Effects of scale economies and production seasonality on optimal hub locations: the case of regional fresh produce aggregation

Interest in supporting local and regional food systems is rising and food hubs have attracted considerable attention among Federal, State, and local policymakers. This study explores the problem of endogenous hub location in fresh produce value chains in the Northeastern United States. To overcome limitations in the literature, we incorporate the effects of economies of scale and production seasonality into our models. Three experimental models are designed to examine the effects of alternatively applying yearly, quarterly, and monthly data on model solutions. We explicitly assess how interactions of scale economies and seasonality influence the structure and spatial attributes of an optimal regional produce aggregation hub system. The three models generate marketed different solutions and in many respects they lead to different conclusions about developing local/regional supply chains. The monthly model allows for production seasonality and actual hub operation cycle frequency and thus leads to more efficient hub solution with rich policy implications.     

The quality of cooking oil used in informal food processing in Malawi: a preliminary study

A survey was conducted in Lilongwe city urban markets in Malawi, to assess the quality of cooking oil used for frying potato chips. Purposive sampling was performed to come up with respondents who were using vegetable oils. A stratified random sampling was used to select the 32 informal food processors who were interviewed using a structured questionnaire. Oil samples were collected from the most commonly used brand of oil. Fifteen respondents were selected and these were divided into three categories of five: those who were not reusing the oil, those who were reusing the oil and those who were preparing potato chips and chicken in the same oil, for chemical analysis. The preliminary results showed that while the majority (59.4%) of the informal food processors discarded the oil after 1 day, 3.1% discarded it after 4 days and another 12.5% after 3 days. A larger proportion of the respondents (40.6%) used the leftover oils at home, 37.5% kept it in oil bottles, 3.1% kept it in plastic papers for reuse the following day. Also, most respondents (57%) indicated dark colour as the sign of oil deterioration, 29% discarded the oil after noticing foam formation while 8.2% and 6.1% said they discarded the oil after noticing a bad smell and food absorbing the oils respectively. A physical observation of the various oils showed that for most of the respondents (34%), the oils were dark brown in colour, in 22%, the oils were slightly dark brown and 16%, the oils were brown. Foam formation was noticed in 13% of the respondents. It was also noted that 91% of the respondents had not been trained or briefed of food quality and safety issues. A chemical analysis of the oils showed high values of free fatty acids (range, 0.84–1.4112 compared with 0.42 in the fresh oil) and peroxide values (range 14.7–16.6 compared with 9.0 in the fresh oil). It may be concluded that the oils being used by the informal food processors in Malawi are of poor quality and so the foods cooked in them may be a health hazard to the consumers and the processors themselves. Although this work in ongoing, it may be recommended at the outset that the health department of the city assemblies should inspect these oils for the good health of the consumers.     

Creating the Customer: The Influence of Advertising on Consumer Market Segments – Evidence and Ethics

For over half a century market segments have been considered objective groupings of individuals which marketers identify, understand, and target with advertising messages. The process of market segmentation has, therefore, occupied a position of moral neutrality. An increasingly popular method of segmentation is by consumer personality, with advertisers targeting messages to specific personality types. This paper explores personality segmentation, and presents empirical evidence to support the proposition that personality metrics that are used to assign individuals to segments may, in fact, be manipulable by advertising executions themselves. Quite apart from the implications that this has for the business efficacy of the segmentation process, the ethical implications – particularly as applied to children – are considerable.     

The service sector of Cuba: An analysis and critique

The Cuban economy has experienced a significant increase in foreign direct investment over the past decade due to the end of the Soviet Union and the establishment of more liberal trade policies. Although the U.S. embargo of trade with Cuba still exists, there has been movement lately that suggests the end of the four‐decades‐old policy. The purpose of this article is to analyze the current Cuban business environment and to identify potential entrepreneurial opportunities in the service sector. Major trade partners are also reviewed and managerial implications discussed. © 2006 Wiley Periodicals, Inc.     

This is what the leading indicators lead

We propose an optimal filter to transform the Conference Board Composite Leading Index (CLI) into recession probabilities in the US economy. We also analyse the CLI's accuracy at anticipating US output growth. We compare the predictive performance of linear, VAR extensions of smooth transition regression and switching regimes, probit, non‐parametric models and conclude that a combination of the switching regimes and non‐parametric forecasts is the best strategy at predicting both the NBER business cycle schedule and GDP growth. This confirms the usefulness of CLI, even in a real‐time analysis. Copyright © 2002 John Wiley & Sons, Ltd.     

The Lifetime Distributional Impact of Government Health Outlays

This article examines the lifetime redistributive impact of government health outlays and finds that such outlays redistribute income from the lifetime rich to the lifetime poor and from men to women.     

Multivariate statistics in industrial marketing management: A practitioner tool kit

Much published work over the years has pointed to the differences between business-to-consumer (B2C) and business-to-business (B2B) marketing. An undesirable by-product of this sometimes misdirected distinction is that managers working within B2B environments have generally not considered the use of what are seen as B2C techniques, such as multivariate statistical analysis. This article is structured in three parts. First, the argument for the similarities between B2B and B2C marketing is developed; second, three different multivariate statistical techniques are presented and combined to form a practical tool kit for use by B2B managers on strategic, operational, and tactical levels; and third, the results of an application of the techniques in the life science research chemicals industry is reported, demonstrating that the tool kit substantially enhanced managerial understanding of customer decision processes.     

Persistence,mean reversion and non-linearities in the US housing prices over 1830–2013

The objective of this study is to provide a direct estimate of the degree of persistence of measures of nominal and real house prices for the US economy, covering the longest possible annual sample of data, namely 1830–2013. The estimation of the degree of persistence accommodates for non-linear (deterministic) trends using Chebyshev polynomials in time. In general, the results show a high degree of persistence in the series along with a component of non-linear behaviour. In general, if we assume uncorrelated errors, non-linearities are observed in both nominal and real prices, but this hypothesis is rejected in favour of linear models for the log-transformation of the data. However, if autocorrelated errors are permitted, non-linearities are observed in all cases, and mean reversion is found in the case of logged prices, though given the wide confidence intervals, the unit root null hypothesis cannot be rejected in these cases.     

Extracting Nonlinear Signals from Several Economic Indicators

We develop a twofold analysis of how the information provided by several economic indicators can be used in Markov switching dynamic factor models to identify the business cycle turning points. First, we compare the performance of a fully nonlinear multivariate specification (one‐step approach) with the ‘shortcut’ of using a linear factor model to obtain a coincident indicator, which is then used to compute the Markov switching probabilities (two‐step approach). Second, we examine the role of increasing the number of indicators. Our results suggest that one step is generally preferred to two steps, especially in the vicinity of turning points, although its gains diminish as the quality of the indicators increases. Additionally, we also obtain decreasing returns of adding more indicators with similar signal‐to‐noise ratios. Using the four constituent series of the Stock–Watson coincident index, we illustrate these results for US data. Copyright © 2014 John Wiley & Sons, Ltd.