consumer involvement as a construct with unique predictive ability for international marketing strategy decisions. A model-based segmentation process, using structural equation models, is implemented to illustrate the application of the framework.     

Do we need a global VAR model to forecast inflation and output in South Africa?

This study determines whether the global vector autoregressive (GVAR) approach provides better forecasts of key South African variables than a vector error correction model (VECM) and a Bayesian vector autoregressive (BVAR) model augmented with foreign variables. The article considers both a small GVAR model and a large GVAR model in determining the most appropriate model for forecasting South African variables. We compare the recursive out-of-sample forecasts for South African GDP and inflation from six types of models: a general 33 country (large) GVAR, a customized small GVAR for South Africa, a VECM for South Africa with weakly exogenous foreign variables, a BVAR model, autoregressive (AR) models and random walk models. The results show that the forecast performance of the large GVAR is generally superior to the performance of the customized small GVAR for South Africa. The forecasts of both the GVAR models tend to be better than the forecasts of the augmented VECM, especially at longer forecast horizons. Importantly, however, on average, the BVAR model performs the best when it comes to forecasting output, while the AR(1) model outperforms all the other models in predicting inflation. We also conduct ex ante forecasts from the BVAR and AR(1) models over 2010:Q1–2013:Q4 to highlight their ability to track turning points in output and inflation, respectively.     

Salesforce decisions: A Markovian approach

This paper reports on the development, application, and evaluation of a Markov model used for macro sales force planning and control. The model portrays the succession of levels of sales force members from application to join the sales force, through all possible states, including possibilities of termination due to promotion, firing, and voluntary departures. The impact of several decision states such as recruiting, promotion, and training are then assessed, and the implications are evaluated through the use of the data from two large pharmaceutical firms. Several uses of the model are illustrated and the impact of managerial decisions on costs and profits are shown. The uses of the model for sales force design are also discussed.