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John Callister reviews Phil Carpenter's eBrands: Building an Internet Business at Breakneck Speed

This article describes a research project answering the question "Can advanced information systems, such as expert knowledge-based systems help in business strategy formulation?"

John Bello, aka the “Lizard King,” has been lionized in the business press as having been the brilliant entrepreneur who started a beverage company from scratch in early 1995 with his partner, Tom Schwalm, and then sold the product line to PepsiCo seven years later for a reported $375 million. What many people do not know is how close Bello came to failing with his SoBe line of innovative drinks.

This article examines the professional development of entrepreneurs. It describes how cognitive mapping tools drawn from knowledge engineering can be employed to help entrepreneurs both to make decisions and to grow professionally.

Rising operational costs and software sustainment concerns have driven the Air Force to move to newer technology to ensure that the Air Force Standard Base Supply System (SBSS) can continue to provide affordable and sustainable mission support in the years to come. This paper aims to summarize the successful software modernization effort the Air Force undertook to achieve that objective.

The paper describes the preliminary system updates that were required to isolate the SBSS software from all internal and external system and user interfaces in preparation for the subsequent successful code roll effort. Once the legacy SBSS component was fully isolated, the SBSS software modernization objective was achieved via a “code roll” conversion of the SBSS software from legacy COBOL to Java code, and movement of the integrated logistics system-supply application from a proprietary information technology (IT) platform to an open IT operating environment.

The SBSS system modernization yielded immediate and significant IT operational cost reductions and provided an important foundation for achieving Air Force logistics system consolidation and cloud computing objectives going forward.

The SBSS modernization experience should be useful in assisting similar data system software modernization efforts.

Pilot upgrade training is critical to aircraft and passenger safety. This study aims to identify variances in the US Air Force C-130J pilot upgrade training based on geographic location and provide a model to enhance policy that will impact future pilot training efforts that lower cost and increase operator quality and proficiency.

This research employed a mixed-method approach. First, the authors collected data and analyzed 90 C-130J pilots' aviation records and then contextualized this analysis with interviews of experts. Finally, the authors present a modified version of Six Sigma's define–measure–analyze–improve–control (DMAIC) that identifies and reduces the variances in C-130J pilot training, translating into higher quality outcomes.

The results indicate significant statistical variances across geographically separated C-130J pilot training organizations. This leads some organizations to have higher proficiency levels in specific tasks and others with comparative deficiencies. Additionally, the data analysis in this study enabled a recommended number of flight hours in several distinct categories that should be obtained before upgrading a pilot to aircraft commander to enhance standards.

This research was limited to C-130J pilot upgrades, but these results can be implemented within any field that utilizes hours as a measure of experience. Implications from this research can be employed to scope policy that will influence pilot training requirements across all airframes in civilian and military aviation.

This research proposes a process improvement methodology that could be immediately implemented within the C-130J community and, more importantly, in any upgrade training where humans advance into higher echelons of a profession.

The US Government is challenged to maintain pace as the world’s de facto provider of space object cataloging data. Augmenting capabilities with nontraditional sensors present an expeditious and low-cost improvement. However, the large tradespace and unexplored system of systems performance requirements pose a challenge to successful capitalization. This paper aims to better define and assess the utility of augmentation via a multi-disiplinary study.

Hypothetical telescope architectures are modeled and simulated on two separate days, then evaluated against performance measures and constraints using multi-objective optimization in a heuristic algorithm. Decision analysis and Pareto optimality identifies a set of high-performing architectures while preserving decision-maker design flexibility.

Capacity, coverage and maximum time unobserved are recommended as key performance measures. A total of 187 out of 10¹⁷ architectures were identified as top performers. A total of 29% of the sensors considered are found in over 80% of the top architectures. Additional considerations further reduce the tradespace to 19 best choices which collect an average of 49–51 observations per space object with a 595–630 min average maximum time unobserved, providing redundant coverage of the Geosynchronous Orbit belt. This represents a three-fold increase in capacity and coverage and a 2 h (16%) decrease in the maximum time unobserved compared to the baseline government-only architecture as-modeled.

This study validates the utility of an augmented network concept using a physics-based model and modern analytical techniques. It objectively responds to policy mandating cataloging improvements without relying solely on expert-derived point solutions.

This paper aims to explore effective supply chain principles, through the theory of transaction cost economics, as measures to improve current contingency pharmaceutical item shortfalls in the Air Force Medical Service (AFMS) Contingency Pharmaceutical Programme.

In this research, AFMS contingency pharmaceutical data was collected from various databases, including the Joint Medical Asset Repository, Medical Contingency Requirements Workflow and the Medical Requirements List. Through the methodology of cost-benefit analysis, alternative sourcing and fulfilment practices are evaluated.

The findings of this research indicate that the application of centralized purchasing principles, in an effort to leverage prime vendor contract fill rates for shortage items, can lead to 12%–17% increases in pharmaceutical material availability across the programme.

This research clearly shows that consolidating demand for shortage items across Active Duty War Reserve Material assemblages, though applications of centralized purchasing principles that leverage prime vendor contract fill rates, can lead to substantial increases in material availability at costs that justify the calculated benefits.

The purpose of this paper is to illustrate how game theoretic solution concepts inform what classes of problems will be amenable to artificial intelligence and machine learning (AI/ML), and how to evolve the interaction between human and artificial intelligence.

The approach addresses the development of operational gaming to support planning and decision making. It then provides a succinct summary of game theory for those designing and using games, with an emphasis on information conditions and solution concepts. It addresses how experimentation demonstrates where human decisions differ from game theoretic solution concepts and how games have been used to develop AI/ML. It concludes by suggesting what classes of problems will be amenable to AI/ML, and which will not. It goes on to propose a method for evolving human/artificial intelligence.

Game theoretic solution concepts inform classes of problems where AI/ML 'solutions' will be suspect. The complexity of the subject requires a campaign of learning.

Though games have been essential to the development of AI/ML, practitioners have yet to employ game theory to understand its limitations.