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.     

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.     

Currency crisis early warning systems: Why they should be dynamic

Traditionally, financial crisis Early Warning Systems (EWSs) have relied on macroeconomic leading indicators when forecasting the occurrence of such events. This paper extends such discrete-choice EWSs by taking the persistence of the crisis phenomenon into account. The dynamic logit EWS is estimated using an exact maximum likelihood estimation method in both a country-by-country and a panel framework. The forecasting abilities of this model are then scrutinized using an evaluation methodology which was designed recently, specifically for EWSs. When used for predicting currency crises for 16 countries, this new EWS turns out to exhibit significantly better predictive abilities than the existing static one, both in- and out-of-sample, thus supporting the use of dynamic specifications for EWSs for financial crises.     

Corporate bond market interdependence: Credit spread correlation between and within U.S. and Canadian corporate bond markets

This study investigates the correlation and interdependence between and within the U.S. and Canadian corporate bond markets. The empirical framework adopted allows credit spreads to depend on common systematic risk factors derived from structural models and incorporates dynamic conditional correlations (DCC) between spreads. Results show that there is a surprisingly weak correlation between the two markets in normal times. However, during crises, there is a sudden and strong increase in the correlation between U.S. and Canadian credit spreads. The analysis of credit spread correlation within each market also shows an unusual increase in credit spread correlations between sectors and between risk classes in the U.S. during the 2007–2009 global financial crisis. This increase persists over the post-crisis period. By contrast, in Canada, credit spread correlations between sectors remain remarkably stable over time, suggesting an interdependence of credit spreads within the Canadian market.     

Optimal investment strategies in an international economy with stochastic interest rates

We investigate how investors should optimally choose to invest in a dynamically complete international market. We find closed-form solutions for the optimal investment strategy and for the wealth loss an investor suffers from not investing internationally. Theoretically, we show that the gain from international investment is due to the speculative investment only, and why it is important for an investor from a large economy to invest in a small economy. In a numerical example we compare the wealth losses investors from Denmark and the U.S. suffer due to home bias.     

网络嵌入、绿色动态能力与企业绿色创新——环境规制和管理者环境注意力的调节作用

基于动态能力理论、社会网络理论和制度理论等,探讨网络嵌入对企业绿色创新的影响,并进一步考察绿色动态能力在其中的中介作用以及环境规制、管理者环境注意力的调节作用。运用多元回归和Bootstrap方法进行实证检验,结果显示：结构嵌入和关系嵌入对企业绿色创新均具有显著影响;绿色动态能力在结构嵌入、关系嵌入与绿色创新之间起中介作用;环境规制、管理者环境注意力均正向调节绿色动态能力与绿色创新间关系。     

谈静态扭矩开发

文章从扭矩监控的角度,分析监控扭矩的工具——静态扭矩的开发,以及利用SPC原理计算静态扭矩和判断静态扭矩是否合理的方法。     

Monitoring trends of technological changes based on the dynamic patent lattice: A modified formal concept analysis approach

The strategic importance of monitoring technological changes is highlighted given the ever faster pace and increasing complexity of technological innovation. In this respect, patent citation analysis has been the most frequently adopted tool among others. However, patent citation analysis is subject to certain drawbacks that stem from only consideration of citing-cited information and time lags between citing and cited patents. This study proposes a formal concept analysis (FCA)-based approach to developing a dynamic patent lattice that can analyze complex relations among patents and monitor trends of technological changes. The FCA is a mathematical tool for grouping objects with shared properties based on the lattice theory. The distinct strengths of FCA, vis-á-vis other methods, lie in structuring and displaying the relations among objects from a massive amount of data. For the purpose of technology monitoring, the FCA is modified to take into account time periods and changes of patent keywords. A patent context is first constructed with the aid of domain experts and text mining technique. Two types of dynamic patent lattices are then developed by executing the modified FCA algorithm. A case study of laser technology in lithography for semiconductor manufacturing shows that the suggested dynamic patent lattice has considerable advantages over conventional patent citation maps in terms of visualization and informative power.     

Biological conservation in dynamic agricultural landscapes: Effectiveness of public policies and trade-offs with agricultural production

Land use change and land management intensification are major drivers of biodiversity loss, especially in agricultural landscapes, that cover a large and increasing share of the world's surface. Incentive-based agri-environmental policies are designed to influence farmers' land-use decisions in order to mitigate environmental degradation. This paper evaluates the effectiveness of agri-environmental schemes for biological conservation in a dynamic agricultural landscape under economic uncertainty. We develop a dynamic ecological economic model of agricultural land-use and spatially explicit population dynamics. We then relate policies (subsidies to grassland, taxation of agricultural intensity) to the ecological outcome (probability of persistence of a species of interest). We also analyze the associated trade-offs between agricultural production (in value) and biological conservation (in probability of persistence) at the landscape scale.