Consumer response to food labels in an emerging market: the case of Romania

This study investigates consumer response to food labels in an emerging market. More specifically, it measures the levels of awareness, objective and perceived understanding, perceived usefulness and perceived trustworthiness of the most prominent food labels found in the Romanian market. An online survey was conducted with a convenience sample of 428 respondents (45.6% males of an average age of 30.6 years). Results revealed that for most respondents, awareness levels towards food labels are generally low, except for the Guideline Daily Amount (GDA) and the organic food labels. Objective understanding towards food labels was relatively high, especially towards those food labels that included a clear text element. Perceived understanding, perceived usefulness and perceived trustworthiness were found to be consistently high with regard to the GDA and the national organic food labels, while the European organic label scored lower. Finally, response to food labels was found to differ between aware and unaware respondents.     

Probabilistic assessment of fleet-level noise impacts of projected technology improvements

Demand projections for civil aviation have forecast increases in operations in future decades. Increases in demand are beneficial to the growth and advancement of the aviation industry, but also come with the threat of significant increase in environmental impacts. In response, the industry is focusing on programs to develop technologies for reductions in fuel burn, NO_x emissions, and noise. While aircraft-level impacts are an obvious metric of success, it is difficult to make informed robust technology investment decisions with respect to noise without understanding the fleet-level impacts. Fleet-level predictions of noise for technology explorations are especially complicated because it is computationally expensive, highly combinatorial, and airport-specific. Recently, rapid automated airport noise models have been developed, which can be simulated using Design of Experiments (DOE). The results of these simulations are used to generate surrogate models for airport noise contour area, which can be summed to yield a fleet-level impact. These models make use of simplifying assumptions to provide estimates of airport-level noise that are substantially cheaper to compute. They can be used to perform parametric trade-off analyses in conjunction with the equivalency assumption. Equivalency asserts that environmental impacts of a technology infused aircraft can be represented by scaled operations of the baseline aircraft in the same class. This simple assumption allows for the modeling of technology and market penetration factors under the same units: operations. This research uses surrogate models in conjunction with the equivalency assumption to examine two potential technology scenarios in a target forecast year, simulating technology and market performance factors to identify vehicle classes that could have the greatest impact in reducing contour area. Results show that technology and market performance of future notional Small Single Aisle and Large Single Aisle vehicle aircraft have the highest positive correlations with potential reductions in contour area.     

Diversification strategy with random yield suppliers for a mean–variance risk-sensitive manufacturer

We consider the diversification strategy for a mean–variance risk-sensitive manufacturer with unreliable suppliers. We first analyze the linear model and find that the suppliers are selected according to the descending order of their contributed marginal expected profit, and increasing the manufacturer’s risk-averseness leads to a more even allocation of demand across the suppliers. Then, we study the general newsvendor model. By approximating the leftover inventory with a normal distribution, we establish the general properties of the active supplier set and show that the supplier selection rule is similar to that under the risk-neutral setting when the demand uncertainty is large. Moreover, we conjecture that the selection rule also applies when the demand uncertainty is low, which we verify with an extensive numerical study. Our paper makes two contributions: First, we establish the properties of the optimal diversification strategy and develop corresponding insights into the trade off between cost and reliability under the mean–variance framework. Second, we perform comparative statics on the optimal solution, with a particular emphasis on investigating how changes in the supplier’s cost or reliability affect the risk-averse manufacturer’s ordering decisions and customer service level.     

Arc routing problems to restore connectivity of a road network

After a disaster, restoring accessibility in the affected area is critical for response operations. We study two arc routing problems for clearing blocked roads. The first problem minimizes the time to reconnect the road network, while the second maximizes the total benefit gained by reconnecting network components within a time limit. For each problem, we develop a mixed integer programming formulation and two versions of a heuristic algorithm. We conduct computational experiments on Istanbul data and instances adapted from the literature. The heuristics achieve near-optimal or optimal solutions quickly in most of the tested instances.     

A contingent plan for disaster response

Natural and man-made disasters imply a great deal of uncertainty in terms of potential damage, though it is certain that there would be a huge spike in the demand for relief supplies causing shortages and/or delays in providing aid. Ruptures in the infrastructure (roads, utility, and communication lines) cause additional delays due to repairs. Therefore, the relief providers need to work in collaboration with retailers, and infrastructure service providers for improving responsiveness. The relief providers (government and non government) rely on acquiring and delivering supplies in real time because such actions accompany little risk of resource underutilization, though the cost of real time acquisitions can be high. In contrast, a proactive response, while minimizing acquisition cost, can be very ineffective if demand surges are high. We study a hybrid of reactive and proactive approaches, where the reactive response is contingent upon the disaster intensity exceeding a certain threshold. We show how the threshold value may impact capacity acquisitions and prices and establish the optimality of contingent response. Further, we establish how an infrastructure contract may help reducing the social cost of disaster.     

大数据时代下电子商务平台的探索和研究——以淘宝网为例

随着网络用户的日益增长,互联网记录着大量的用户个人信息和由智能终端产生的图片和信息,这些信息爆炸性的增长,并不断涌入网络海洋,产生海量的数据信息。在电子商务环境中大数据处理将会发展出更多强大和多元的功能。本文以淘宝网为例,分析研究如何合理利用数据,为企业的经营模式做出相应调整,并且在变化中不断进行企业新技术、新方法和新思路的探索。同时指出数据泄露的隐患,并给出相应建议。     

Local Venturing as Compassion Organizing in the Aftermath of a Natural Disaster: The Role of Localness and Community in Reducing Suffering

In contrast to models of compassion within existing organizations, this grounded theory study examines how ventures emerge relying on localness and community in direct response to ‘opportunities’ to alleviate suffering in the aftermath of a natural disaster. While a natural disaster is a surprising disruptive event devastating a local community, that local community is nested within a broader community, which can be a source of abundant resources. Ventures created in the aftermath of a natural disaster, given local knowledge and unencumbered by pre‐existing systems, procedures, and capabilities, are highly effective at connecting the broader community with the local community through customizing resources to meet victims' needs and to quickly delivering these resources to alleviate suffering.     

A true simulation study of three estimators at equal protection of respondents in randomized response sampling

In this study, three different estimators for estimating the proportion of a sensitive attribute in survey sampling are compared at equal protection of the respondents. The three estimators considered are due to Odumade and Singh (2009, Comm. Statist. Theory Methods) , Singh and Sedory (2011, Sociological Methods and Research) and a new estimator obtained by minimizing a chi‐squared distance. A SAS Macro is developed to compare these three estimators using a simulation study at equal protection of the respondents. A set of data from a real face‐to‐face interview was collected using two decks of cards and has been analyzed. The results are discussed.     

Volatility Relationship between Crude Oil and Petroleum Products

This paper utilizes calculated historical volatility and GARCH models to compare the historical price volatility behavior of crude oil, motor gasoline and heating oil in U.S. markets since 1990. We incorporate a shift variable in the GARCH/TARCH models to capture the response of price volatility to a change in OPEC’s pricing behavior. This study has three major conclusions. First, there was an increase in volatility as a result of a structural shift to higher crude oil prices after April 1999. Second, volatility shocks from current news are not important since GARCH effects dominate ARCH effects in the variance equation. Third, persistence of volatility in all commodity markets is quite transitory, with half-lives normally being a few weeks.