Productivity growth and efficiency change in Malaysian manufacturing : recent evidence from disaggregated data

This paper estimates productivity growth in Malaysian manufacturing over the period 1983-1999. Malmquist productivity Indices (MPIs) have been computed using non parametric Data Envelopment Analysis (DEA) type linear programming, which show productivity growth sourced from efficiency change and growth in technology. Unlike previous studies, this study identifies the Malaysian manufacturing industries at the five digit breakdown of Malaysian Standard Industrial Classification (MSIC) thereby revealing more industry specific efficiency and technical growth patterns. Results indicate that two third of the industries (76 out of total 114 categories) experienced average annual
productivity improvement ranging from 0.1% to 7.8% over the sampled period. Average annual technical progress was recorded by 95 industry categories while technical efficiency improvement was achieved by 53 industries. Overall yearly average indicated relatively low productivity growth from the mid 1990’s onwards caused by either efficiency decline or technical regress. Summary results for industries reveal that some of the high rates of productivity growth have been recorded in glass and glass products (7.3%), Petroleum and coal (7.2%), industrial chemicals (4.9%) contributed from both efficiency improvement and technical progress ranging from 0.8% to 5.4% and from 1.7% to 4.1%, respectively. These results are expected to have some implications for ongoing and future strategic policy reform in Malaysian manufacturing generating a more sustainable growth for specific industry categories.

Evaluation of research in efficiency and productivity:a survey and analysis of the first 30 years of scholarly literature in DEA

Since the original Data Envelopment Analysis (DEA) study by Charnes et al. [Measuring the efficiency of decision-making units. European Journal of Operational Research 1978;2(6):429–44], there has been rapid and continuous growth in the field. As a result, a considerable amount of published research has appeared, with a significant portion focused on DEA applications of efficiency and productivity in both public and private sector activities. While several bibliographic collections have been reported, a comprehensive listing and analysis of DEA research covering its first 30 years of history is not available. This paper thus presents an extensive, if not nearly complete, listing of DEA research covering theoretical developments as well as “real-world” applications from inception to the year 2007. A listing of the most utilized/relevant journals, a keyword analysis, and selected statistics are presented.

Costs and efficiency of higher education institutions in England:a DEA analysis

As student numbers in higher education in the UK have expanded during recent years, it has become increasingly important to understand its cost structure. This study applies Data Envelopment Analysis (DEA) to higher education institutions in England to assess their cost structure, efficiency and productivity. The paper complements an earlier study that used parametric methods to analyse the same panel data. Interestingly, DEA provides estimates of subject-specific unit costs that are in the same ballpark as those provided by the parametric methods. The paper then extends the previous analysis and finds that further student number increases of the order of 20–27% are feasible through exploiting operating and scale efficiency gains and also adjusting student mix. Finally the paper uses a Malmquist index approach to assess productivity change in the UK higher education. The results reveal that for a majority of institutions productivity has actually decreased during the study period.

The Relative Efficiency of International, Domestic, and Budget Airlines : Nonparametric Evidence

This study determines whether the inclusion of low-cost airlines in a dataset of international and domestic airlines has an impact on the efficiency scores of so-called ‘prestigious’ purportedly ‘efficient’ airlines. This is because while many airline studies concern efficiency, none has truly included a combination of international, domestic and budget airlines. The present study employs the nonparametric technique of data envelopment analysis (DEA) to investigate the technical efficiency of 53 airlines in 2006. The findings reveal that the majority of budget airlines are efficient relative to their more prestigious counterparts. Moreover, most airlines identified as inefficient are so largely because of the overutilization of non-flight assets.

Operating efficiency and return to scale of Malaysian REITS: The preliminary findings

This paper aims to present preliminary findings on measuring the technical efficiencies using Data Envelopment Analysis (DEA) in Malaysian Real Estate Investment Trusts (REITs) to determine the best practice for operations which include the asset allocation and scale size to improve the performance of Malaysian REITs. Variables identified as input and output will be assessed in this cross section analysis using the operational approach and Variable Return to Scale DEA (VRS-DEA) by focusing on Malaysian REITs for the year 2013. Islamic REITs have higher efficiency score as compared to the conventional REITs for both models. Diversified REITs are more efficient as compared to the specialised REIT using both models. For Model 1, the negative inefficient value is identified in the managerial inefficiency as compared to the scale inefficiency. This shows that inputs are not fully minimised to produce more outputs. However, when other expenses are considered as different input variables, the efficiency score becomes higher from 60.3% to 81.2%. In model 2, scale inefficiency produce greater inefficiency as compared to the managerial efficiency. The result suggests that Malaysian REITs have been operating at the wrong scale of operations as majority of the Malaysian REITs are operating at decreasing return to scale.

Microfinance, Efficiency and Agricultural Production in Bangladesh

The objectives of this study were to make a detailed and systematic empirical analysis of microfinance borrowers and non-borrowers in Bangladesh and also examine how efficiency measures are influenced by the access to agricultural microfinance. In the empirical analysis, this study used both parametric and non-parametric frontier approaches to investigate differences in efficiency estimates between microfinance borrowers and non-borrowers. This thesis, based on five articles, applied data obtained from a survey of 360 farm households from north-central and north-western regions in Bangladesh. The methods used in this investigation involve stochastic frontier (SFA) and data envelopment analysis (DEA) in addition to sample selectivity and limited dependent variable models. In article I, technical efficiency (TE) estimation and identification of its determinants were performed by applying an extended Cobb-Douglas stochastic frontier production function. The results show that farm households had a mean TE of 83% with lower TE scores for the non-borrowers of agricultural microfinance. Addressing institutional policies regarding the consolidation of individual plots into farm units, ensuring access to microfinance, extension education for the farmers with longer farming experience are suggested to improve the TE of the farmers. In article II, the objective was to assess the effects of access to microfinance on household production and cost efficiency (CE) and to determine the efficiency differences between the microfinance participating and non-participating farms. In addition, a non-discretionary DEA model was applied to capture directly the influence of microfinance on farm households production and CE. The results suggested that under both pooled DEA models and non-discretionary DEA models, farmers with access to microfinance were significantly more efficient than their non-borrowing counterparts. Results also revealed that land fragmentation, family size, household wealth, on farm-training and off farm income share are the main determinants of inefficiency after effectively correcting for sample selection bias. In article III, the TE of traditional variety (TV) and high-yielding-variety (HYV) rice producers were estimated in addition to investigating the determinants of adoption rate of HYV rice. Furthermore, the role of TE as a potential determinant to explain the differences of adoption rate of HYV rice among the farmers was assessed. The results indicated that in spite of its much higher yield potential, HYV rice production was associated with lower TE and had a greater variability in yield. It was also found that TE had a significant positive influence on the adoption rates of HYV rice. In article IV, we estimated profit efficiency (PE) and profit-loss between microfinance borrowers and non-borrowers by a sample selection framework, which provided a general framework for testing and taking into account the sample selection in the stochastic (profit) frontier function analysis. After effectively correcting for selectivity bias, the mean PE of the microfinance borrowers and non-borrowers were estimated at 68% and 52% respectively. This suggested that a considerable share of profits were lost due to profit inefficiencies in rice production. The results also demonstrated that access to microfinance contributes significantly to increasing PE and reducing profit-loss per hectare land. In article V, the effects of credit constraints on TE, allocative efficiency (AE) and CE were assessed while adequately controlling for sample selection bias. The confidence intervals were determined by the bootstrap method for both samples. The results indicated that differences in average efficiency scores of credit constrained and unconstrained farms were not statistically significant although the average efficiencies tended to be higher in the group of unconstrained farms. After effectively correcting for selectivity bias, household experience, number of dependents, off-farm income, farm size, access to on farm training and yearly savings were found to be the main determinants of inefficiencies. In general, the results of the study revealed the existence substantial technical, allocative, economic inefficiencies and also considerable profit inefficiencies. The results of the study suggested the need to streamline agricultural microfinance by the microfinance institutions (MFIs), donor agencies and government at all tiers. Moreover, formulating policies that ensure greater access to agricultural microfinance to the smallholder farmers on a sustainable basis in the study areas to enhance productivity and efficiency has been recommended. Key Words: Technical, allocative, economic efficiency, DEA, Non-discretionary DEA, selection bias, bootstrapping, microfinance, Bangladesh.

Search engine advertising in web retailing : an efficiency analysis

This study examines the efficiency of search engine advertising strategies employed by firms. The research setting is the online retailing industry, which is characterized by extensive use of Web technologies and high competition for market share and profitability. For Internet retailers, search engines are increasingly serving as an information gateway for many decision-making tasks. In particular, Search engine advertising (SEA) has opened a new marketing channel for retailers to attract new customers and improve their performance. In addition to natural (organic) search marketing strategies, search engine advertisers compete for top advertisement slots provided by search brokers such as Google and Yahoo! through keyword auctions. The rationale being that greater visibility on a search engine during a keyword search will capture customers' interest in a business and its product or service offerings. Search engines account for most online activities today. Compared with the slow growth of traditional marketing channels, online search volumes continue to grow at a steady rate. According to the Search Engine Marketing Professional Organization, spending on search engine marketing by North American firms in 2008 was estimated at $13.5 billion. Despite the significant role SEA plays in Web retailing, scholarly research on the topic is limited. Prior studies in SEA have focused on search engine auction mechanism design. In contrast, research on the business value of SEA has been limited by the lack of empirical data on search advertising practices. Recent advances in search and retail technologies have created datarich environments that enable new research opportunities at the interface of marketing and information technology. This research uses extensive data from Web retailing and Google-based search advertising and evaluates Web retailers' use of resources, search advertising techniques, and other relevant factors that contribute to business performance across different metrics. The methods used include Data Envelopment Analysis (DEA), data mining, and multivariate statistics. This research contributes to empirical research by analyzing several Web retail firms in different industry sectors and product categories. One of the key findings is that the dynamics of sponsored search advertising vary between multi-channel and Web-only retailers. While the key performance metrics for multi-channel retailers include measures such as online sales, conversion rate (CR), c1ick-through-rate (CTR), and impressions, the key performance metrics for Web-only retailers focus on organic and sponsored ad ranks. These results provide a useful contribution to our organizational level understanding of search engine advertising strategies, both for multi-channel and Web-only retailers. These results also contribute to current knowledge in technology-driven marketing strategies and provide managers with a better understanding of sponsored search advertising and its impact on various performance metrics in Web retailing.

Technical and scale efficiency of cassava production system in Delta State, Nigeria: an application of Two-Stage DEA approach

The present study examines the level of pure technical and scale efficiencies of cassava production system including its sub-processes (that is production and processing stages) of 278 cassava farmers/processors from three regions of Delta State, Nigeria by applying Two-Stage Data Envelopment Analysis (DEA) approach. Results reveal that pure technical efficiency (PTE) is significantly lower at the production stage 0.41 vs 0.55 for the processing stage, but scale efficiency (SE) is high at both stages (0.84 and 0.87), implying that productivity can be improved substantially by reallocation of resources and adjusting operation size. The socio-economic determinants exert differential impacts on PTE and SE at each stage. Overall, education, experience and main occupation as farmer significantly improve SE while subsistence pressure reduces it. Extension contact significantly improves SE at the processing stage but reduces PTE and SE overall. Inverse size-PTE and size-SE relationships exist in cassava production system. In other words, large/medium farms are technically and scale inefficient. Gender gap exists in performance. Male farmers are technically efficient at processing stage but scale inefficient overall. Farmers in northern region are technically efficient. Investments in education, extension services and infrastructure are suggested as policy options to improve the cassava sector in Nigeria.

Efficiency measurement of Australian dairy farms: national and regional performance

In this paper we use Data Envelopment Analysis (DEA) to estimate technical efficiency for a sample of 1742 Australian dairy farms. Bearing in mind data limitations we find that average technical efficiency is 59 per cent, but there are significant regional differences. These results reflect differences in State level milk marketing arrangements in place before dairy deregulation in July 2000 providing an ex post explanation for the changing composition of dairy farms in Australia. We also examine two important technical aspects of DEA implementation. First, how changes in model input specification alter the relative performance of farms. Second, we employ a simple bootstrap procedure to show how changes in sample size affects estimates of technical efficiency. These results have simple but important implications for the use of DEA as an industry-benchmarking tool.

Technical and scale efficiency of Islamic banking operations in Malaysia: an empirical investigation with a longitudinal perspective

Against the background of increasing competition from globalization and the trend towards consolidation, diversification and rationalization, the study of efficiency is most relevant in the Malaysian Islamic banking context, where all domestic commercial banks operate Islamic banking schemes. Using the non-parametric method of Data Envelopment Analysis (DEA), this study investigates the recent efficiency of the Malaysian Islamic Banking system. The attributions of technical efficiency (utilization of capacity) and scale efficiency (optimality of scale achieved) are identified. Further, Islamic Banking Schemes operating under the dual banking system of foreign and domestic commercial banks were benchmarked to the country's two full-fledged Islamic banks to provide insight of the relative efficiencies. Amidst an overall improvement in TE and SE, it was noted that foreign banks (FB) increased efficiency levels to achieve full efficiency over the six-year period, and domestic banks (DB) followed by smaller improvement while the fully-fledged Islamic banks (FFIE) experienced a general decline in efficiency which was solely attributed to scale inefficiency. The findings provide useful guidelines for policy implications and may also assist banks concerned with their strategic planning with regard to the future of Islamic banking.

Envelopment methodology to measure and compare subcontractor productivity at the firm level

This paper describes a conceptual approach to measure and compare productivity of resource utilization at the firm level, adapting a set of techniques known as Data Envelopment Analysis (DEA). Within this approach, the paper addresses the issues of multiple inputs and multiple outputs of a construction firm, level of detail for data collection, and the required transformations to correct for differences among projects. In particular, we focus on the resource management of subcontractors. Subcontractors manage multiple, concurrent projects and must allocate limited resources across these projects. Interaction between projects and resource allocation creates non-linear effects, and therefore the productivity of the firm is not simply the productivity of its projects. The proposed measurement methodology will allow assessment of the impact of different management policies (including many of those proposed by lean construction researchers) on firm performance. It is hoped that this novel approach to productivity measurement will help subcontractors identify efficient practices and superior management policies, and will promote adoption of these policies.

Research of the construction industry efficiency in China-based on DEA panel data approach

The efficiency of the construction industry is analyzed based on provinces panel data in China in this paper. The Mean Number of Employee and the Mean Completed Investment are used as inputs. The Mean Actual Sales of Commercial Houses and the Mean Net Profit are used as outputs. Data Envelopment Analysis (DEA) model is used to measure the efficiency of the construction industry. Shanghai and Zhejiang are found technically efficient. Shandong is scale efficient but technology efficiency is lower. There are two provinces are decreasing returns to scale and other provinces are increasing returns to scale. On the whole, the technology efficiency of the construction industry of China is lower. Based on the conclusions, the paper proposes some suggestions to improve the efficiency of the construction industry in China.

Impact of policy changes on the efficiency and returns-to-scale of Japanese financial institutions: an evaluation

This paper examines the impact of FSA's (Financial Services Agency) recent policy changes on the efficiency and returns-to-scale (RTS) of Japanese financial institutions including banks, securities companies and bank holding companies. Three kinds of efficiency are investigated namely, technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) using the non-parametric methodology named data envelopment analysis (DEA). The DEA analysis shows a substantial improvement in the overall efficiency of Japanese banks, albeit a significant difference of efficiency scores between the major/city banks and the regional banks. Results are robust to alternative specifications of efficiency and scale changes.

Efficiency in Brazil's industrial sectors in terms of energy and sustainable development

This article evaluates the efficiency of Brazil's industrial sectors from 1996 to 2009, taking into account energy consumption and respective contributions to the country's economic and social aspects. This analysis used a mathematical programming method called Data Envelopment Analysis (DEA), which enabled, from the SBM model and the window analysis, to evaluate the ability of industries to reduce energy consumption and fossil-fuel CO2 emissions (inputs), as well as to increase the Gross Domestic Product (GDP) by sectors, the persons employed and personnel expenses (outputs). The results of this study indicated that the Textile sector is the most efficient industrial sector in Brazil, according to the variables used, followed by these sectors: Foods and Beverages, Chemical, Mining, Paper and Pulp, Nonmetallic and Metallurgical.

Technical Efficiency and Stock Market Reaction to Horizontal Mergers

This study examines the relationship between stock market reaction to horizontal merger announcements and technical efficiency levels of the participating firms. The analysis is based on data pertaining to eighty mergers between firms in the U.S. manufacturing industry during the 1990s. We employ Data Envelopment Analysis (DEA) to measure technical efficiency, which capture the firms. competence to produce the maximum output given certain productive resources. Abnormal returns related to the merger announcements provide the investor.s re-evaluation on the future performance of the participating firms. In order to avoid the problem of nonnormality, heteroskedasticity in the regression analysis, bootstrap method is employed for estimations and inferences. We found that there is a significant relationship between technical efficiency and market response. The market apparently welcomes the merger as an arrangement to improve resource utilizations.