Full Information Product Pricing: An Information Strategy for Harnessing Consumer Choice to Create a More Sustainable World

Research and practice in the information systems (IS) field have been evolving over time, nourishing and promoting the development of applications that transform the relationships of individuals, corporations, and governments. Building on this evolution, we push forward a vision of the potential influence of the IS field into one of the most important problems of our times, an increasingly unsustainable world, which is traditionally considered the product of imperfect markets or market externalities. We describe our work in Full Information Product Pricing (FIPP) and our vision of a FIPP global socio-technical system, I-Choose, as a way to connect consumer choice and values with environmental, social, and economic effects of production and distribution practices. FIPP and I-Choose represent a vision about how information systems research can contribute to interdisciplinary research in supply chains, governance, and market economies to provide consumers with information packages that help them better understand how, where, and by whom the products they buy are produced. We believe that such a system will have important implications for international trade and agreements, for public policy, and for making a more sustainable world

A process pattern model for tackling and improving big data quality

Data seldom create value by themselves. They need to be linked and combined from multiple sources, which can often come with variable data quality. The task of improving data quality is a recurring challenge. In this paper, we use a case study of a large telecom company to develop a generic process pattern model for improving data quality. The process pattern model is defined as a proven series of activities, aimed at improving the data quality given a certain context, a particular objective, and a specific set of initial conditions. Four different patterns are derived to deal with the variations in data quality of datasets. Instead of having to find the way to improve the quality of big data for each situation, the process model provides data users with generic patterns, which can be used as a reference model to improve big data quality

Hydra: A mixture modeling framework for subtyping pediatric cancer cohorts using multimodal gene expression signatures.

Precision oncology has primarily relied on coding mutations as biomarkers of response to therapies. While transcriptome analysis can provide valuable information, incorporation into workflows has been difficult. For example, the relative rather than absolute gene expression level needs to be considered, requiring differential expression analysis across samples. However, expression programs related to the cell-of-origin and tumor microenvironment effects confound the search for cancer-specific expression changes. To address these challenges, we developed an unsupervised clustering approach for discovering differential pathway expression within cancer cohorts using gene expression measurements. The hydra approach uses a Dirichlet process mixture model to automatically detect multimodally distributed genes and expression signatures without the need for matched normal tissue. We demonstrate that the hydra approach is more sensitive than widely-used gene set enrichment approaches for detecting multimodal expression signatures. Application of the hydra analysis framework to small blue round cell tumors (including rhabdomyosarcoma, synovial sarcoma, neuroblastoma, Ewing sarcoma, and osteosarcoma) identified expression signatures associated with changes in the tumor microenvironment. The hydra approach also identified an association between ATRX deletions and elevated immune marker expression in high-risk neuroblastoma. Notably, hydra analysis of all small blue round cell tumors revealed similar subtypes, characterized by changes to infiltrating immune and stromal expression signatures

Using Ontologies to Develop and Test a Certification and Inspection Data Infrastructure Building Block

Global markets for information-intensive products contain sharp information asymmetries that lead to market inefficiencies resulting from consumer purchasing decisions that are based on incomplete information. Elimination or reduction of such information asymmetries has long been the goal of governments as well as various nongovernmental entities that recognize that addressing issues such as sustainable production, socially just labor practices, and reduction in energy needs and health expenditure is closely linked to consumers being fully aware of the economic, environmental, and social impacts of their purchasing decisions. This chapter reports on the creation of ontology-enabled interoperable data infrastructure based on semantic technologies that would enable information sharing in traditionally information-restricted markets. The main technical result is a proof-of-concept set of data standards built on semantic technology applications and the functionalities of formal ontology of certification and inspection processes. The current proof of concept focuses specifically on certified fair-trade coffee, and while its applicability is currently limited, it has the potential to become universally applicable to any certification and inspection process for any product and service. In addition to producing a number of artifacts relevant to the expandability of the work, such as domain ontologies, the research indicates that while big data systems are necessary, they are not sufficient to create high levels of consumer trust. By testing the criteria using both hand-generated and automated queries, we are able to demonstrate that CIDIBB (Certification and Inspection Data Infrastructure Building Block) is not only able to test the trustworthiness of certification schemes but also that our ontology generates consistent results

Stretchable Conductive Composites Based on Metal Wools for Use as Electrical Vias in Soft Devices

Soft devices can be bent, stretched, and compressed reversibly, but conventional wires are rigid. This work describes stretchable composites that are easily fabricated with simple tools and commodity materials, and that can provide a strategy for electrical wiring that meets certain needs of soft devices. These composites are made by combining metal wool and elastomeric polymers. Embedding fine (average fiber width ≈25 μm) steel wool (or other metal wools) in a silicone polymer creates an electrically conductive path through the nonconductive elastomer. This composite is flexible, stretchable, compressible, inexpensive, and simple to incorporate into the bodies of soft devices. It is also electrically anisotropic, and shows maximum conductivity along the majority axis of the fibers, but maximum extension perpendicular to this axis. The utility of this composite for creating an electrically conductive path through an elastomer was demonstrated in several devices, including: a soft, solderless breadboard, a soft touch sensor, and a soft strain gauge.Chemistry and Chemical Biolog

Directionally tunable and mechanically deformable ferroelectric crystals from rotating polar globular ionic molecules

Ferroelectrics are used in a wide range of applications, including memory elements, capacitors and sensors. Recently, molecular ferroelectric crystals have attracted interest as viable alternatives to conventional ceramic ferroelectrics because of their solution processability and lack of toxicity. Here we show that a class of molecular compounds-known as plastic crystals-can exhibit ferroelectricity if the constituents are judiciously chosen from polar ionic molecules. The intrinsic features of plastic crystals, for example, the rotational motion of molecules and phase transitions with lattice-symmetry changes, provide the crystals with unique ferroelectric properties relative to those of conventional molecular crystals. This allows a flexible alteration of the polarization axis direction in a grown crystal by applying an electric field. Owing to the tunable nature of the crystal orientation, together with mechanical deformability, this type of molecular crystal represents an attractive functional material that could find use in a diverse range of applications

Supply-Chain transparency and governance systems: market penetration of the I-Choose system

In this chapter, we explore the impacts of key characteristics of Supply Chain Governance Systems in the development and diffusion of technology innovations that promote supply chain transparency and sustainable consumption and production. The model presented in this chapter was developed following group model building methods. Our simulation experiments reveal that the market resists “take-off” unless external financial support can be found. Additionally, “take-off” dynamics of the system are dominated by marketing budgets and external support for infrastructure. Marketing budgets drive how fast users adopt the system, and without external sponsorship of system, the final market collapses. Finally, the quality of governance—reflected in information completeness, openness, relevance and reliability, and the resultant trustworthiness of information determines final sustainable market share