The strategic role of HRM in organizational performance: the large hotel sector in New Zealand

It is a commonly belief held that in today’s highly unstable and competitive business environment, human resources (HR) are the best and ultimate resource an organization can buy for its survival and long-term success. Thus, human resources are attracting more and more attention from both academia and industries. The traditional role of human resource management, which focuses on the various practices used to manage people within an organization, is widely challenged. In the past two decades, more and more human resource managers and scholars have advocated strongly that human resources have great potential that has been ‘hidden’, and, instead, should be fully considered during an organization’s strategic planning and decision-making process. This thesis is devoted to exploring whether and how HR contributes to improved organizational performance when it is integrated with the organization’s strategic planning and decision making at different levels. The research is conducted on the large hotel sector in New Zealand. This context was chosen because of the gaps in the current strategic human resource management studies – they are dominated by research on manufacturing sectors in Europe and the US and lack evidence from the service industries in other parts of the world. The significance of the hotel business to New Zealand’s economy as a whole adds value to the justification. A mixed-method approach, namely interviews and a web survey, was used to collect data from general managers of hotels with more than 50 rooms throughout New Zealand. Emphasis was put on two major areas: current HR practices in the hotels, and the HR-strategy integration level and its influence on a hotel’s financial and non-financial performances. To explore the influence in depth, factors such as the size and ownership of the hotel, as well as business strategies being used by the hotels, were taken into consideration. Results from the two sources (interviews and a web survey) are carefully compared and contrasted. Results of the research indicate that the importance of HR is widely recognized by New Zealand hotel managers. HR practices that are being used by hotels all over the world have been adopted by hotels in New Zealand. More importantly, the HR-strategy integration present in New Zealand hotels is found have a positive association with a hotel’s future performance, through the hotel’s HR outcomes. More particularly, the high level of HR’s involvement in a hotel’s strategic decision-making process is significantly linked with the functional flexibility of a hotel’s staff, which in turn links to the hotel’s labour productivity. The findings of the thesis contribute to the theory development of strategic human resource management in that it supports the proposition that close HR-strategy integration has positive impacts on an organization’s performance. Also, it supports the hypothesis that there exists a time lag between the integration and the performance. The methodology used by the thesis also contributes to research in strategic human resources and hotel studies. The implications of the findings for hotel practitioners and policy-makers within the tourism industry are also discussed

Bayesian methods of vector autoregressions with tensor decompositions

Vector autoregressions (VARs) are popular in analyzing economic time series. However, VARs can be over-parameterized if the numbers of variables and lags are moderately large. Tensor VAR, a recent solution to overparameterization, treats the coefficient matrix as a third-order tensor and estimates the corresponding tensor decomposition to achieve parsimony. In this paper, the inference of Tensor VARs is inspired by the literature on factor models. Firstly, we determine the rank by imposing the Multiplicative Gamma Prior to margins, i.e. elements in the decomposition, and accelerate the computation with an adaptive inferential scheme. Secondly, to obtain interpretable margins, we propose an interweaving algorithm to improve the mixing of margins and introduce a post-processing procedure to solve column permutations and sign-switching issues. In the application of the US macroeconomic data, our models outperform standard VARs in point and density forecasting and yield interpretable results consistent with the US economic history

Salt-tolerant cation exchange HD-Sb hydrogel membrane: mAb purification performance in flowthrough mode

Development of Protein A based purification platforms have simplified the downstream processing of monoclonal antibodies (mAb), the largest component of biopharmaceuticals. The ever increasing titer of the cell culture process is putting more pressure on the downstream process to further increase its productivity. The classical Protein A based mAb purification platform consists of two polishing steps, bind and elute cation-exchanger and flowthrough anion-exchanger. Cation-exchange chromatography is very efficient at the separation of HCP, leached Protein A and product-related impurities such as aggregates and fragments in bind and elute mode. However, anion-exchange chromatography is a proven technology to remove DNA, viruses, endotoxins and HCP in flowthrough mode. This study compares bind and elute mAb purification performance with that in flowthrough mode for the Natrix HD-Sb hydrogel membrane. Natrix HD-Sb is a salt-tolerant strong cation-exchange membrane augmented with hydrophobic butyl groups. This study demonstrates the effectiveness of Natrix HD-Sb chemistry in removing aggregates and HCP from challenging feed at high load with significant improvement in productivity and simplicity. The flowthrough separation performance of Natrix HD-Sb at neutral pH will be highlighted to show the potential of having tandem polishing steps (cation-exchange → anion-exchange) without needing any pH or conductivity adjustment. This tandem membrane approach has the potential for streamlining the downstream process for increased productivity & process efficiency

DDX5 facilitates HIV-1 replication as a cellular co-factor of Rev.

HIV-1 Rev plays an important role in the late phase of HIV-1 replication, which facilitates export of unspliced viral mRNAs from the nucleus to cytoplasm in infected cells. Recent studies have shown that DDX1 and DDX3 are co-factors of Rev for the export of HIV-1 transcripts. In this report, we have demonstrated that DDX5 (p68), which is a multifunctional DEAD-box RNA helicase, functions as a new cellular co-factor of HIV-1 Rev. We found that DDX5 affects Rev function through the Rev-RRE axis and subsequently enhances HIV-1 replication. Confocal microscopy and co-immunoprecipitation analysis indicated that DDX5 binds to Rev and this interaction is largely dependent on RNA. If the DEAD-box motif of DDX5 is mutated, DDX5 loses almost all of its ability to bind to Rev, indicating that the DEAD-box motif of DDX5 is required for the interaction between DDX5 and Rev. Our data indicate that interference of DDX5-Rev interaction could reduce HIV-1 replication and potentially provide a new molecular target for anti-HIV-1 therapeutics

Low Cost Interconnected Architecture for the Hardware Spiking Neural Networks

A novel low cost interconnected architecture (LCIA) is proposed in this paper, which is an efficient solution for the neuron interconnections for the hardware spiking neural networks (SNNs). It is based on an all-to-all connection that takes each paired input and output nodes of multi-layer SNNs as the source and destination of connections. The aim is to maintain an efficient routing performance under low hardware overhead. A Networks-on-Chip (NoC) router is proposed as the fundamental component of the LCIA, where an effective scheduler is designed to address the traffic challenge due to irregular spikes. The router can find requests rapidly, make the arbitration decision promptly, and provide equal services to different network traffic requests. Experimental results show that the LCIA can manage the intercommunication of the multi-layer neural networks efficiently and have a low hardware overhead which can maintain the scalability of hardware SNNs