Monitoring the foreign exchange rate benchmark fix

ABSTRACT

We develop a Manipulation Index (ManIx) that captures the potential manipulation intention of dealers during the World Markets/Reuters (WMR) benchmark (London Close) period at 4 pm London time through a unique algorithm and simulation. The application of this model (using a dataset with dealers’ identities) can identify banks that are prone to potential manipulative behavior. The results concerning the identified banks are validated by the regulatory investigations. Implementation of this algorithm allows regulators better direct their limited resources towards more targeted in-depth investigation.     

Effects of individual resources and team-member exchange on service quality

While workplace resources are generally viewed as positively affecting performance, some studies indicate that not all resources increase performance. This study addresses the controversial disparate effects of workplace resources on performance by exploring functionally classified workplace resources in self-managing service teams and their relative impacts on team service quality. Considering membership dynamics and consequences between members, a field experiment was conducted in a cafeteria, with data collected through a working diary for workplace resources and a customer survey to evaluate service quality. Results suggest that efficacy-resources in self-managing teams should be controlled with caution as they may adversely affect team service quality. Supporting the person–situation interactionism perspective, workplace resources interact dynamically with individual employees and with situations. Esteem-resources were found to increase team service quality, while team-member exchange not only improved team service quality but also moderated the impact of esteem-resources on team service quality.     

The Relationship Between Consumer-Brand Identification and Brand Extension

The present research aims at examining the role of consumer-brand identification (CBI) in attitude toward brand extension regarding the congruency between the values of consumers and brands. In this way, the benefits of CBI to consumers and brand managers are outlined. This research has been conducted through designing a survey and collecting data through a questionnaire. For data mining and investigating the model, the SEM approach is implemented. According to the findings, high levels of CBI lead to positive attitudes toward the brand extension, and that value congruity positively impacts this relationship. The results outline that CBI impacts fit and tie in separate ways, so that CBI effect on fit is more substantial. Furthermore, according to the results, in comparison to the role of tie, the role of fit is more significant in predicting attitudes toward brand extension. The sample from university students is appropriate for testing theory, but limits generalizing the results of the research. In addition, this research has studied one product category and is limited in this perspective. The findings have remarkable recommendations for implementing brand extension as they emphasize the role of perceived fit. Moreover, by reexamining CBI in a less known market, the research has outlined its positive outcomes for firms. This research has used perceived tie in a brand extension context and, similar to perceived fit, has implemented it as another factor to predict attitude toward brand extension. In addition, this research is unique, as it has investigated CBI in a new context.     

Dynamic linkages among equity markets in the Middle East and North African countries

The relaxation of security laws and regulations in emerging markets in the Middle East and North Africa (MENA) provides abundant opportunities for foreign investors. These markets exhibit high-expected returns and substantial volatility. In this paper, we investigate the lead/lag relationship between the MENA countries and regions. We find no market causality or spillover from one country to another in the North Africa region. Our results for the Levant region reveal that there are linkages between stock markets in this region. The results for the Gulf Cooperation Council (GCC) region show that there is more interaction and linkage in the GCC region than in the North Africa and Levant regions. An unexpected result is that UAE's stock market leads all the markets in this region. Finally, we investigate linkages among the three regions. We find that GCC influences the other two regions.     

Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models

The study examines the relative ability of various models to forecast daily stock index futures volatility. The forecasting models that are employed range from naïve models to the relatively complex ARCH-class models. It is found that among linear models of stock index futures volatility, the autoregressive model ranks first using the RMSE and MAPE criteria. We also examine three nonlinear models. These models are GARCH-M, EGARCH, and ESTAR. We find that nonlinear GARCH models dominate linear models utilizing the RMSE and the MAPE error statistics and EGARCH appears to be the best model for forecasting stock index futures price volatility.     

Linking performance drivers in production planning and inventory control to process choice

This study investigates how process choice relates to production planning and inventory control decisions. We empirically examine the validity of deductively derived patterns about these types of decisions. More importantly, we look for normative insights by exploring how production planning and inventory control decisions affect operations performance. Our findings show that production line and continuous flow plants use more of a level production strategy, and carry less raw material and work-in-process inventory. The performance drivers for these plants, through which the operations function excels, are effective utilization of equipment, reduced finished goods inventory, and reduced setup down time. To gain forward demand visibility and batching economies, job and batch shops rely much more on backlogs in their planning process. These plants use more of a production chase strategy and position inventory lower in the bills of materials. Four performance drivers for top-performing job and batch shops are to find ways that better anticipate customers' orders, have a more responsive chase strategy, carry less raw material or purchased inventory, and shorten production planning horizon, partly through less reliance on backlogs. It is intriguing that top-performing plants not only do the expected things, given their choice of process, but also excel in selected dimensions—some of which fit the profile normally associated with a different process choice. To monitor and continuously improve operations, evaluation ‘scorecards’ should pay particular attention to performance drivers, which change depending on the plant's process choice.     

Sustainable resource use,economic development,and public regulation

The role of production technology for sustainable economic growth and resource management in the multispecies renewable resources industries is a neglected issue, particularly in complex tropical ecosystems. Given the still rudimentary understanding of biological interactions among species, even in most temperate ecosystems, the importance of under-standing the technological and economic interactions is heightened for sustainable economic growth and public regulation. This paper evaluates these interactions for the multiproduct gill net fisheries of Peninsular Malaysia. Standard price and quantity controls may have little promise. Gear regulations, a policy of constant escapement, and managing the entire mix of species as a single stock for economic rather than biomass yield appear the most promising management tools given the limited regulatory options.     

Towards a resilience management framework for complex enterprise systems upgrade implementation

The lack of knowledge of how resilience management supports enterprise system (ES) projects accounts for the failure of firms to leverage their investments in costly ES implementations. Using a structured-pragmatic-situational (SPS) case study research approach, this paper reports on an investigation into the resilience management of a large utility company as it implemented an ES upgrade. Drawing on the literature and on the case study findings, we developed a process-based resilience management framework that involves three strategies (developing situation awareness, demystifying threats, and executing restoration plans) and four organisational capabilities that transform resilience management concepts into practices. We identified the crucial phases of ES upgrade implementation and developed indicators for how different strategies and capabilities of resilience management can assist managers at different stages of an ES upgrade. This research advances the state of existing knowledge by providing specific and verifiable propositions for attaining a state of resilience, the knowledge being grounded in the empirical reality of a case study. Moreover, the framework offers ES practitioners a roadmap to better identify appropriate responses and levels of preparedness.     

A fuzzy goal programming approach to analyse sustainable development goals of India

Energy policy, environmental planning and economic development play a key role in sustainable development. Sustainable development requires suitable and strategic policies satisfying multiple and conflicting objectives. Fuzzy goal programming (FGP) is a well-known approach in multi-criteria decision-making for its practical application. In this article, a FGP approach is proposed to analyse environmental, energy and sustainability goals of India by the year 2030 with reference to the key economic sectors of India. The presented model analyses the improvement opportunities, requirement of efforts and implementation of the sustainable development plans. Numerical illustration is also provided for validation and application of the proposed model.     

Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High-Dimension Regime

In this study, we suggest pretest and shrinkage methods based on the generalised ridge regression estimation that is suitable for both multicollinear and high-dimensional problems. We review and develop theoretical results for some of the shrinkage estimators. The relative performance of the shrinkage estimators to some penalty methods is compared and assessed by both simulation and real-data analysis. We show that the suggested methods can be accounted as good competitors to regularisation techniques, by means of a mean squared error of estimation and prediction error. A thorough comparison of pretest and shrinkage estimators based on the maximum likelihood method to the penalty methods. In this paper, we extend the comparison outlined in his work using the least squares method for the generalised ridge regression.