High-performance work system or “wolf in sheep’s clothing?” a mediating effect of organisational cynicism and its outcome

Cynicism is new developing pattern of employer–employee relations. Current academicians realise the profound effect which cynicism can have on organisations, this significance of understanding the seemingly widespread organisational phenomenon. This study takes a systematic view in which organisational cynicism considered as negative attitude directed, particularly towards the educational sector. The current study aimed to endeavours to examine the mediating role of organisational cynicism on high-performance work system with the outcome of organisational citizenship behaviour among teachers of the public schools in Malaysia. The current study will show the work environmental factors and personal characteristics in determining organisational cynicism and will suggest the causes and consequences of cynicism

A review of traditional cost system versus activity based costing approaches

In the last two decades, business environment has been changing rapidly with fierce global competition. Firms using the traditional costing system were forced to change from their old system traditional-cost method and to accept the newer cost system, better known as the activity based on costing (ABC system). The new system is able to support and enhance decision making of the decision makers, besides being adaptable to the new business environment. Therefore, this paper aimed to review the applications and importance of both traditional cost system and ABC system for business decision making, and compare the results of ABC and the traditional costing systems via literature reviews of works by previous authors. The results reflected that activity based on the costing system is a better system comparing to the traditional costing systems. ABC system enhances decision making of the interested user with its better adaptable costing features to support the new business environment and global business competition. It thus creates a more sustainable source of competitive advantage. In addition, it identifies the under-costed and over-costed of the products of a firm

Syndromic surveillance: STL for modeling, visualizing, and monitoring disease counts

<p>Abstract</p> <p>Background</p> <p>Public health surveillance is the monitoring of data to detect and quantify unusual health events. Monitoring pre-diagnostic data, such as emergency department (ED) patient chief complaints, enables rapid detection of disease outbreaks. There are many sources of variation in such data; statistical methods need to accurately model them as a basis for timely and accurate disease outbreak methods.</p> <p>Methods</p> <p>Our new methods for modeling daily chief complaint counts are based on a seasonal-trend decomposition procedure based on loess (STL) and were developed using data from the 76 EDs of the Indiana surveillance program from 2004 to 2008. Square root counts are decomposed into inter-annual, yearly-seasonal, day-of-the-week, and random-error components. Using this decomposition method, we develop a new synoptic-scale (days to weeks) outbreak detection method and carry out a simulation study to compare detection performance to four well-known methods for nine outbreak scenarios.</p> <p>Result</p> <p>The components of the STL decomposition reveal insights into the variability of the Indiana ED data. Day-of-the-week components tend to peak Sunday or Monday, fall steadily to a minimum Thursday or Friday, and then rise to the peak. Yearly-seasonal components show seasonal influenza, some with bimodal peaks.</p> <p>Some inter-annual components increase slightly due to increasing patient populations. A new outbreak detection method based on the decomposition modeling performs well with 90 days or more of data. Control limits were set empirically so that all methods had a specificity of 97%. STL had the largest sensitivity in all nine outbreak scenarios. The STL method also exhibited a well-behaved false positive rate when run on the data with no outbreaks injected.</p> <p>Conclusion</p> <p>The STL decomposition method for chief complaint counts leads to a rapid and accurate detection method for disease outbreaks, and requires only 90 days of historical data to be put into operation. The visualization tools that accompany the decomposition and outbreak methods provide much insight into patterns in the data, which is useful for surveillance operations.</p

Preserving privacy and fairness in peer-to-peer data integration

Peer-to-peer data integration - a.k.a. Peer Data Management Systems (PDMSs) - promises to extend the classical data integration approach to the Internet scale. Unfortunately, some challenges remain before realizing this promise. One of the biggest challenges is preserving the privacy of the exchanged data while passing through several intermediate peers. Another challenge is protecting the mappings used for data translation. Protecting the privacy without being unfair to any of the peers is yet a third challenge. This paper presents a novel query answering protocol in PDMSs to address these challenges. The protocol employs a technique based on noise selection and insertion to protect the query results, and a commutative encryption-based technique to protect the mappings and ensure fairness among peers. An extensive security analysis of the protocol shows that it is resilient to several possible types of attacks. We implemented the protocol within an established PDMS: the Hyperion system. We conducted an experimental study using real data from the healthcare domain. The results show that our protocol manages to achieve its privacy and fairness goals, while maintaining query processing time at the interactive level

Features of Gulf Cooperation Council banks investment in Malaysia

Finance is the lifeblood of trade and commercial industry. Today’s competitive markets uses of complementary resources in collaborative agreements for many enterprises are the only means to expand internationally and gain global competitiveness. Trades between countries occur by exchanging goods and/or services with their counterparts. The economic interactions between parts of the world with another have expanded over the centuries and exerted significant impact on the world’s economic development. This study is among the earliest to investigate the various GCC bank features that operate in Malaysia. Seven large GCC banks in Malaysia were studied to document the GCC Banks features that have invested in Malaysia. The data of this study were collected through surfing the websites of all these GCC banks, conducting semi-structured interviews with the top managements of these banks and through reviewing, tracing and comparing the information of their past and current from literature works to report the features of GCC banks investment in Malaysia

A Visual Analytics Approach to Understanding Spatiotemporal Hotspots

As data sources become larger and more complex, the ability to effectively explore and analyze patterns amongst varying sources becomes a critical bottleneck in analytic reasoning. Incoming data contains multiple variables, high signal to noise ratio, and a degree of uncertainty, all of which hinder exploration, hypothesis eneration/exploration, and decision making. To facilitate the exploration of such data, advanced tool sets are needed that allow the user to interact with their data in a visual environment that provides direct analytic capability for finding data aberrations or hotspots. In this paper, we present a suite of tools designed to facilitate the exploration of spatiotemporal datasets. Our system allows users to search for hotspots in both space and time, combining linked views and interactive filtering to provide users with contextual information about their data and allow the user to develop and explore their hypotheses. Statistical data models and alert detection algorithms are provided to help draw user attention to critical areas. Demographic filtering can then be further applied as hypotheses generated become fine tuned. This paper demonstrates the use of such tools on multiple geo-spatiotemporal datasets

Causes of organizational cynicism and its consequence on teaching staff in Malaysia

Cynicism reveals itself as a new pattern in employer and employee relations. Now academicians are realising the effect that cynicism can have on organizations. This phenomenon has widespread in various kinds of organizations. This study considering a systematized view in which organizational cynicism measured as a negative behaviour, mainly in the educational sector. Current study aimed to endeavours to analyse the mediator role of organizational cynicism on the relationship among workplace incivility, psychological contract violation, with the outcome of organisational citizenship behaviour among teaching staff of the public secondary schools of Malaysia. The current study emphasises the value of working environment and personal characteristics of employees in determining organisational cynicism and will suggest the causes and consequences of cynicism

COVID-19 Intelligence-Driven Operational Response Platform: Experience of a Large Tertiary Multihospital System in the Middle East

The COVID-19 pandemic has resulted in global disruptions within healthcare systems, leading to quick dynamic fluctuations in hospital operations and supply chain management. During the early months of the pandemic, tertiary multihospital systems were highly viewed as the go-to hospitals for handling these rapid healthcare challenges caused by the rapidly increasing number of COVID-19 cases. Yet, this pandemic has created an urgent need for coordinated mechanisms to alleviate increasing pressures on these large multihospital systems and ensure services remain high-quality, accessible, and sustainable. Digital health solutions have been identified as promising approaches to address these challenges. This case report describes results for developing multidisciplinary visualizations to support digital health operations in one of the largest tertiary multihospital systems in the Middle East. The report concludes with some lessons and insights learned from the rapid development and delivery of this user-centric COVID-19 multihospital operations intelligent platform