Learning to win process-control games watching game-masters

The present paper focuses on some interesting classes of process-control games, where winning essentially means successfully controlling the process. A master for one of these games is an agent who plays a winning strategy. In this paper we investigate situations in which even a complete model (given by a program) of a particular game does not provide enough information to synthesize—even incrementally—a winning strategy. However, if in addition to getting a program, a machine may also watch masters play winning strategies, then the machine is able to incrementally learn a winning strategy for the given game. Studied are successful learning from arbitrary masters and from pedagogically useful selected masters. It is shown that selected masters are strictly more helpful for learning than are arbitrary masters. Both for learning from arbitrary masters and for learning from selected masters, though, there are cases where one can learn programs for winning strategies from masters but not if one is required to learn a program for the master's strategy itself. Both for learning from arbitrary masters and for learning from selected masters, one can learn strictly more by watching m+1 masters than one can learn by watching only m. Last, a simulation result is presented where the presence of a selected master reduces the complexity from infinitely many semantic mind changes to finitely many syntactic ones.

Invention and business performance in the tissue-engineering industry

Tissue engineering is a young and interdisciplinary scientific discipline but it offers exciting opportunities to improve the quality of health care for hundreds of thousands of patients. Lured by its potential, several start-up companies, pharmaceutical corporations, and medical device enterprises alike are investing heavily in this sector. Invention is a key driver of competition in this sector. In this study, we aim to explain the variation in inventive output across the different firms in the sector. Our major premise is that firms that forge alliances will be able to tap into the expertise of their partners and thus improve their chances of inventive output. We further argue that alliances that enable technology acquisition or learning will enhance the inventive output of firms more than other kinds of alliances. We measure the inventive output of a company by the number of patents filed. On the basis of a preliminary analysis of seven companies, we find support for the hypotheses. We also argue that, to achieve commercial success, firms need to manage time to market (through alliances or otherwise), have a global outlook, nurture their financial resources, and attain critical mass through mergers.

Business Leaders Hall of Fame collection

"Qld Business Leaders Hall of Fame" is a research project that includes interviews with eminent Qlders that produced oral history interviews and digital stories about their life/company's achievements. This model was able to test and evaluate the use of oral history and digital storytelling for learning and community heritage purposes. Interviewees include; Sir John and Valmai Pidgeon, Joseph Saragossi, Robert Bryan, Clem Jones, Jim Kennedy, Sr Angela Mary, Castelmaine Perkins, Burns and Philp, Qantas, Don Argus & Steve Irwin.

Business Process Model Merging : An Approach to Business Process Consolidation

This paper addresses the problem of constructing consolidated business process models out of collections of process models that share common fragments. The paper considers the construction of unions of multiple models (called merged models) as well as intersections (called digests). Merged models are intended for analysts who wish to create a model that subsumes a collection of process models - typically representing variants of the same underlying process - with the aim of replacing the variants with the merged model. Digests, on the other hand, are intended for analysts who wish to identify the most recurring fragments across a collection of process models, so that they can focus their efforts on optimizing these fragments. The paper presents an algorithm for computing merged models and an algorithm for extracting digests from a merged model. The merging and digest extraction algorithms have been implemented and tested against collections of process models taken from multiple application domains. The tests show that the merging algorithm produces compact models and scales up to process models containing hundreds of nodes. Furthermore, a case study conducted in a large insurance company has demonstrated the usefulness of the merging and digest extraction operators in a practical setting.

How does small business impact on utilization of industry-led supply chain innovation capacity

This research uses confirmatory factor analysis and structural equation modelling to examine how organizational size - made up of four dimensions - control, resources, trust and complexity - impacts on utilization of industry-led supply chain innovation capacity in a traditional agribusiness industry, the Australian beef industry. It confirms small business rather than larger business accords greater importance to exploiting supply chain dynamic capabilities, particularly in relation to utilizing industry –led supply chain innovation capacity. For small business in Australian beef supply chains, being agile and able to adapt and align their business practices with supply chain partners is integral to ensuring these businesses remain relevant and competitive in this market. In theoretical terms this is supported by authors in the dynamic capabilities literature as they argue these types of capabilities enable organizations to innovate faster (or better), often leading to the creation of newer sources of competitive advantage.