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The purpose of this paper is to analyse the long-run relationship between geopolitical risk and exchange rates in four ASEAN countries.

We augment theoretical nominal exchange rate models available in the literature with the geopolitical risk index developed by Caldara and Iacoviello (2019), and then estimate these models using the ARDL approach to Cointegration.

Our analysis uncovers evidence of Cointegration in the exchange rate models when the MYR-USD, IDR-USD, THB-USD and PHP-USD exchange rates are used as dependent variable. Next, geopolitical risk is a significant long-run driver for these exchange rates. Third, in all countries higher geopolitical risk leads to a depreciation of domestic currency.

There are implications for entrepreneurs, central banks, portfolio managers and arbitrageurs who actively trade in financial markets. Financial market players can benefit from a better understanding of how geopolitical events affect the portfolio of financial assets across various countries, while entrepreneurs can work out hedging strategies.

This is a contribution to the study of interlinkages between political risk and foreign exchange markets. It is the first study to adopt the geopolitical risk index of Caldara and Iacoviello (2019) to the study the foreign exchange markets of ASEAN countries.

Various empirical studies have demonstrated that house prices in different geographic regions have a tendency to co‐move. But these studies have focused on developed economies in the west. The purpose of this paper is to test this hypothesis in the case of three major urban areas in the rapidly developing economy of Malaysia, namely Klang Valley, Penang and Johor.

Using Pesaran et al.'s bounds testing approach to cointegration and Granger non‐causality analysis, the short‐run and long‐run dynamics of regional house prices are analysed.

First, house prices in all three regions appear to be cointegrated. Second, there is evidence of short‐run bi‐directional causality between house prices in all regions. Third, long‐run house price movements in Johor are not Granger‐caused by house prices in Klang Valley and Penang. This observation could be rationalised in the light of the argument that Johor house values may be more closely aligned with activities in the Singaporean economy, given the region's geographic proximity to Singapore.

The findings have several practical implications for housing investors who intend to optimise investment decisions on housing purchases. The understanding of the nature of regional house dynamics could also enrich the government's knowledge of how the local housing markets work and enable the design and implementation of relevant housing policies.

This is the first known study that establishes stylised facts of lead‐lag relationships for regional house prices, while also providing short‐run and long‐run estimates of regional house price interactions for Malaysia.

There exists a voluminous literature which examines house price diffusions across space and quality tiers. Numerous observers have pointed out that housing price dynamics can also be analysed in terms of house price diffusions across different housing sub‐markets (e.g. landed vs non‐landed housing). However, there has been no research to document these cyclical interactions. The purpose of this paper is to remedy this research gap by offering evidence of cyclical dynamics between different housing sub‐markets for the case of Malaysia.

The dynamics between house prices of non‐landed housing (condominium) and landed housing (terrace, semi‐detached and detached housing sub‐markets) are analysed. Band‐pass filters are first used to extract the cyclical components from the four house price series. Next, interactions between house price cycles are documented using cross‐correlation analysis, Granger‐causality tests and impulse response functions. Finally, the out‐of‐sample forecasting performance of the respective house price series is examined.

The author finds that condominium price cycles are exogenous in that they lead the price cycles in other housing sub‐markets by one‐ to two‐quarters. Second, condominium price cycles drive price cycles in the terrace and detached sub‐markets. Third, cycles in condominium prices are able to predict house price cycles in other sub‐markets with a high degree of precision.

This is the first known study that establishes stylised facts of lead‐lag relationships between house price cycles in different housing sub‐markets. The findings have several practical implications for housing investors who intend to optimise investment decisions on housing purchases.

Examines the economy of Southeast Asia during the period 1997 to 1999 against a background of socio‐economic theory and a transition from disequilibrium to general stable and equilibrium conditions. Discusses solutions towards establishing self‐regulating mechanisms needed for a free, just and stable economy and society: reform of officially organized securities commodities and foreign exchange makets; reform of the public budget and budgetary policies; and reform of the foreign exchange system and internaitonal commercial and financial relations.

This paper aims to maintain the high service quality of the long-term care service providers by establishing a knowledge-based system so as to enhance the service quality of nursing homes and the performance of its nursing staff continually.

An intelligent case-based knowledge management system (ICKMS) is developed with the integration of two artificial intelligence techniques, i.e. fuzzy logic and case-based reasoning (CBR). In the system, fuzzy logic is adopted to assess the performance through the analysis of the long-term care services provided, nurse performance and elderly satisfaction, whereas CBR is used to formulate a customized re-training program for quality improvement. A case study is conducted to validate the feasibility of the proposed system.

The empirical findings indicate that the ICKMS helps in identification of those nursing staff who cannot meet the essential service standard. Through the customized re-training program, the performance of the nursing staff can be greatly enhanced, whereas the medical errors and complaints can be considerably reduced. Furthermore, the proposed methodology provides a cost-saving approach in the administrative work.

The findings and results of the study facilitate decision-making using the ICKMS for the long-term service providers to improve their performance and service quality by providing a customized re-training program to the nursing staff.

This study contributes to establishing a knowledge-based system for the long-term service providers for maintaining the high service quality in the health-care industry.

The purpose of this paper is to examine how a company’s symmetrical internal communication efforts could influence its employees’ perception of relationship outcomes with the company and the subsequent employee communication behaviors about the company to others and their turnover intention. Additionally, the mediation effects of employee-organization relationship (EOR) quality between symmetrical internal communication and employee engagement were tested.

The study collected the data from a survey of randomly selected 438 individuals who work as sales representatives of the case organization. Respondents were randomly selected through stratified sampling. For the overall statistical procedure, this study adopted the two-step structural equation modeling: on the basis of the final measurement model analysis from confirmatory factor analysis, the proposed structural model was tested using latent variables.

The findings of this research clearly demonstrate: employee/internal communication management is linked with employee engagement; employee engagement enhances supportive employee communication behaviors and reduces turnover intention. Also, the mediation results show strong mediation of EORs on the effects of symmetrical internal communication on employee engagement.

Employees’ communication behaviors such as megaphoning and scouting have special strategic values to organizations. With information seeking, selecting, forwarding, and sharing behaviors of employees, organizations may obtain more valuable information than through formal procedures and channels. Professional literature has long been supporting the importance of fostering positive employee communication behaviors (ECBs), suggesting that WOM and information from the employees deemed as most trustworthy by the external publics. ECBs about their organizations may be viewed as a testament of the quality of EOR. This study results show that employee engagement plays a key role in creating positive ECBs.

Pragmatically, as noted in the findings, symmetrical communication is an important factor that leads to positive ECB. To facilitate employees’ favorable communication regarding an organization, therefore, the organization needs to practice a two-way, employee-centered symmetrical communication system in its everyday communication management. Communication managers are advised to nurture internal communication practices that listen to the employees and invite their participation in addition to providing complete and fair information to employees. Second, by showing the significant positive influence of EOR on employee engagement and ECB, the finding of the study suggests that strategic relationship management with internal publics affect overall management effectiveness. Hence, organizational managers need to adopt various relationship cultivation strategies in their communication with employees, which have been previously proposed by several studies.

The findings of the study demonstrated that the effects of employee relationship management and symmetrical internal communication indeed exist beyond ECBs to the actual managerial outcomes. The findings also suggest a three-stage model of employee communication management: employee/internal communication management antecedents; employee engagement; and supportive outcomes of effective employee communication programs, such as supportive/extra ECBs.

The presented research explored artificial intelligence (AI) application in the learning and development (L&D) function. Although a few studies reported AI and the people management processes, a systematic and structured study that evaluates the integration of AI with L&D focusing on scope, adoption and affecting factors is mainly absent. This study aims to explore L&D-related AI innovations, AI’s role in L&D processes, advantages of AI adoption and factors leading to effective AI-based learning following the analyse, design, develop, implement and evaluate approach.

The presented research has adopted a systematic literature review method to critically analyse, synthesise and map the extant research by identifying the broad themes involved. The review approach includes determining a time horizon, database selection, article selection and article classification. Databases from Emerald, Sage, Francis and Taylor, etc. were used, and the 81 research articles published between 1996 and 2022 were identified for analysis.

The result shows that AI innovations such as natural language processing, artificial neural networks, interactive voice response and text to speech, speech to text, technology-enhanced learning and robots can improve L&D process efficiency. One can achieve this by facilitating the articulation of learning module, identifying learners through face recognition and speech recognition systems, completing course work, etc. Further, the result also shows that AI can be adopted in evaluating learning aptitude, testing learners’ memory, tracking learning progress, measuring learning effectiveness, helping learners identify mistakes and suggesting corrections. Finally, L&D professionals can use AI to facilitate a quicker, more accurate and cheaper learning process, suitable for a large learning audience at a time, flexible, efficient, convenient and less expensive for learners.

In the absence of any systematic research on AI in L&D function, the result of this study may provide useful insights to researchers and practitioners.

This paper aims to explore principal drivers affecting prices in the Australian housing market, aiming to detect the presence of housing bubbles within it. The data set analyzed covers the past two decades, thereby including the period of the most recent housing boom between 2012 and 2015.

The paper describes the application of combined enhanced rigorous econometric frameworks, such as ordinary least square (OLS), Granger causality and the Vector Error Correction Model (VECM) framework, to provide an in-depth understanding of house price dynamics and bubbles in Australia.

The empirical results presented reveal that Australian house prices are driven primarily by four key factors: mortgage interest rates, consumer sentiment, the Australian S&P/ASX 200 stock market index and unemployment rates. It finds that these four key drivers have long-term equilibrium in relation to house prices, and any short-term disequilibrium always self-corrects over the long term because of economic forces. The existence of long-term equilibrium in the housing market suggests it is unlikely to be in a bubble (Diba and Grossman, 1988; Flood and Hodrick, 1986).

The foremost contribution of this paper is that it is the first rigorous study of housing bubbles in Australia at the national level. Additionally, the data set renders the study of particular interest because it incorporates an analysis of the most recent housing boom (2012-2015). The policy implications from the study arise from the discussion of how best to balance monetary policy, fiscal policy and macroeconomic policy to optimize the steady and stable growth of the Australian housing market, and from its reconsideration of affordability schemes and related policies designed to incentivize construction and the involvement of complementary industries associated with property.

The purpose of this paper is to address “how Toyota can continuously and consistently achieve its dramatic success through its competences ‐ continuous waste elimination and the objective of long term philosophy”; the paper aims to summarize some solid suggestions and comprehensive ideas for those industries planning to implement lean production.

The methodology used is the case based approach (CBA), which described lean supply chain (LSC) through value stream mapping (VSM) using a case study from the Ford Motor Company in Chung Li, Taiwan. The paper follows a four‐step problem solving process to demonstrate how lean supply chain affects product cost and quality.

Using VSM case study to demonstrate LSC, all the measurable indices helpful for cost reduction, quality enhancement and lead time reduction are shown. The paper also provides some recommendations and basic principles to implement VSM successfully through P‐D‐C‐A improving cycle.

Since a comprehensive demonstration of VSM implementation is likely to be both expensive and time‐consuming, this study provides a case study from the Ford Motor Company in Taiwan.

VSM through lean process is considered to be one of the best practices in supply chain management. It has been shown to be successful for implementing lean production in Toyota Production System (TPS). However, other competitors struggle despite adopting similar principles. It seems that there is a special ingredient within TPS that Toyota's competitors do not fully comprehend.

This paper not only shows the value of VSM as a supply chain tool in implementing lean production; but also provides industrial insight for enterprising companies to follow a four‐step problem‐solving process to effectively develop their lean supply chain.

The marketing information system (MkIS) in the data-rich business environment receives all the attention these days, but as essential and perhaps even more essential is the marketing information system management capability (MkISMC). Although many service firms apprehend the return from MkIS, others clearly struggle. It seems that MkIS management capability dynamics and their direct/indirect holistic influence on service firm's competitive performance (SFCP) are unsolved in the current data-driven service economy. This study aims to conceptualize a model and test the antecedents on service firms' competitive performance.

This study utilizes a survey of a sizeable sample of service firms’ managers at the firm level. A total of 250 useable responses were obtained and analyzed through structural equation modeling.

Results reveal that variables under their respective direct influences are positively and significantly related. Interestingly, MkISMC has a relatively large magnitude of positive and direct effects on service firms' competitive performance. The other variables, such as the use of marketing analytics (UMAN), service innovation and management (SINM), partially mediate the effect of MkISMC on the competitive performance of service firms.

The findings inform practitioners that MkISMC, UMAN and SINM play a vital role in attaining service firms' competitive performance in the data-rich environment. Overall, it deepens the understanding of the mediation effect of UMAN and SINM of service firms on competitive performance.

The study advances theoretical understanding of resource-based view (RBV), market orientation and dynamic capability that formulate the relationship of MkISMC, UMAN and SINM in attaining SFCP in the ever-changing data-driven business economy.