Evaluating museum visitor experiences based on user-generated travel photos

ABSTRACT

This research introduces online travel photos published on social media platforms as a complementary data resource to examine the behavior and experience of museum visitors. The practical value of online travel photos is demonstrated through a case study of popular Hong Kong museums, particularly by using the photo content and metadata available from the Flickr platform. The proposed approach is a generic method for understanding museum visitor behavior and preferences, and supports museum practitioners in developing improved products for visitors. The case study findings are particularly beneficial for tourism managers, especially those in Hong Kong, in promoting and attracting tourists to visit local museums.     

Embedding Ethics: Dialogic Partnerships and Communitarian Business Ethics

Although emotion has become one of the most popular research areas within organizational scholarship, few studies have considered its connection with unethical behavior. Using dual-process theory, we expand on the rationalist perspective within the field of behavioral ethics by considering the process through which two discrete emotions, anger and guilt, influence unethical behavior. Across two studies using different methodologies, we found that anger increases unethical behavior whereas guilt reduces unethical behavior. These effects were mediated by impulsive and deliberative processing. Overall, our results shed light on distinct mechanisms through which emotions can influence unethical behavior. Both theoretical and practical implications are discussed.     

An item response theory approach to constructing and evaluating brief and in-depth financial literacy scales

We applied item response theory (IRT) to construct and evaluate new brief and in-depth financial literacy scales. A survey of a UK adult sample (N = 589) included 50 questions to assess knowledge about managing financial resources and competence in using personal finance-related information—including five widely used items, on interest rates, inflation, investment diversification, mortgages and bonds. IRT applied to a scale of these items identified some limitations, overcome via further iterations to construct a new brief scale with sound psychometric properties. IRT was then applied iteratively to our pool, resulting in an in-depth, 20-item scale, also psychometrically sound, covering four broad financial domains: everyday money transactions; the concept of money; borrowing; and saving and investment. Parallel 10-item sub-scales were also evaluated. The validity of the new scales was demonstrated by regression analyses which found that, controlling for demographic variables, financial literacy predicted key indicators of financial well-being.     

The Euro Illusion in Consumers’ Price Estimation: An Italian–Irish Comparison in the Third Year of the Euro

The euro illusion is a transient phenomenon that consists of currency-related asymmetries in the intuitive judgment of product prices made by consumers. The results of a cross-country study in the third year after the introduction of the euro show a strong price estimation asymmetry in a country with an extreme exchange rate (Italy) and a weaker effect in a country in which the nominal values of the new and the old currency are much closer (Ireland). These results rule out proposed explanations of the euro illusion in price estimation that assume the sole influence of plausible anchors (reference prices stored in memory within the plausible price range), supporting instead accounts also endorsing the role of implausible anchors (reference prices outside the plausible price range). Beyond contributing to our theoretical understanding of the euro illusion, this research starts to unveil the interplay between structural factors (i.e., the currency exchange rate) and psychological mechanisms that produce long-lasting difficulties for consumers after a monetary changeover.

The Ethical Mutual Fund Performance Debate: New Evidence from Canada

Although the academic interest in ethical mutual fund performance has developed steadily, the evidence to date is mainly sample-specific. To tackle this critique, new research should extend to unexplored countries. Using this as a motivation, we examine the performance and risk sensitivities of Canadian ethical mutual funds vis-à-vis their conventional peers. In order to overcome the methodological deficiencies most prior papers suffered from, we use performance measurement approaches in the spirit of Carhart (1997, Journal of Finance 52(1): 57–82) and Ferson and Schadt (1996, Journal of Finance 51(2): 425–461). In doing so, we investigate the aggregated performance and investment style of ethical and conventional mutual funds and allow for time variation in the funds’ systematic risk. Our␣Canadian evidence supports the conjecture that any␣performance differential between ethical mutual funds and their conventional peers is statistically insignificant.      

Crude oil price forecasting based on internet concern using an extreme learning machine

The growing internet concern (IC) over the crude oil market and related events influences market trading, thus creating further instability within the oil market itself. We propose a modeling framework for analyzing the effects of IC on the oil market and for predicting the price volatility of crude oil’s futures market. This novel approach decomposes the original time series into intrinsic modes at different time scales using bivariate empirical mode decomposition (BEMD). The relationship between the oil price volatility and IC at an individual frequency is investigated. By utilizing decomposed intrinsic modes as specified characteristics, we also construct extreme learning machine (ELM) models with variant forecasting schemes. The experimental results illustrate that ELM models that incorporate intrinsic modes and IC outperform the baseline ELM and other benchmarks at distinct horizons. Having the power to improve the accuracy of baseline models, internet searching is a practical way of quantifying investor attention, which can help to predict short-run price fluctuations in the oil market.