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The past several years have seen dramatic increases in oil prices, which have adversely impacted airlines, with the average price of jet fuel increasing from $1.34 per gallon between 1995 and 2005 to $2.81 per gallon between 2006 and 2009. As a partial response to these increases in costs, many airlines have introduced fees for services that were previously provided to their customers free of charge. One such charge is a fee on checked baggage, which most airlines introduced in 2008. These charges have been successful in increasing airline revenues, so successful that many airlines have increased their fees multiple times over the past two years. Baggage fees have also enabled airlines to avoid dramatic increases in their airfares, which may result in significantly fewer customers, as these additional fees generate revenues, but since they are not collected when passengers book their tickets, the cost of air travel on these airlines appears lower than it actually is. The most notable exception to this pattern of charging baggage fees is Southwest Airlines, which has launched a “Bags Fly Free” advertising campaign in an attempt to differentiate their product from that of fee charging airlines. In this chapter, we use a spatial autoregressive model to analyze what impact the increase in fuel costs, and the introduction of baggage fees have had on ticket prices. Our results suggest that increases in jet fuel prices are passed along to travelers in the form of higher ticket prices but that baggage fees actually reduce ticket prices, as airlines may substitute baggage fee revenue for ticket revenue to become more competitive on their airfare. We also find that Southwest Airlines has increased their ticket prices on routes in which they compete with fee charging firms, leveraging their “Bags Fly Free” product differentiation to increase their revenues.

In the last two decades, different policy initiatives have been set up to increase the share of intermodal freight transport through a modal shift. In the design of these policies, often critical break-even distances are set, showing the cost or price competitiveness of intermodal transport to delineate transport routes that qualify for such a modal shift. In this chapter, we discuss to which extent such break-even distances can be generalized on a larger scale and how they are calculated.

We use two price-based models to calculate break-even distances for an intermodal rail and an intermodal barge transport case. General break-even values do not show the price variation in the transport market and vagueness in the calculation of these values adds to this problem.

We find that for the inland waterway case, intermodal barge transport shows potential on shorter distances as well. In addition, different ways to lower the break-even distance are discussed and a framework for calculating break-even distances is suggested.

The research elaborates on break-even distances in a European context using price data which are fluctuating over time, location specific and often not publicly available.

Policy initiatives promoting intermodal transport should not focus solely on long distance transport. Moreover, evaluating the competitiveness of the intermodal sector solely on a price comparison dishonours its true potential.

This chapter challenges the current European policy on intermodal transport by showing the price competitiveness of intermodal transport in two cases.

The real estate market shows a number of distinctive features that are yet to be clearly understood at the theoretical level, because of the extreme complexity of its nature of both financial instrument and mere commodity. Moreover, as we know, a long lasting speculative bubble in the housing market was one of the main causes of the great recession. The aim of this chapter is to generate an index to explain how inclusive contextual factors influence the price level of real estate in Genoa, Italy. The authors use the non-parametric methodologies of factor analysis and cluster analysis. The results of the analysis suggest that most of the variability in the fluctuation of the average price of properties is strictly connected to the features of the reference context (such as neighbourhood prestige, type and level of education of residents, access to services, etc.). However, the percentage of unjustified price variability is assumed to refer to the incidence of the intrinsic variables of the estate assets.

This chapter presents projections of residential development in Wappinger Creek watershed of Dutchess County, New York in the Hudson River Valley. A spatial econometric model is developed based on data from a geographical information system (GIS) of county-level socio-economic trends, tax parcel attributes, town-level zoning restrictions, location variables, and bio-geophysical constraints including slope, soil type, riparian and agricultural zones. Monte Carlo simulation is employed to distribute spatially explicit projections of land-use change under various residential development scenarios. Scenario analysis indicates the likelihood of continued residential, decentralized development patterns in formerly agricultural and forested parcels. Policy scenarios demonstrate possible courses of action to direct development and protect watershed health.

Objective – The current biotechnology revolution has been associated with newly developed genetic modifications (GM) that offer new prospects for increasing agricultural productivity. This has stimulated a rapid adoption of GM corn hybrids by U.S. farmers. Yet, there is concern about the structure of competition among biotech firms that own patents over GM traits. This chapter evaluates the spatial differences in pricing of biotech corn hybrids, with a focus on the fringe versus core regions of the U.S. Corn Belt.

Methods – The analysis examines how local conditions and market concentrations affect the pricing of GM corn hybrids in different locations.

Results – We find evidence of more extensive subadditive pricing in the fringe region. We also examine how both own- and cross-market concentrations affect prices across regions. For GM hybrids, the results show that market power is generally more prevalent in the core region compared to the fringe.

Conclusions – The evidence shows that the pricing of GM corn hybrids varies across space. The observed pricing schemes benefit farmers more in the fringe than in the core region of the Corn Belt.

Customer experience is a relevant concept in marketing and tourism research since its correct understanding allows companies to achieve competitive advantage and service providers can reach several outcomes such as customer engagement, loyalty, and customer satisfaction. This chapter aims to analyze one of the main outcomes of the customer experience, the customer satisfaction through online reviews, and using spatial analysis as a tool to incorporate the contextual nature of the customer experience. Thus, our study considers online rating as a measure of customer satisfaction and tries to analyze the impact of actions under the control of the service provider (price and objective quality) and actions under the control of the customer (subjective quality) on customer satisfaction.

With the Spanish hotel industry as a study framework, an empirical study is developed to analyze, through geographically weighted regression techniques, the relationship between price, objective quality and subjective quality, and online ratings given by consumers with a sample of 1870 of geolocated hotels in Spain. The findings show how a premium price, depending on the geolocation, is an indicator for better customer experiences, and they also show that objective quality is the antecedent of customer experience whose positive effect on customer satisfaction is geographically more widespread. Results show contradictory effects of subjective quality, while in some areas subjective quality does not match the product fit of customers, in others it allows hotels to provide more satisfactory experiences.