The Cost Efficiency of Real Estate Investment Trusts: An Analysis with a Bayesian Stochastic Frontier Model

Using a stochastic frontier methodology that incorporates Bayesian statistics, this paper analyzes the cost efficiency of real estate investment trusts (REITs) by observing the deviations of the measured costs of individual REITs from a defined efficient cost frontier. Using 1995–1997 data, we extend the previous research in this area and measure REIT efficiency more precisely by isolating random measurement error from the overall deviations from the efficient cost frontier. We calculate the magnitude of each REIT's managerial inefficiency, the industry inefficiency, and returns to scale. In addition, we assess specific characteristics of REITs for their contribution to inefficiency by calculating the odds ratio that a REIT with a specific characteristic is more efficient than a REIT with an alternative characteristic. The results show that, for the years studied, REITs are relatively cost efficient with most REITs facing increasing returns to scale. Additionally, the REIT's use of debt and the REIT's management style significantly affect the cost performance of REITs during the aforementioned time period. Finally, diversification across property types, as measured, does not seem to influence REIT cost efficiency.     

Households transport-home energy conservation strategies in response to energy price policies: A stated adaptation experiment based on portfolio choices and cross effects designs

This article explores consumer investment choice in long-term energy conservation technology and assesses trade-offs in energy saving behaviour between the housing and transportation domains. The long-term energy conservation choice problem is conceptualized as a portfolio choice problem. Consequently, to measure trade-offs between investments in housing and transport options, a cross effects choice design is developed in which respondents were shown one or more alternate ways to reduce their current energy consumption: (1) investing in new technology in the house, such as solar panels; (2) exchanging the current car for a more energy efficient car; (3) buying a new energy-efficient car, such as EV or solar car; (4) moving house to reduce current travel distances. To help respondents linking these options to their current energy consumption, a new Web-based survey system (SINA) to implement and administer stated adaptation experiments was developed. The system was used to collect two sets of data. First, data about out-of-home and in-home energy consumption, together with detailed time use data, was collected. Second, using a cross effects design, respondents were asked to select a portfolio of energy-saving strategies in response to different energy pricing policy scenarios. Results reported in this paper are based on 572 respondents who completed the survey and responded to seven adaptation questions based on their current energy expenditures. A random parameters logit model is estimated to predict the probability of choosing a particular portfolio of energy-saving options. Estimation results indicate that individuals from different socio-demographic groups exhibit varied preferences. The saving option characteristics, especially cost related characteristics have significant effects on individuals' preferences. Moreover, the results also showed significant effects of choice set composition on energy saving options. Further, the energy pricing policies had showed mixed effects on individual's preferences.     

Money Allocation to Out-of-Home Leisure Activities and the Organization of These Activities in Time and Space

Monetary budgets influence activity participation and related travel as they demarcate limits on how people organize their activities in time and space. In this paper, we are interested in money allocation to out-of-home leisure activities and how this is affected by duration, sociodemographics, and time-location variables. Analyses were carried out by applying a seemingly unrelated regression model to a leisure activity data set. The analyses revealed that expenditures for out-of-home leisure activities are influenced by the variables mentioned above. Moreover, the results indicate that there is a substitution between expenditure of each activity.     

Who produces for whom in the world economy?

Abstract For two decades, the share of trade in inputs, also called vertical trade, has been dramatically increasing. In reallocating trade flows to their original input‐producing industries and countries, this paper suggests a new measure of international trade: ‘value‐added trade’ and makes it possible to answer the question ‘who produces for whom?’ In 2004, 27% of international trade was vertical trade. The industrial and geographic patterns of value‐added trade are very different from those of standard trade. Value‐added trade is relatively less important in regional trade but the difference is not more important for Asia than for America.     

Exploring the use of travel information – identifying contextual market segmentation in Seoul, Korea

As the amount of information is rapidly growing, and ubiquitous urban environments are emerging, the question which kind of information to provide is a major challenge for commercial and public travel-information service providers alike. This paper reports the analyses of recent data, collected in Metropolitan Seoul, about the acquisition of travel information. The study applies CHAID analysis to find homogeneous segments in travel information acquisition. Findings indicate that contextual variables are crucial to explain information acquisition behaviour, depending on decision context. The implication is that both socioeconomic and contextual variables are important to better understand the acquisition (and provision) of travel information. The results have important implications for managers and policy-makers, in particular in the way they respond to dynamic, contextual market segmentation.     

Imputing relevant information from multi-day GPS tracers for retail planning and management using data fusion and context-sensitive learning

It is well known that the right location of shopping centres is of paramount importance. Unless stores succeed in attracting their own clientele, they rely to a large extent on the impulse behaviour of shoppers. To evaluate alternative locations, models of pedestrian behaviour may be useful. Modern technologies such as GPS and RFID offer new possibilities providing data on routes and stops, which are required as input for such models. An automatic interpretation of GPS tracers with respect to the activities being conducted could enhance the applicability of such technologies to retail management applications. This paper reviews this rapidly growing literature, and shows how automatic data imputation can be established by using Bayesian belief networks and how GPS traces can be fused with land use data of retail location.     

Issues which Impact upon Marketing in the Small Firm

Defining the small firm is somewhat arbitrary as criteria used to classify entities as such include size, number of employees, sales volume, asset size, type of customer, capital requirements and market share. There is, however, general agreement that smallness and newness create specific difficulties for business. Furthermore, there is widespread acceptance of the notion that small firms typically possess certain characteristics, which serve to differentiate them from larger organisations. These characteristics include inherent weaknesses with respect to capitalisation and marketing awareness and practice. Small firms are perceived as vulnerable yet valuable entities, important both economically and socially. High failure rates of small firms are largely attributed to weaknesses in financial management and marketing. Many classical management concepts are unsuitable for application in a small firm context, with research suggesting non-implementation of theoretically based marketing practice is the rule rather than the exception in the small firm. This paper reviews issues pertaining to marketing practice in the small firm. It examines the absence of agreed definitions of "the small firm" and "success" or "failure" of such entities, offers definitions for these terms, acknowledges the importance of small firms to the economy, reviews small firm characteristics, acknowledges inherent weaknesses with regard to finance and marketing in small firms, reviews marketing practice in the context of small firm characteristics, and considers the roles of marketing educators and owner/managers in improving small firm's marketing practice.     

Tradeoffs between sensory attributes and organic labels: the case of orange juice

Researchers have investigated the role of sensory attributes and organic labels on consumers’ preferences and perceptions of food, but few has examined whether sensory attributes are relevant for consumers who prefer organic food and the extent to which sensory attributes influence consumer's marginal willingness to pay for organic food. The objective of this study is to determine how sensory attributes and organic label work together to influence consumer's stated preference and marginal willingness to pay for orange juice. To achieve this, we conducted a blind sensory evaluation of two orange juices followed by a discrete choice experiment to determine the extent to which consumer's stated preference for orange juice labelled as organic is affected by sensory experience preceding the choice experiment. Random parameter logit models and latent class conditional logit models are used to explain stated preference. Results indicate that the effect of sensory attributes on consumer's marginal willingness to pay differed by organic juice and conventional juice.     

Experimental analysis of choice

Experimental choice analysis continues to attract academic and applied attention. We review what is known about the design, conduct, analysis, and use of data from choice experiments, and indicate gaps in current knowledge that should be addressed in future research. Design strategies consistent with probabilistic models of choice process and the parallels between choice experiments and real markets are considered. Additionally, we address the issues of reliability and validity. Progress has been made in accounting for differences in reliability, but more research is needed to determine which experiments and response procedures will consistently produce more reliable data for various problems.Sawtooth SoftwareDecision Research     

Risk Interpretation of the CAPM's Beta: Evidence from a New Research Method

This study tests the validity of using the CAPM beta as a risk control in cross‐sectional accounting and finance research. We recognize that high‐risk stocks should experience either very good or very bad returns more frequently compared to low‐risk stocks, that is, high‐risk stocks should cluster in the tails of the cross‐sectional return distribution. Building on this intuition, we test the risk interpretation of the CAPM's beta by examining if high‐beta stocks are more likely than low‐beta stocks to experience either very high or very low returns. Our empirical results indicate that beta is a strong predictor of large positive and large negative returns, which confirms that beta is a valid empirical risk measure and that researchers should use beta as a risk control in empirical tests. Further, we show that because the relation between beta and returns is U‐shaped, that is, high betas predict both very high and very low returns, linear cross‐sectional regression models, for example, Fama–MacBeth regressions, will fail on average to reject the null hypothesis that beta does not capture risk. This result explains why previous studies find no significant cross‐sectional relation between beta and returns.