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Talent management.

Management level proposed courses: knowledge management, human resource management, leadership and fundamentals of strategic management.

Legacy and succession issues plague rising economies. Attracting the local talent to stay is becoming increasingly difficult. This is especially the case for the family run businesses and also local government lead industries. Many MNCs have to bring in their own qualified staff making that an added cost and a disincentive to work in Malaysia. Thus, Malaysia has been experiencing a brain drain. The case study explores the generational differences in retaining staff and the challenges of a global demand and war for top talent. This affects emerging economies that are competing to keep their top talent from being lured away by their competitors. Brain drain is occurring in almost all sectors, but the Malaysian accountancy sector is the most affected. In view of this issue, this case addresses the common challenges facing accounting firms which is talent management and succession planning. ABC Ltd, a fictional firm is one of the Big Four accounting firms (four largest international accountancy and professional services firms), chosen as the context. Jeremy Tan is a manager of ABC Ltd

This case is the basis for class discussion and group presentations. Students will be able to understand generational differences, apply strategies to recruit and retain high-potential talent, and develop awareness of issues regarding Generation Y in Asia.

Teaching notes.

The stress–strain behaviors of rockfill materials in dams are significantly affected by the anisotropy and grain crushing. However, these factors are rarely considered in numerical simulations of high rockfill dams. This study intends to develop a reasonable and practical constitutive model for rockfill materials to overcome the above problems.

The effects of anisotropy and grain crushing are comprehensively considered by the spatial position of the reference state line. After the improved generalized plasticity model for rockfill materials (referred to as the PZR model) is developed and verified by laboratory tests, it is used with the finite element method to simulate the stress–strain behaviors of the Nuozhadu high core rockfill dam.

The simulated results agree well with the laboratory tests data and the situ monitoring data, verifying the reliability and practicability of the developed PZR model.

A new anisotropic state parameter is proposed to reflect the nonmonotonic variation in the strength as the major principal stress direction angle varies. This advantage is verified by the simulation of a set of conventional triaxial tests with different inclination angles of the compaction plane. 2) This is the first time that the elastoplastic model is verified by the situ monitoring data of high core rockfill dams. The numerical simulation results show that the PZR model can well reflect the stress–strain characteristics of rockfill materials in high core rockfill dams and is better than the traditional EB model.

The purpose of this paper is to study the correlation between the dynamic features of the running-in attractor and the wear particle group, so as to characterize the running-in attractor by means of the wear particle group.

Wear particles are collected in phased wear experiments, and their dynamic features are investigated by the equivalent mean chord length L. Then, the correlation between the equivalent mean chord length L and the correlation dimension D of the running-in attractor is studied.

In the wear process, the equivalent means chord length L first decreases, then remains steady, and finally increases, this process agrees with the increase, stabilization and decrease of the correlation dimension D. Therefore, the wear particle group has a dynamic nature, which characterizes the formation, stabilization, and disappearance of a running-in attractor. Consequently, the dynamic characteristics and evolution of a running-in attractor can be revealed by the wear particle group.

The intrinsic relationship between the wear particle group and the running-in attractor is proved, and this is advantageous for further revealing the dynamic features of the running-in attractor and identifying the wear states.

Corporate social responsibility (CSR) practice and research regarding construction contractors are comparatively limited. The purpose of this research is to identify a series of CSR issues that reflect the major components of CSR, and to determine the perceived importance of these factors in the context of construction contractors.

A CSR indicator framework was developed based on stakeholder theory. CSR stakeholders and their corresponding CSR performance issues in construction contractors are classified into two levels, i.e. project level and organizational level. This is followed by a questionnaire survey to investigate the perceptions on relative importance of CSR issues of four key stakeholders in typical construction projects in China, i.e. construction contractors, clients, design and engineering consultancy and supervision firms.

The study highlighted a number of factors, e.g. “quality and safety of construction”, “occupational health and safety” and “supplier/partner relationship” were highly regarded; however, their relative importance varied according to the type of responding organization.

The findings indicated the major concerns of the different parties in construction projects, thereby providing a pathway for construction contractors to improve their CSR practice.

The priorities of various stakeholders described in this paper provide a useful reference for construction contractors in the selection and adoption of criteria for CSR performance. A better understanding of perceived priorities of CSR factors from different participating parties also serves useful inputs to construction contractors in their stakeholder management process.

Most epidemic transmission forecasting methods can only provide deterministic outputs. This study aims to show that probabilistic forecasting, in contrast, is suitable for stochastic demand modeling and emergency medical resource planning under uncertainty.

Two probabilistic forecasting methods, i.e. quantile regression convolutional neural network and kernel density estimation, are combined to provide the conditional quantiles and conditional densities of infected populations. The value of probabilistic forecasting in improving decision performances and controlling decision risks is investigated by an empirical study on the emergency medical resource planning for the COVID-19 pandemic.

The managerial implications obtained from the empirical results include (1) the optimization models using the conditional quantile or the point forecasting result obtain better results than those using the conditional density; (2) for sufficient resources, decision-makers' risk preferences can be incorporated to make tradeoffs between the possible surpluses and shortages of resources in the emergency medical resource planning at different quantile levels; and (3) for scarce resources, the differences in emergency medical resource planning at different quantile levels greatly decrease or disappear because of the existing of forecasting errors and supply quantity constraints.

Very few studies concern probabilistic epidemic transmission forecasting methods, and this is the first attempt to incorporate deep learning methods into a two-phase framework for data-driven emergency medical resource planning under uncertainty. Moreover, the findings from the empirical results are valuable to select a suitable forecasting method and design an efficient emergency medical resource plan.

This study aims to investigate the determinants of herd behavior in online hotel service evaluations, focusing on the cultural and geographic distance characteristics of customers.

On the basis of 381,462 TripAdvisor reviews of hotels in the USA written by more than 100,000 customers from 92 countries, this study uses the empirical analysis to explore the collective roles of cultural distance, geographic distance and hospitality experience on herd behavior in online hotel ratings.

Cultural and geographic distances between customers and product and service locations positively affect herding and these two effects are substitutable. The hospitality experience of customers attenuates the impacts of distances on herding. These results are robust for multiple hotel service ratings.

Findings help hotels understand perceptual biases of customers on hotel services under the social influence and consequently develop effective marketing strategies to boost hotel revenues and increase profitability.

The research contributes to hospitality and online review literature by understanding how cultural and geographic distances shape online hotel service evaluations under the root of the uncertainty of decision-making and the observation of others’ behavior. The research also contributes to the distances in international business literature by deepening the understanding of the substitution and heterogeneity of distance effects. Methodologically, a time-varying and monotonously increasing variable is constructed to depict customers’ hospitality experience. The extensive data volume ensures the generalizability of our results.

Sustainability and competitiveness have received extensive attentions. Despite a large number of studies on sustainability and competitiveness in the construction industry, little research has been conducted to holistically explore the interactions between these two concepts. From a dynamic transition perspective, the purpose of this paper is to link sustainability and competitiveness of construction firms by developing a Sustainability-Competitiveness Dynamic Interaction Framework (SCDIF).

Conceptual theory-building approach was adopted to develop the conceptual framework. It is an iterative analysis and synthesis process, which involves reading literature, identifying commonalities and differences, synthesizing, proposing an initial framework, collecting additional literature, and revisiting and revising the framework.

There are complex interactions between sustainability and competitiveness of construction firms. This leads to uncertain relationships between sustainability and competitiveness, which is context dependent. Under evolving economic and socio-political environments, sustainability and competitiveness of construction firms could transition from mutually exclusive to mutually supportive, and finally merge into “sustainable competitiveness.”

A SCDIF proposed in this study demonstrates that the interactions between sustainability and competitiveness evolves according to the evolving economic and socio-political environments and firms’ strategies, and thus the relationships and interactions between sustainability and competitiveness are context dependent. This framework helps corporate managers to understand how corporate sustainability and competitiveness interact with each other, thereby informing their decision-making of sustainability strategy. Similarly, the framework provides useful references for policymakers to understand the mechanisms of transitioning industries toward sustainable competitiveness.

The proposed framework offers a new perspective for understanding sustainability and competitiveness. From the dynamic transition perspective, this study effectively illustrates that the interactions between sustainability and competitiveness evolves according to the evolving economic and socio-political environments and firms’ strategies. Compared to existing approaches, the dynamic and holistic approach proposed in this paper provides the capacity to capture the complexity of sustainability and competitiveness.

To implement a risk-based regulatory approach, this paper aims to make an assessment on customers' money laundering risk and conducts some applications.

During the transition of a regulatory approach from “rule-based” to “risk-based”, this paper considers that the area of a customer, types of business and the industries to which the customer belongs are the main indicators to judge money laundering risk of a customer. Based on the statistical analysis of 221 typical money laundering cases, first-class index weights are given by using the entropy weight method and then by combining with the membership function, this paper determines a customer’s money laundering risk levels. On the basis of the entropy weight method, this paper uses the C5.0 algorithm to construct a decision tree model and then carries out application research on customer money laundering risk assessment to verify the effectiveness of the entropy weight method and the decision tree model.

This empirical research found the weights of three key money laundering indicators: customer areas, business types and corresponding industries.

Asserting that current money laundering risk assessments of customers are marginal at best, this paper contends from the perspective of practice, and applies the entropy weight method and the decision tree model for money laundering risk assessment of customers.

The purpose of this paper is to provide an understanding of principal preparation and training in China by providing a background discussion of principal preparation in a number of countries. As an illustration, it provides an overview of the curriculum used in the initial preparation of school principals at Beijing Normal University.

The paper draws mainly on writing and research from China, Australia and the USA to explore principal preparation and training in China.

In addition to providing a rich description of principal preparation in China, the paper's main findings comprise seven key challenges that confront China as it endeavours to provide quality principal preparation. These challenges include China's diversity and uneven social, cultural and educational development; limited resources in some regions throughout China; the place and importance of study tours for principal preparation; the teaching approach used to train principals; the process used for assessing principal learning during their training programs; the limited transfer of learning from the classroom to the school environment; and the timing of training for principals.

Each of the challenges arising here raises important practical implications for developers of principal training programs.

The paper paints a picture of principal preparation in China and raises a number of issues and challenges with which it continues to grapple. Of note is that China is not alone in facing some of these ongoing concerns.

Through examining the development of the video compact disc player industry in China, this article aims to explore the main characteristics of world‐first innovation and identify four success factors for innovation followers to launch world‐first products in catching‐up countries.

This article takes the form of a case study

The main characteristics of world‐first innovation in catching‐up countries include: from the demand side, innovation is mainly pulled by the local market, rather than technology‐push; from the supply side, innovation cannot isolate itself from the rest of the world – suppliers of key technologies in advanced countries play an important role; inter‐firm alliances are an increasingly important way to generate world‐first innovation; and downstream integration capabilities are required for followers to mix pieces of technologies together at competitive pricing. The success of followers from catching‐up countries to launch world‐first products hinges on the four critical factors: strengths of complementary assets; figuring out ways to meet local market demand without relying on large R&D spending; emphasizing untapped innovation opportunities by multinationals; and positioning themselves on the proper points of the globally coordinated network for innovation.

This article identifies the main characteristics of world‐first innovation and points out four success factors for innovation followers to launch world‐first products, which could be significant to managers in catching‐up countries. Findings of this paper are more relevant to large catching‐up countries such as India, Brazil, Mexico and Indonesia where a large domestic market could serve as important launch markets for the world‐first innovation.