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The purpose of this paper is to discuss the challenges and obstacles encountered in the implementation of a mentoring program for Master of Business Administration (MBA) students at the University of South Australia (UniSA) Business School. The paper starts with an exploration into the need for a mentoring program, the trial and subsequent four years of implementation. The paper also explores the network model of mentoring and the reasons why this, rather than a more traditional model, was chosen for the program’s implementation.

This exploratory case study uses data from over 600 students and their alumni mentors over a five-year period to evaluate and improve the program as well as cultivating a critical community of adult learners.

Feedback from students indicates that the mentoring program is regarded by most as a value-added feature of their early learning as it offers support, if and when it is required, from those who have been there before.

Results are limited to one institution. However, as research into mentoring for higher education students is thin on the ground, this study contributes to our understanding of the positive impacts of mentoring on student success.

This paper emphasizes the importance of business leaders giving back to their alma mater through mentoring current MBA students. It shows how mentoring can support learning and management development.

This is an original study which explores ways to increase the learning of higher education students for positive social outcomes.

The purpose of this study is to explore Australian Indigenous women’s customary use of marine resources and views on aquaculture as a development opportunity. The value participants placed on economic, social and cultural outcomes were explored, as were benefit sharing, governance and business considerations.

Using a form of action research, workshops were conducted with a focus group of Indigenous women and interviews with men and women living on a remote island off northern Australia. Multimedia materials and a game were used to elicit a deeper understanding and facilitate discussion.

Women preferred aquaculture options respectful of culture and accommodating cultural and family obligations, that engage young adults in meaningful work, improve access to sea country and provide local foods and support economic development. Participants placed significant dependence on their governance body to support businesses and expressed disparate views on profit sharing. Women continue to engage in customary harvesting and fishing but various limitations impact on this.

Conclusions based on one case study need to be confirmed in other communities. Future research should include a broader representation of youth and strategies to improve people’s understanding of aquaculture operations and business management.

This research improves our understanding of Indigenous women’s preferred economic development pathways and their advocacy role within the community. These findings are relevant for policy-makers, businesses, other Indigenous communities and researchers.

This paper seeks to recognise and integrate Indigenous women’s economic and cultural aspirations within development policy. Such a place-based, gender-based consultative process is generally lacking in the Australian Indigenous policy arena.

The purpose of this paper was mainly to select one of the three types of coatings for protection of steel used as reinforcement in composite pipes (thin steel shell covered by cement-mortar) subjected to chloride exposure. To achieve this target, an attempt was made to develop a simple methodology for evaluating the performance of corrosion protection measures in terms of chloride threshold level (CTL) and corrosion initiation time (TI).

Bare, epoxy, red oxide and zinc primer-coated steel strips were embedded in cement mortar with sand/cement and water/cement ratios of 2 and 0.5 (by mass), respectively, to prepare the specimens which were exposed to chloride solution having a high concentration of 10 per cent NaCl. For determining the amounts of the water-soluble chloride diffused inside the specimens, powdered samples of mortar were collected from two different depths from the exposed surface of specimens on completion of each of the four different exposure times. The corrosion current densities were determined at two different stages. A step-by-step procedure for calculating CTL and TI using the measured chloride contents and corrosion current densities was established with the help of relevant information available in the literature.

Based on the comparison of the values of CTL and TI calculated for bare steel and steel with all three types of coatings, utilizing the experimental data and the proposed calculation procedure, the epoxy-coated steel was found to have the best performance.

This research has resulted into development of a simple methodology for evaluation of the performance of protective measures against corrosion of steel embedded in mortar or concrete exposed to chloride-bearing environment.

The purpose of this paper is to clarify the ontological and epistemological basis of classification.

Attention is drawn to a 1785 article on abstraction by Thomas Reid and the contents and theories of the article are explained. The Reid article both provides a sound approach to classification and is interesting historically as it influenced the classification pioneer Charles Ammi Cutter who, in turn, is responsible for much of the modern theory of functional bibliography. Reid's account is supplemented by brief descriptions of fallibilism and fuzziness. An associated view, Aristotelian essentialism is explained and criticized. Some observations are offered on the role of prototypes in classification and on the monothetic‐polythetic distinction.

Reid's theories, suitably embedded in fallibilism and augmented with a respect for truth, provide a sound ontological and epistemological basis for classification.

Reid's essay, together with an appreciation of fallibility and determinate and indeterminate properties, amount to a good basic theoretical foundation for cataloging.

The purpose of this paper is to explore the evolving balance between the use of print and electronic sources for answering reference questions.

A review of the international literature from the mid‐1990s is conducted. A case study of reference questions received at the Northern Territory Library is undertaken, by auditing data held in the online reference information management system, RefTracker. Over 620 questions are categorised according to the sources used in responding to those questions.

Results indicate that print and electronic sources are both important to the reference service at the Northern Territory Library.

There is great difficulty in assessing what constitutes a “correct” balance between print and electronic sources for responding to reference questions, and the current practice is likely to differ significantly between libraries. The results of the study are discussed in terms of their implications for the future of reference services and the education and training needs of reference librarians.

From the results of this study, coupled with data gathered from the review of international literature, it is possible to identify trends and issues influencing reference services and collections.

The complexity of analysis of geotechnical behavior is due to multivariable dependencies of soil and rock responses. In order to cope with this complex behavior, traditional forms of engineering design solutions are reasonably simplified. Incorporating simplifying assumptions into the development of the traditional models may lead to very large errors. The purpose of this paper is to illustrate capabilities of promising variants of genetic programming (GP), namely linear genetic programming (LGP), gene expression programming (GEP), and multi‐expression programming (MEP) by applying them to the formulation of several complex geotechnical engineering problems.

LGP, GEP, and MEP are new variants of GP that make a clear distinction between the genotype and the phenotype of an individual. Compared with the traditional GP, the LGP, GEP, and MEP techniques are more compatible with computer architectures. This results in a significant speedup in their execution. These methods have a great ability to directly capture the knowledge contained in the experimental data without making assumptions about the underlying rules governing the system. This is one of their major advantages over most of the traditional constitutive modeling methods.

In order to demonstrate the simulation capabilities of LGP, GEP, and MEP, they were applied to the prediction of: relative crest settlement of concrete‐faced rockfill dams; slope stability; settlement around tunnels; and soil liquefaction. The results are compared with those obtained by other models presented in the literature and found to be more accurate. LGP has the best overall behavior for the analysis of the considered problems in comparison with GEP and MEP. The simple and straightforward constitutive models developed using LGP, GEP and MEP provide valuable analysis tools accessible to practicing engineers.

The LGP, GEP, and MEP approaches overcome the shortcomings of different methods previously presented in the literature for the analysis of geotechnical engineering systems. Contrary to artificial neural networks and many other soft computing tools, LGP, GEP, and MEP provide prediction equations that can readily be used for routine design practice. The constitutive models derived using these methods can efficiently be incorporated into the finite element or finite difference analyses as material models. They may also be used as a quick check on solutions developed by more time consuming and in‐depth deterministic analyses.

The purpose of this perspective paper is to answer the question of why some multinational corporations (MNCs) do not evolve and fail to avoid retrogression by natural selection in international business (IB) and to introduce eight papers selected for this special issue.

The authors conceptually discuss the reasons for MNC failure by illustrating key motivations behind foreign direct investment (FDI) undertaken by MNCs based on internalization theory, the OLI paradigm and the OILL (i.e. OLI plus the learning motivation) paradigm. Then, the authors develop an evolutionary perspective to explore the survival of the fittest in the global markets and the natural selection of MNCs.

The eight papers selected for this special issue expand the authors’ understanding of globalized organizations' challenges, evolution and decline as well as offering a distinct opportunity to reconsider diverse extant theories about MNCs by suggesting an extension that accounts for the rise of various globalized organizations particularly in and from emerging markets.

Despite increased numbers of MNCs, which struggle to survive and are faced with great risk of failure, the authors’ understanding of them still remains in infancy. While scholars have investigated diverse topics related to MNCs, existing studies have developed theories predominantly emphasizing MNC success. Thus, conventional theories in IB such as internalization theory and the OLI paradigm may not be sufficiently applicable to explain the phenomenon of MNC failure (i.e. MNC decline). Based on authors’ discussions, the authors believe this is an appropriate time to refine mainstream IB theories by concurrently considering both evolution and retrogression.

The purpose of this paper is to examine the applicability and capability of models based on a genetic algorithm and support vector machine (GA-SVM) and a genetic algorithm and relevance vector machine (GA-RVM) for the prediction of phytoplankton abundances associated with algal blooms in a Macau freshwater reservoir, and compare their performances with an artificial neural network (ANN) model.

The hybrid models GA-SVM and GA-RVM were developed for the optimal control of parameters for predicting (based on the current month’s variables) and forecasting (based on the previous three months’ variables) phytoplankton dynamics in a Macau freshwater reservoir, MSR, which has experienced cyanobacterial blooms in recent years. There were 15 environmental parameters, including pH, SiO₂, alkalinity, bicarbonate (HCO₃−), dissolved oxygen (DO), total nitrogen (TN), UV254, turbidity, conductivity, nitrate (NO₃−), orthophosphate (PO₄³⁻), total phosphorus (TP), suspended solids (SS) and total organic carbon (TOC) selected from the correlation analysis, with eight years (2001-2008) of data for training, and the most recent three years (2009-2011) for testing.

For both accuracy performance and generalized performance, the ANN, GA-SVM and GA-RVM had similar predictive powers of R² of 0.73-0.75. However, whereas ANN and GA-RVM models showed very similar forecast performances, GA-SVM models had better forecast performances of R² (0.862), RMSE (0.266) and MAE (0.0710) with the respective parameters of 0.987, 0.161 and 0.032 optimized using GA.

This is the first application of GA-SVM and GA-RVM models for predicting and forecasting algal bloom in freshwater reservoirs. GA-SVM was shown to be an effective new way for monitoring algal bloom problem in water resources.

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.