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    Predicting the performance of MSMEs: a hybrid DEA-machine learning approach
    (Springer Science+Business Media, LLC, 2023-02-14) Boubaker S; Le TDQ; Ngo T; Manita R
    Micro, small and medium enterprises (MSMEs) dominate the business landscape and create more than half of employment worldwide. How we can apply big data analytical tools such as machine learning to examine the performance of MSMEs has become an important question to provide quicker results and recommend better and more reliable solutions that improve performance. This paper proposes a novel method for estimating a common set of weights (CSW) based on regression analysis for data envelopment analysis (DEA) as an important analytical and operational research technique, which (i) allows for measurement evaluations and ranking comparisons of the MSMEs, and (ii) helps overcome the time-consuming non-convexity issues of other CSW DEA methodologies. Our hybrid approach used several econometric and machine learning techniques (such as Tobit, least absolute shrinkage and selection operator, and Random Forest regression) to empirically explain and predict the performance of more than 5400 Vietnamese MSMEs (2010‒2016), and showed that the machine learning techniques are more efficient and accurate than the econometric ones. Our study, therefore, sheds new light on the two-stage DEA literature, especially in terms of predicting performance in the era of big data to strengthen the role of analytics in business and management.
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    From Efficiency Analyses to Policy Implications: a Multilevel Hierarchical Linear Model Approach
    (Taylor and Francis Group, 2021-09-25) Dao TTT; Mai XTT; Ngo T; Le T; Ho H
    This paper examines the key factors that influenced the cost efficiency of 7,633 Vietnamese manufacturing firms during 2010–2016 via a hierarchical linear modelling (HLM) approach. The main reason for using HLM in this case is that observations in the same group may not be independent from each other (e.g. firms operate within the same city), and some variables may not vary across those observations. Although most of the findings are consistent with previous studies, the statistical power of our HLM model is higher than that of the traditional single-level analysis, suggesting that HLM can provide better analytical insights. The results further indicate a case for cities or provinces pursuing different policies aimed at improving the performance of their local firms.
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    Decomposing productivity and efficiency of Western Australian grain producers
    (Western Agricultural Economics Association, 2013) Tozer PR; Villano R
    We provide empirical evidence to decompose productivity growth of a group of producers into technical change and efficiency measures at the farm level. Using four years of farm-level data from forty-five grain producers in the low- to medium-rainfall zone of Western Australia, we decompose productivity numbers to analyze total factor productivity. The results show that producers are generally technical, mix, and scale efficient, but the results for input and output mix efficiencies vary. The outcomes for input mix efficiency suggest that producers face some rigidity in their production decisions. In contrast, output mix efficiency suggests that most producers adjust their output mixes to account for different seasonal conditions and enterprise mixes.
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    The efficiency of the commercial banks in six Pacific Island countries : a dissertation in partial fulfilment of the requirements for the degree of Doctor in Philosophy, Banking Studies, School of Economics and Finance, Massey University, Palmerston North, New Zealand
    (Massey University, 2010) Maea, Samisoni Fotu
    This thesis explores the efficiency of the commercial banks in six Pacific Island Countries (PICs): Fiji, Papua New Guinea, Samoa, Solomon Islands, Tonga, and Vanuatu over the period 2000 to 2006 using Data Envelopment Analysis (DEA). The use of DEA is justified primarily due to the small number of commercial banks operating in these small countries. This is the first detailed study of the relative efficiency and performance of banking firms in this selected group of small countries. The dominant feature of this research is to investigate the primary prudential tools commonly used by banking supervisors in regulating the local banking system. In our understanding, this is the first effort to investigate the link between individual prudential tools and bank efficiency. The small number of banks in this dataset further enables a structural investigation of the relative efficiency across commercial banks nationally and across countries, employs a series of explanatory variables to explain the possible sources of efficiency variation, and provides a series of practical measures to validate resulting efficiency scores from DEA. This comprehensive structural construct is also a new development in bank efficiency studies. The key research finding is the identification of liquidity requirements as the main source of bank inefficiency. Capital requirements are not only ineffective in promoting bank efficiency but in the absence of formal liquidity requirements, they become a contributing factor for causing asset deterioration. Hence, asset quality is inversely related to bank efficiency. Scale inefficiency is unusually large compared with reported scale inefficiency in the literature and in most countries, it dominates technical inefficiency. Finally, efficiency-based ratios should continue to supplement resulting efficiency scores, at least in the current measurement and development of bank efficiency in the context of smaller developing economies.
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    Low-complexity block dividing coding method for image compression using wavelets : a thesis presented in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Systems Engineering at Massey University, Palmerston North, New Zealand
    (Massey University, 2007) Zhu, Jihai
    Image coding plays a key role in multimedia signal processing and communications. JPEG2000 is the latest image coding standard, it uses the EBCOT (Embedded Block Coding with Optimal Truncation) algorithm. The EBCOT exhibits excellent compression performance, but with high complexity. The need to reduce this complexity but maintain similar performance to EBCOT has inspired a significant amount of research activity in the image coding community. Within the development of image compression techniques based on wavelet transforms, the EZW (Embedded Zerotree Wavelet) and the SPIHT (Set Partitioning in Hierarchical Trees) have played an important role. The EZW algorithm was the first breakthrough in wavelet based image coding. The SPIHT algorithm achieves similar performance to EBCOT, but with fewer features. The other very important algorithm is SBHP (Sub-band Block Hierarchical Partitioning), which attracted significant investigation during the JPEG2000 development process. In this thesis, the history of the development of wavelet transform is reviewed, and a discussion is presented on the implementation issues for wavelet transforms. The above mentioned four main coding methods for image compression using wavelet transforms are studied in detail. More importantly the factors that affect coding efficiency are identified. The main contribution of this research is the introduction of a new low-complexity coding algorithm for image compression based on wavelet transforms. The algorithm is based on block dividing coding (BDC) with an optimised packet assembly. Our extensive simulation results show that the proposed algorithm outperforms JPEG2000 in lossless coding, even though it still leaves a narrow gap in lossy coding situations
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    Impact of gender and governance on microfinance efficiency
    (Elsevier, 2018-03) Bibi UB; Ozer-Balli H; Matthews CM; Tripe DT
    This study examines the efficiency of South Asian microfinance institutions (MFIs) using Data Envelopment Analysis. Bias corrected efficiency estimates for the individual MFIs are regressed on a set of explanatory variables (including governance and gender) employing the double bootstrap truncated regression approach (Simar & Wilson, 2007) and panel data regression. First stage results suggest that South Asian MFIs are more financially efficient than socially efficient. More precisely, we find that these MFIs are technically inefficient but scale efficient, and that there was some improvement in financial efficiency over time. The relatively low average efficiency scores show that there is quite a bit of variation in microfinance efficiency. Second stage regression reveals that female loan officers are positive determinants of MFIs’ efficiency. We find a strong association between a MFI’s governance and its financial and social efficiency.