Marketing and Poverty Alleviation: Synergizing Research, Education, and Outreach Through the Subsistence Marketplaces Approach

In this article, we describe our journey through the creation and development of the stream of subsistence marketplaces, summarize our learning, and discuss implications at the intersection of the field of Marketing and poverty alleviation. Distinct from macro level economic research in impoverished contexts, or mid-level approaches, such as the base of the pyramid (BOP) approach in business strategy, this approach is rooted at the micro-level, enabling bottom up understanding of buyer and seller. The term, subsistence marketplaces, reflects understanding these contexts in their own right, not just as markets to sell to, but as individuals, communities, consumers, entrepreneurs, and marketplaces to learn from

Intelligent agents in electronic markets for information goods: customization, preference revelation and pricing

Electronic commerce has enabled the use of intelligent agent technologies that can evaluate buyers, customize products, and price in real-time. Our model of an electronic market with customizable products analyzes the pricing, profitability and welfare implications of agent-based technologies that price dynamically based on product preference information revealed by consumers. We find that in making the trade-off between better prices and better customization, consumers invariably choose less-than-ideal products. Furthermore, this trade-off has a higher impact on buyers on the higher end of the market and causes a transfer of consumer surplus towards buyers with a lower willingness to pay. As buyers adjust their product choices in response to better demand agent technologies, seller revenues decrease since the gains from better buyer information are dominated by the lowering of the total value created from the transactions. We study the strategic and welfare implications of these findings, and discuss managerial and technology development guidelines.NYU, Stern School of Business, IOMS Department, Center for Digital Economy Researc

The Impact of Intelligent Agents on Electronic Markets: Customization, Preference Revelation and Pricing.

Apart from reducing buyer search costs, web-based commerce has also enabled the use of intelligent agent technologies that reduce seller search costs by targeting buyers, customizing, and pricing products in real-time. Our model of an electronic market with customizable products analyzes the pricing, profitability and welfare implications of these agent-based technologies that price dynamically, based on product preference and demographic information revealed by consumers. We find that in making the trade-off between better prices and better customization, consumers invariably choose less-than-ideal products. Furthermore, this trade-off impacts buyers on the higher end of the market more, and causes a transfer of consumer surplus towards buyers with a lower willingness to pay. As buyers adjust their product choices in response to better demand agent technologies, sellers may experience reduced revenues, since the gains from better buyer information are countered by the lowering of the total value created from the transactions. We study the strategic and welfare implications of these findings, and discuss managerial and technology development guidelines.Information Systems Working Papers Serie

Adversarial Assessment of the \u3ci\u3eF Prime\u3c/i\u3e Flight Software Framework: Findings and Recommendations

F Prime (F’) is a multi-platform, open-source flight software (FSW) framework developed by the Jet Propulsion Laboratory (JPL). F’ provides a highly capable, component-driven framework tailored towards, but not limited to, small-scale systems like CubeSats, SmallSats, and instruments. We conducted an adversarial assessment of F’ aimed at evaluating its security vulnerabilities. This preliminary assessment of F’ entailed a multi-stage simulation of a malicious actor’s activities, including open-source reconnaissance, passive and active reconnaissance, and exploitation. In this paper, we present our methodology and discuss the preliminary findings of this assessment, which highlighted several areas where F’ could be enhanced. These areas include the implementation of encryption for uplink and down-link communication, command authentication, the establishment of community standard cybersecurity practices, remediation of information leakage, and development of an opcode randomizer to provide secure defaults. We expect this preliminary work to inspire further detailed security assessments, and further the design and development of more secure and resilient flight software architectures

Conjoined Processor: A Fault Tolerant High Performance Microprocessor

Reliability has become a serious concern as systems embrace nanometer technologies. Current reliability enhancement techniques cause slowdown in processor operation. In this work, we propose a novel approach that organizes redundancy in a special way to provide high degree of fault tolerance. Our approach improves performance by reliably adapting the system clock frequency during run time, based on the current running application and environmental conditions. The organization of redundancy in the proposed conjoined processor supports overclocking, provides concurrent error detection and recovery capability for soft errors, timing errors, intermittent faults and detects silicon defects. The fast recovery process requires no checkpointing and takes three cycles. Post-layout timing annotated gate level simulations of a conjoined two stage arithmetic pipeline shows that our approach achieves near 100% fault coverage, and a performance improvement of 21%. A five stage in-order conjoined pipeline processor was designed and implemented to verify correctness of the proposed architecture

Open Source Infrastructure for Differentiable Density Functional Theory

Learning exchange correlation functionals, used in quantum chemistry calculations, from data has become increasingly important in recent years, but training such a functional requires sophisticated software infrastructure. For this reason, we build open source infrastructure to train neural exchange correlation functionals. We aim to standardize the processing pipeline by adapting state-of-the-art techniques from work done by multiple groups. We have open sourced the model in the DeepChem library to provide a platform for additional research on differentiable quantum chemistry methods

SEU Mitigation Techniques for Microprocessor Control Logic

The importance of fault tolerance at the processor architecture level has been made increasingly important due to rapid advancements in the design and usage of high performance devices and embedded processors. System level solutions to the challenge of fault tolerance flag errors and utilize penalty cycles to recover through the re-execution of instructions. This motivates the need for a hybrid technique providing fault detection as well as fault masking, with minimal penalty cycles for recovery from detected errors. We propose three architectural schemes to protect the control logic of microprocessors against single event upsets (SEUs). High fault coverage with relatively low hardware overhead is obtained by using both fault detection with recovery and fault masking. Control signals are classified as either static or dynamic, and static signals are further classified as opcode dependent and instruction dependent. The strategy for protecting static instruction dependent control signals utilizes a distributed cache of the history of the control bits along with the triple modular redundancy (TMR) concept, while the opcode dependent control signals are protected by a distributed cache which is used to flag errors. Dynamic signals are protected by selective duplication of datapath components. The techniques are implemented on the OpenRISC 1200 processor. Our simulation results show that fault detection with single cycle recovery is provided for 92% of all instruction executions. FPGA synthesis is performed to analyze the associated cycle time and area overheads

Intelligent agents in electronic markets for information goods: customization, preference revelation and pricing

Electronic commerce has enabled the use of intelligent agent technologies that can evaluate buyers, customize products, and price in real-time. Our model of an electronic market with customizable products analyzes the pricing, profitability and welfare implications of agent-based technologies that price dynamically based on product preference information revealed by consumers. We find that in making the trade-off between better prices and better customization, consumers invariably choose less-than-ideal products. Furthermore, this trade-off has a higher impact on buyers on the higher end of the market and causes a transfer of consumer surplus towards buyers with a lower willingness to pay. As buyers adjust their product choices in response to better demand agent technologies, seller revenues decrease since the gains from better buyer information are dominated by the lowering of the total value created from the transactions. We study the strategic and welfare implications of these findings, and discuss managerial and technology development guidelines.NYU, Stern School of Business, IOMS Department, Center for Digital Economy Researc

The Impact of Intelligent Agents on Electronic Markets: Customization, Preference Revelation and Pricing.

Apart from reducing buyer search costs, web-based commerce has also enabled the use of intelligent agent technologies that reduce seller search costs by targeting buyers, customizing, and pricing products in real-time. Our model of an electronic market with customizable products analyzes the pricing, profitability and welfare implications of these agent-based technologies that price dynamically, based on product preference and demographic information revealed by consumers. We find that in making the trade-off between better prices and better customization, consumers invariably choose less-than-ideal products. Furthermore, this trade-off impacts buyers on the higher end of the market more, and causes a transfer of consumer surplus towards buyers with a lower willingness to pay. As buyers adjust their product choices in response to better demand agent technologies, sellers may experience reduced revenues, since the gains from better buyer information are countered by the lowering of the total value created from the transactions. We study the strategic and welfare implications of these findings, and discuss managerial and technology development guidelines.Information Systems Working Papers Serie