The promise and peril of dynamic targeted pricing

Dynamic pricing is widely adopted in many industries, such as travel and insurance. These industries are also gaining extensive capabilities in identifying and segmenting customers, partly fueled by the increasing availability of data. It is natural to ask whether firms should take advantage of such developments by charging different prices to different customer segments. If so, under what conditions? We seek answers to these highly managerially relevant questions.We consider a market with two customer segments served by a monopolist. The monopolist can choose among a set of pricing strategies to exploit consumers’ inter-temporal preferences and/or inter-segment variations. At one end of the spectrum, the firm can charge a constant price to all customers, which is called static pricing. At the other end of the spectrum, the firm can charge different prices to different customer segments and vary these prices over time, which is referred to as dynamic targeted pricing. We systematically compare these alternative pricing strategies. We show that dynamic pricing without targeting can be more effective than static targeted pricing when customers are not very forward looking, which corroborates the findings in the empirical literature. Interestingly, we find that the monopolist can be worse off when she adopts targeting in addition to dynamic pricing. We conduct laboratory experiments to test several key model predictions. The studies show that individuals behave in a manner consistent with the predictions of our model.     

Financial stress,sovereign debt and economic activity in industrialized countries: Evidence from dynamic threshold regressions

We analyze how the impact of a change in the sovereign debt-to-GDP ratio on economic growth depends on the level of debt, the stress level on the financial market and the membership in a monetary union. A dynamic growth model is put forward demonstrating that debt affects macroeconomic activity in a non-linear manner due to amplifications from the financial sector. Employing dynamic country-specific and dynamic panel threshold regression methods, we study the non-linear relation between the growth rate and the debt-to-GDP ratio using quarterly data for sixteen industrialized countries for the period 1981Q1-2013Q2. We find that the debt-to-GDP ratio has impaired economic growth primarily during times of high financial stress and only for countries of the European Monetary Union and not for the stand-alone countries in our sample. A high debt-to-GDP ratio by itself does not seem to necessarily negatively affect growth if financial markets are calm.     

Same as it ever was? Europe's national borders and the market for corporate control

National borders continue to be strong barriers for mergers and acquisitions in Europe. Using regional data, we construct a gravity model and find that the restraining impact of national borders decreased by more than 17 percent between 1991 and 2007. However, no significant change has occurred since the mid-1990s (i.e., four years before the introduction of the euro). In comparison, we run a corresponding analysis in the United States using the 10 federal regions as country equivalents. The resulting ‘quasi-border’ effect in the United States is weaker than that in the European Union. Yet its decline by 43 percent is much stronger in the same period. We conclude that European integration policy has had little effect on fostering M&A cross-border transactions.     

Dynamic DEA models with network structure: An application for Iranian airlines

Efficiency estimation of interdependent divisions within a company or assessing the interrelated processes in a production system provides insights for improving the operational performance. Recent developments in network data envelopment analysis (NDEA) models enable decision making units (DMUs) to be informed of inefficient processes within the system. The NDEA model assesses the processes of the system in a specific moment and ignores the dynamic effects within the production processes. Thus, without considering the temporal dimension of production processes, biased efficiency measurement will be obtained that provides misleading information to DMUs. For evaluating the performance of a DMU with interrelated processes during specified multiple periods, this paper proposes a relational dynamic NDEA (DNDEA) model which measures the efficiencies of the system and its internal processes over the time, simultaneously. To illustrate the capability of the proposed model, this study for the first time measures the efficiency of eight Iranian airlines in several periods connected to each other by carry over flows. The actual data is gathered in three periods from 2010 to 2012 and the results are compared with the dynamic DEA and network DEA models in the same time span.     

Time heals many wounds – explaining the immediate and delayed effects of message sidedness

This study investigates the immediate and delayed effects of advertising messages including both positive and negative information. A two-sided message has a negative effect on message attitudes due to two mediating variables with trade-off effects: valence and balance. These two variables are also responsible for the alignment of the effect of sidedness on message attitudes and purchase intentions over time: the negative effects of two-sided messages are neutralized over time because negative information is reevaluated, improving the valence of the message. The results explain the negative effects of message sidedness that have been found in prior research and they show that a two-sided message in advertising is not necessarily inferior to a one-sided message despite unfavorable short-term effects.     

FIRE SALES FORENSICS: MEASURING ENDOGENOUS RISK

We propose a tractable framework for quantifying the impact of loss‐triggered fire sales on portfolio risk, in a multi‐asset setting. We derive analytical expressions for the impact of fire sales on the realized volatility and correlations of asset returns in a fire sales scenario and show that our results provide a quantitative explanation for the spikes in volatility and correlations observed during such deleveraging episodes. These results are then used to develop an econometric framework for the forensic analysis of fire sales episodes, using observations of market prices. We give conditions for the identifiability of model parameters from time series of asset prices, propose a statistical test for the presence of fire sales, and an estimator for the magnitude of fire sales in each asset class. Pathwise consistency and large sample properties of the estimator are studied in the high‐frequency asymptotic regime. We illustrate our methodology by applying it to the forensic analysis of two recent deleveraging episodes: the Quant Crash of August 2007 and the Great Deleveraging following the default of Lehman Brothers in Fall 2008.     

Price promotion with reference price effects in supply chain

We consider the price promotion in a supply chain comprising one manufacturer and one retailer, who take into account the reference price effects of consumers. The problem is analyzed as a manufacturer-lead Stackelberg game. The results indicate that reference price effects could mitigate “double marginalization” effects, and improve the channel efficiency. We also show that the optimal price promotion benefits the manufacturer, retailer and consumers in consumer promotion model. Furthermore, we provide the conditions under which the retailer has an interest in offering price promotion to consumers. Finally, we employ numerical analysis to demonstrate more managerial insights.     

Sentiment,mood and outbound tourism demand

We investigate spillover effects from sentiment and mood shocks on US outbound tourism demand from 1996 until 2013. We use the Index of Consumer Sentiment and Economic Policy Uncertainty Index as proxies for sentiment and the S&P500 as a proxy for mood. We find a moderate to high interrelationship among sentiment, mood and outbound tourism demand. More importantly, sentiment and mood indicators are net transmitters of spillover shocks to outbound tourism demand. The magnitude of spillover effects sourced by sentiment and mood is time-varying and depends on certain socio-economic and environmental events. Our results have important implications for policymakers and travel agents in their efforts to predict tourism arrivals from key origin countries and to plan their tourism strategy.     

A tourist kit ‘made in Italy’: An ‘intelligent’ system for implementing new generation destination cards

This study investigates the advantages and the potentiality of the ‘tourist kit’, an Italian solution based on the concept of a prepaid card that is issued by a large postal operator. The destination card can be reloaded by tourists according to their needs and its validity is not restricted to short periods. Thus, the kit provides tourists with an integrated, practical, and flexible tool capable of making their stay more enjoyable as it allows cardholders to choose and buy many products and services at discounted prices. The kit creates customer loyalty by utilising smart technology aimed at collecting accurate tourist information. This model deserves attention because it is probably the world's first case of a large postal operator entering the tourism sector with the proposal of an integrated and advanced destination card scheme. This research also discusses interesting opportunities and challenges related to the implementation of new generation tourist cards.     

Mobile technology & resident attitude research

This research note highlights the novelty of integrating location-based services (LBS) available on Smart Phones and Tablets into traditional resident attitude survey methodologies such as door-to-door data collection. It specifically reviews how the LBS technology available on mobile devices can be used to systematically capture GPS coordinates of one's residence and integrate this captured spatial information into software such as ArcGIS and SPSS for further analysis. By having GPS coordinates associated with respondents' answers, researchers have an additional layer of information available for conducting a multitude of tests previously not possible with subjective categorical spatial data. Two research applications using the spatial location of residences are provided as examples of how LBS available on mobile devices can be integrated within resident attitude projects. The use of LBS technology can help researchers better understand how the distance residents live from major tourist attractions influences their attitudes towards tourism.