Learning orientation and market orientation: From an alliance perspective

The literature on market orientation has grown in significance during the past decade. Whilst there is more literature on market orientation, the literature on learning orientation is also starting to increase. Numerous researchers have studied and found support for the positive relationship between market orientation and learning orientation (eg Slater and Narver 1995). However, not many researchers have investigated the relationship that firms with a high learning orientation have a high market orientation (eg Sinkula, Baker and Noordewier 1997). This paper attempts to investigate that link in more detail. An alliance perspective is taken in understanding this relationship.

Personality and goal orientation as predictors of performance in a learning context

The current study aimed to investigate and provide furthering evidence of individual differences as determinants of task performance. This research focused on the effects of the personality traits Openness to Experience and Neuroticism, and two goal orientation traits. Learning Orientation and Avoid Orientation, on task performance. The hypotheses addressed the predictability of the traits, the differential effects of personality and goal orientation traits, and the mediating effects of goal orientation on the relationship between personality and performance. The results were based on questionnaire responses completed by a sample of 103 students. Scores on a computerised Air Traffic Control (ATC) decision-making task were used as a measure of task performance. Learning Orientation was found to be a significant predictor of performance, whilst the effect of Neuroticism was 'approaching' significance. Results indicated strong support for the differential relationship between personality traits and corresponding goal orientation traits. The mediating relationship between Openness to Experience, Learning Orientation and performance was also found to be 'approaching' significance. Results were indicative of the influences of personality and goal orientation on consequent performance outcomes. Implications were discussed, as well as suggestions for possible future directions in research assessing the predictabilit)' of individual differences in learning contexts.

Antecedents of task-specific goal orientation: An investigation of task practice, personality and global goal orientation

Goal orientation, a mental framework for understanding how individuals approach learning and achievement situations, has emerged as an important topic in organisational psychology. This study investigated the effects of task practice, personality (openness to experience and neuroticism), and global goal orientation (predisposition to adopt a certain response pattern across all domains) on participants’ task-specific goal orientation (response pattern adopted for a specific task). One hundred and three participants performed an air traffic control task and their task-specific goal orientation was measured prior to each of a total of thirty trials. Results revealed an effect of task practice such that individuals’ task-specific learning orientation decreased over time while their task-specific prove orientation increased over time. The results also showed that individuals’ personality can influence their task-specific goal orientation and further, that this relationship can be mediated by global goal orientation. Specifically, the positive relationship between openness to experience and task-specific prove orientation was mediated by global prove orientation. Similarly, the positive relationship between neuroticism and task-specific avoid orientation was mediated by global avoid orientation. Theoretical and practical implications of these findings are considered.

Towards evidence-based guidelines for wise use of computers by children

This paper argues for the systematic development and presentation of evidence-based guidelines for appropriate use of computers by children. The currently available guidelines are characterised and a proposed conceptual model presented. Five principles are presented as a foundation to the guidelines. The paper concludes with a framework for the guidelines, key evidence for and against guidelines, and gaps in the available evidence, with the aim of facilitating further discussion. Relevance to industry The current generation of children in affluent countries will typically have over 10 years of computer experience before they enter the workforce. Consequently, the primary prevention of computer-related health disorders and the development of good productivity skills for the next generation of workers needs to occur during childhood. (c) 2006 Elsevier B.V. All rights reserved.

System for foreign exchange trading using genetic algorithms and reinforcement learning

Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.

Does industry matter? Examining the role of industry structure and organizational learning in innovation and brand performance

A manager's perception of industry structure (dynamism) has the potential to impact various organizational strategies and behaviors. This may be particularly so with regard to perceptions driving organizational learning orientations and innovation based marketing strategy. The position taken here suggests that firms operating within a competitive industry tend to pursue innovative ways of performing value-creating activities, which requires the development of learning capabilities. The results of a study of SMEs suggest that market focused learning, relative to other learning capabilities plays a key role in the relationships between industry structure, innovation and brand performance. The findings also show that market focused learning and internally focused learning influence innovation and that innovation influences a brand's performance. (c) 2005 Elsevier Inc. All rights reserved.

An examination of learning processes during critical incident training: Implications for the development of adaptable trainees

Three experiments are reported that examined the process by which trainees learn decision-making skills during a critical incident training program. Formal theories of category learning were used to identify two processes that may be responsible for the acquisition of decision-making skills: rule learning and exemplar learning. Experiments I and 2 used the process dissociation procedure (L. L. Jacoby, 1998) to evaluate the contribution of these processes to performance. The results suggest that trainees used a mixture of rule and exemplar learning. Furthermore, these learning processes were influenced by different aspects of training structure and design. The goal of Experiment 3 was to develop training techniques that enable trainees to use a rule adaptively. Trainees were tested on cases that represented exceptions to the rule. Unexpectedly, the results suggest that providing general instruction regarding the kinds of conditions in which a decision rule does not apply caused them to fixate on the specific conditions mentioned and impaired their ability to identify other conditions in which the rule might not apply. The theoretical, methodological, and practical implications of the results are discussed.

An Incremental EM-based Learning Approach for On-Line Prediction of Hospital Resource Utilization

Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD

Modulation of channel activity and gadolinium block of MscL by static magnetic fields

The magnetic field of the Earth has for long been known to influence the behaviour and orientation of a variety of living organisms. Experimental studies of the magnetic sense have, however, been impaired by the lack of a plausible cellular and/or molecular mechanism providing meaningful explanation for detection of magnetic fields by these organisms. Recently, mechanosensitive (MS) ion channels have been implied to play a role in magnetoreception. In this study we have investigated the effect of static magnetic fields (SMFs) of moderate intensity on the activity and gadolinium block of MscL, the bacterial MS channel of large conductance, which has served as a model channel to study the basic physical principles of mechanosensory transduction in living cells. In addition to showing that direct application of the magnetic field decreased the activity of the MscL channel, our study demonstrates for the first time that SMFs can reverse the effect of gadolinium, a well-known blocker of MS channels. The results of our study are consistent with a notion that (1) the effects of SMFs on the MscL channels may result from changes in physical properties of the lipid bilayer due to diamagnetic anisotropy of phospholipid molecules and consequently (2) cooperative superdiamagnetism of phospholipid molecules under influence of SMFs could cause displacement of Gd3+ stop ions from the membrane bilayer and thus remove the MscL channel block.

SQLator: An online SQL learning workbench

SQL (Structured Query Language) is one of the essential topics in foundation databases courses in higher education. Due to its apparent simple syntax, learning to use the full power of SQL can be a very difficult activity. In this paper, we introduce SQLator, which is a web-based interactive tool for learning SQL. SQLator's key function is the evaluate function, which allows a user to evaluate the correctness of his/her query formulation. The evaluate engine is based on complex heuristic algorithms. The tool also provides instructors the facility to create and populate database schemas with an associated pool of SQL queries. Currently it hosts two databases with a query pool of 300+ across the two databases. The pool is divided into 3 categories according to query complexity. The SQLator user can perform unlimited executions and evaluations on query formulations and/or view the solutions. The SQLator evaluate function has a high rate of success in evaluating the user's statement as correct (or incorrect) corresponding to the question. We will present in this paper, the basic architecture and functions of SQLator. We will further discuss the value of SQLator as an educational technology and report on educational outcomes based on studies conducted at the School of Information Technology and Electrical Engineering, The University of Queensland.

A machine learning approach to intraday trading on foreign exchange markets

Foreign Exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. In this paper we try to create such a system using Machine learning approach to emulate trader behaviour on the Foreign Exchange market and to find the most profitable trading strategy.