Cross-Border Shopping: A Survey

The aim of this paper is to undertake a review of the most important literature on the phenomenon of fiscally induced cross-border shopping. Following the presentation of the principal theoretical models, the study concentrates on applied literature. Firstly, the elements common to the diverse applications are described, and then, a detailed analysis of the research undertaken into cross-border shopping for alcoholic drinks, tobacco, fuel, and lotteries is provided, concluding with a reference to the interaction between cross-border purchases and those effected over the internet. The results achieved by the empirical research coincide and support the principal result of the theoretical literature: the tax differentials between neighboring territories induce consumers to purchase in the territory where taxation is lower, on the condition that the tax saving compensates for the transport costs associated with the travel made by the purchaser in order to take advantage of the lower taxation.     

DISCRETE CHOICE AND RATIONAL INATTENTION: A GENERAL EQUIVALENCE RESULT

This article establishes a general equivalence between discrete choice and rational inattention models. Matějka and McKay (2015) showed that when information costs are modeled using the Shannon entropy, the choice probabilities in the rational inattention (RI) model take the multinomial logit form. We show that, for one given prior over states, RI choice probabilities may take the form of any additive random utility discrete choice model (ARUM) when the information cost is a Bregman information, a class defined in this article. The prior information of the rationally inattentive agent is summarized in a constant vector of utilities in the corresponding ARUM.     

Assessing the Impact of Formal and Informal Regulations on Environmental and Economic Performance of Brazilian Manufacturing Firms

This study investigates the impact of formal and informal regulations on environmental and economic performance of Brazilian manufacturing firms. We adopt a dual approach where production technology is represented by a cost function, approximated by a translog form. Pollution is considered as a negative by-product that can be modified trough using either formal regulation (inspections or sanctions) or informal regulation (community pressure). A simultaneous equation model is estimated by three-stage least squares on a sample of 404 industrial establishments located in the state of S?o Paulo, Brazil. We show that pollution abatement costs for the Brazilian manufacturing sector are different from zero which suggests that pollution emissions are affected by environmental regulation. We also demonstrate that environmental performance of firms is jointly affected by formal and informal regulation. Lastly, formal regulation is largely influenced by informal regulation and more specifically by community pressure.     

Sustainable product innovation and changing consumer behavior: Sustainability affordances as triggers of adoption and usage

This conceptual paper argues that for sustainable product innovation to make a contribution to addressing sustainability issues, we need to understand not only why consumers adopt sustainable products but also what makes them use these in sustainable way. To explain how specific product features can change the ways in which consumers engage with sustainable products in the adoption and usage phase, we draw on affordance theory. Affordances refer to the potential for agentic action of users in relation to a technological object. We develop a conceptual framework that explains how sustainable product innovation can lead to the design of sustainability affordances that stimulate adoption and sustainable usage. The framework shows how three forms of agency—material, firm, and user agency—interact and together influence a product's sustainability affordances that drive adoption and a change in consumer behavior. The framework explains how trade-offs between a product's environmental features and consumer expectations regarding desired functionalities and user experience can be overcome.     

Understanding the microenterprise sector to design a tailor-made microfinance policy for Cape Verde

Two of the central challenges faced by Cape Verde at the present are the high level of unemployment and the increasing proportion of the population living in (relative) poverty. Microenterprise development can be an effective means of addressing both problems in a developing country like Cape Verde, where microenterprises account for about 50% of employment. In this paper we provide a detailed profile of Cape Verdean microenterprises and microentrepreneurs and investigate the relationship between their characteristics and the resort to outside seed capital. We find a cluster of factors—the microentrepreneur’s age, gender, level of education and reason for being self-employed—which influence significantly the probability of being in need for external start-up capital. The policy implications of these findings for the design of a specific microfinance program for Cape Verde are discussed.

OCB and external–internal social networks: effects on individual performance and adaptation to change

In this study, we develop and test a model that links one's internal and external social network structures to his or her willingness and ability to adapt in a changing work context. Using a survey data from 371 employees working in 133 different branches of a large financial firm, we find that individual behaviors that explain task performance and individual adaptation to change are affected by a number of supportive social ties (size of the support network) with which one receives support inside and, mostly, outside the workplace. The results also show that individual performance and adaptation to change are affected by the level of workers' organizational citizenship behavior. We also identify a mediating effect exerted by the informational network structure (mostly an internal network) on the relationship between the support network (mostly an external network) and individual task performance.     

Extending multi-tenant architectures: a database model for a multi-target support in SaaS applications

Multi-tenant architectures (MTAs) are considered a cornerstone in the success of Software as a Service as a new application distribution formula. Multi-tenancy allows multiple customers (i.e. tenants) to be consolidated into the same operational system. This way, tenants run and share the same application instance as well as costs, which are significantly reduced. Functional needs vary from one tenant to another; either companies from different sectors run different types of applications or, although deploying the same functionality, they do differ in the extent of their complexity. In any case, MTA leaves one major concern regarding the companies’ data, their privacy and security, which requires special attention to the data layer. In this article, we propose an extended data model that enhances traditional MTAs in respect of this concern. This extension – called multi-target – allows MT applications to host, manage and serve multiple functionalities within the same multi-tenant (MT) environment. The practical deployment of this approach will allow SaaS vendors to target multiple markets or address different levels of functional complexity and yet commercialise just one single MT application. The applicability of the approach is demonstrated via a case study of a real multi-tenancy multi-target (MT²) implementation, called Globalgest.     

On the unique features of post-disaster humanitarian logistics

Logistic activity can be thought of as a socio-technical process whereby a social network of individuals orchestrates a series of technical activities using supporting systems such as transportation and communications. To understand the functioning of the entire system requires proper consideration of all its components. We identify seven key components: the objectives being pursued, the origin of the commodity flows to be transported, knowledge of demand, the decision-making structure, periodicity and volume of logistic activities, and the state of the social networks and supporting systems. Based on our analysis of the differences between commercial and humanitarian logistics, we pinpoint research gaps that need to be filled to enhance both the efficiency of humanitarian logistics and the realism of the mathematical models designed to support it.We argue that humanitarian logistics is too broad a field to fit neatly into a single definition of operational conditions. At one end of the spectrum we find humanitarian logistic efforts of the kind conducted in long-term disaster recovery and humanitarian assistance, where operational efficiency – akin to commercial logistics – is a prime consideration. At the other, post-disaster humanitarian logistic operations involved in disaster response and short-term recovery activities represent a vastly different operational environment, often in chaotic settings where urgent needs, life-or-death decisions and scarce resources are the norm. The huge contrast between these operational environments requires that they be treated separately.     

Dynamic redistribution of mitigation resources during influenza pandemics

The Institute of Medicine (IOM) has pointed out that the existing pandemic mitigation models lack the dynamic decision support capability. In this paper, we present a simulation optimization model to generate dynamic strategies for distribution of limited mitigation resources, such as vaccines and antivirals, over a network of regional outbreaks. The model has the capability to redistribute the resources remaining from previous allocations in response to changes in the pandemic progress. The model strives to minimize the impact of ongoing outbreaks and the expected impact of potential outbreaks, considering measures of morbidity, mortality, and social distancing, translated into the societal and economic costs of lost productivity and medical services. The model is implemented on a simulated H5N1 outbreak involving four counties in the state of Florida, U.S. with over four million inhabitants. The performance of our strategy is compared to that of a myopic distribution strategy. Sensitivity analysis is performed to assess the impact of variability of some critical factors on policy performance. The methodology is intended to support public health policy on effective distribution of limited mitigation resources.