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The zirconium-in-rutile thermometer enjoys widespread use, but confidence in its accuracy is limited because experiments were conducted at higher temperatures than many rutile-bearing rocks and calibration uncertainties have not been quantitatively assessed. Refined calibrations were developed using bootstrap regression to minimize residuals in the natural logarithm of the equilibrium constant, based on experiments only (n = 32) and on a combined compilation of experiments and natural data (n = 94, total). Rearranging the regression to solve for T, and expressing Zr concentration (C) in parts per million (µg/g), the calibrations in the α-quartz stability field are: Experimental data set: T (° C) = 68740 + 0.441·P (bars) - 0.114·C (ppm) / 129.76 - R·ln [C(ppm)] - 273.15. Combined data set: T (° C) = 71360 + 0.378 ·P(bars) - 0.130·C(ppm) / 130.66 - R·ln [C(ppm)] - 273.1. Thermodynamics of the quartz-coesite transition as applied to the calibration for α-quartz yields calibrations for the coesite stability field: Experimental data set T (° C) = 71290 + 0.310·P(bars) - 0.114·C (ppm) / 128.76 - R·ln [C(ppm)] - 273.15. Combined data set: T (° C) = 73910 + 0.247·P(bars) - 0.130 ·C(ppm) / 129.65 - R·ln [C(ppm)] - 273.15. Propagated temperature uncertainties are ±20-30 °C (2σ) for the experimental data set calibration, and ±10-15 °C (2σ) for the combined data set. Compared to previous experimental calibrations, the refined thermometer predicts temperatures up to 40 °C lower for T ≤ 550 °C, and systematically higher temperatures for T > 800 °C. With careful attention to distributions of Zr in rutile grains, precisions of ±5 °C and accuracies ∼±15 °C may be possible, although a poor understanding of how to select compositions for thermometry will typically lead to larger uncertainties. The ZiR calibration promises continued high-precision and accurate thermometry, and possibly improved thermodynamic properties, but the sources of compositional variability in rutile warrant further scrutiny.

This paper estimates technical efficiency in the Spanish construction sector before and after the start of the current financial crisis; and examines the impact of socio-economic factors on technical efficiency. Bias-corrected efficiency measures are obtained using Data Envelopment Analysis with bootstrap for a sample of medium-sized and large construction firms over the period 2000–2010. Next; bias-corrected efficiency scores are regressed on the variables explaining efficiency using bootstrap truncated regression. The results show that technical efficiency is very low and is significantly lower after the beginning of the financial crisis than before. Firms with the highest technical efficiency scores have the lowest input-ratio for material and employee costs to output and the highest for fixed assets. The examination of the determinants of technical efficiency indicates that efficiency is higher for firms that export; are highly leveraged; are integrated in the form of joint stock company; and are located in Spanish regions with higher GDP per capita; while firms with high stock relatively to turnover have lower technical efficiency. Technical efficiency increases with size for relatively small sized construction firms; but decreases beyond a critical firm size; while technical efficiency decreases with age for young firms; but eventually increases for older firms.,

Management and utilization of factors of production, in addition to diversification of land use, affect the performance of farms. In this article, it is identified whether the diversification of land use through its disposal to tourism infrastructure has a positive impact on the farms’ income. This identification was conducted by processing technical and economic data and applying bootstrap regression analysis. The research was conducted using a sample of 56 farms active in hospitality alongside agriculture, utilizing possibly uncultivated areas of land. Data collection was carried out by personal visits to the examined farms. The results showed that the performance of the farms is enhanced by tourism activity. At the same time, the results showed that land used for tourism activities has a positive impact on farms’ income. Paid labor also appears to have a positive influence. Although this investigation was executed in the Region of Central Macedonia (Greece), it contributes to strengthening the existing literature on rural tourism and land use. At the same time, it gives alternatives to policy-makers and owner-managers of farms regarding the utilization of the available factors of production with an emphasis on the land one.

Sugarcane farmers in sugar-producing countries are experiencing an economic crisis due to the Covid 19 pandemic. Restrictions on transportation and a scarcity of labor have delayed sugarcane harvesting, increased production costs, decreased productivity, and decreased income. Therefore, our research aims to measure the technical efficiency and the influence of environmental factors on the technical efficiency of sugar cane farming in Malang Regency. The results of the research using the multiple bootstrap regression approach show that the efficiency values based on the VRS and CRS assumptions are 0.854 and 0.834. This value means that sugarcane farmers in Malang Regency must reduce the use of inputs by 16.6% and 14.6% respectively to make sugarcane farming more efficient. The variable age of the head of household reduces technical efficiency, while the variables of sugarcane training experience, organizational experience, ratoon cane, and increases in input prices have the potential to increase technical efficiency. The Covid 19 pandemic has become a momentum for policy makers to create training programs that aim to utilize natural resources to overcome scarcity and rising input prices, as well as realize agricultural sustainability.

PurposeThis paper aims to examine the total factor productivity (TFP) change and its components: efficiency change and technical change in microfinance institutions (MFIs) in India operating from 2005 to 2018. The study also scrutinizes the variations in productivity levels across the distinct organizational form and size groups of MFIs. In addition to this, the authors identify the contextual factors that determine TFP growth, catching-up and technology innovation in MFIs.Design/methodology/approachThe study employs a smooth homogeneous bootstrap estimation procedure of Simar and Wilson (1999) for obtaining reliable estimates of Malmquist indices –productivity and its components – in a data envelopment analysis (DEA) framework for individual MFIs. In order to identify the determinants of productivity change and its components, the study follows Simar and Wilson's (2007) guidelines and applies a bootstrap truncated regression model. The double bootstrap procedure performs well, both in terms of allowing correct estimation of bias and deriving statistically consistent productivity estimates in the first and root mean square errors in the second stage of the analysis.FindingsThe empirical results reveal that the MFIs have shown average productivity growth of 6.70% during the entire study period. The observed productivity gains are primarily contributed by a larger efficiency increase at the rate of 4.80%, while technical progress occurs at 2.3%. Nonbanking financial companies (NBFC)-MFIs outperformed non-NBFC-MFIs. Small MFIs show the highest TFP growth in terms of size groups, followed by the large MFIs and medium MFIs. The bootstrap truncated regression results suggest that the credit portfolio, size and age of MFIs matter in achieving higher productivity levels.Practical implicationsThe practical implication drawn from the study is that the Indian MFI industry might adopt the latest technology and innovations in the products, risk assessment and credit delivery to improve their productivity levels. The industry must focus on enhancing the managerial skill of its employees to achieve a high productivity level.Originality/valueThis study is perhaps the initial attempt to explain the productivity behavior of MFIs in India by deploying a statistically robust double bootstrap procedure in the DEA-based Malmquist Productivity Index (MPI) framework. The authors estimate the bias-adjusted productivity index and its decompositions, which represent more reliable and statistically consistent estimates. For contextual factors responsible for driving productivity change, the study deploys a bootstrap truncated regression approach.

PurposeThe purpose of this paper is to investigate the input- and output-specific technical inefficiency of Vietnamese prawn-rice rotational crops (PRRC) and to identify the impacts of the socio-economic characteristics of farmers and farms on these technical inefficiencies.Design/methodology/approachThis study first used a Russell-type (input-output) directional distance function to estimate the input- and output-specific technical inefficiency. Second, it applied a bootstrap truncated regression to analyze the factors influencing these technical inefficiencies. Data were gathered through a survey among 94 farmers, from Ben Tre and Kien Giang provinces, the two popular PRRC areas in the Mekong Delta.FindingsResults show that Vietnamese PRRC farmers could reduce the water surface area by 3%, the use of seedlings by 15%, labor by 16%, fertilizers by 26%, and the use of others by 24%, while simultaneously increasing the revenue of farming system by 57% relative to the variable returns to scale (VRS) frontier. Farmers with more years of experience are generally better in managing the use of seedlings and in improvement of revenue. Farmers in Kien Giang province are more efficient in achieving revenue of the PRRC farming system than farmers in Ben Tre province.Research limitations/implicationsOutcomes of this study are useful to identify strategies in minimizing the use of inputs while simultaneously maximizing PRRC production.Originality/valueThis paper relates to the comparison of two mostly different ecological zones, being the dominant production areas of PRRC, in which, Kien Giang represents the western part, while Ben Tre is in the eastern part of the Vietnam’s Mekong Delta. The findings not only expand the current understanding but also suggest various meaningful research questions regarding the development of Vietnamese PRRC under the impacts of climate change. The study also contributes to the literature on examining the input- and output-specific technical inefficiencies and influencing factors.

Purpose The purpose of this paper is to provide a new empirical evidence on the impact of economic globalization on the efficiency of the banking sector. The paper also investigates to what extent the internal (i.e. bank specific characteristics) and external (i.e. macroeconomic conditions) factors influence the efficiency of banks while controlling for the impact of the different dimensions of globalization. Design/methodology/approach The analysis is confined into two stages. In the first stage, the authors employ the bias-corrected data envelopment analysis method to compute the efficiency of individual banks during the period 1999-2012. The authors then use bootstrap regressions to examine the impact of economic globalization on bank efficiency, while controlling for the potential impacts of contextual variables. Findings The empirical findings indicate that the impacts of personal contacts, information flows, and cultural proximity seem to work in favor of Malaysian banks’ efficiency. A plausible reason could be due to the fact that capital account liberalization is usually accompanied by liberalization of the financial services sector, resulting in a greater competition and subsequently eroding monopolistic profits. The empirical findings also bring forth the importance of and political globalization in determining the efficiency of banks operating in the Malaysian banking sector. Originality/value The present study aims to provide for the first time empirical evidence on the performance of the banking sector and to establish new empirical evidence on the impact of globalization. The empirical evidence on the impact of globalization on the banking sector is completely missing from the literature.

This study presents a novel application of two-stage bootstrap data envelopment analysis (DEA) to assess the efficiency of radiology units in public hospitals. In the first stage of our analysis, we carry out a bootstrap DEA analysis, testing the hypotheses of variable returns to scale to identify efficient units. In the second stage, we examine the effects of four explanatory variables (chief radiology technologist’s years of service, presence of customer satisfaction survey systems, age of the equipment, and output variety) other than inputs and outputs on the technical efficiency of radiology units using a bootstrap truncated regression. Counterintuitively, the results show that on average, the use of newer equipment leads to a decrease in productivity and that a chief radiology technologist with greater seniority and the presence of customer satisfaction survey systems do not translate into better productivity. Instead, productivity is positively influenced by the variety of a unit’s output.

PurposeThe study attempts to examine the bias-adjusted financial and operational efficiency estimates of microfinance institutions (MFIs) operating in the Eastern Europe and Central Asia (ECA) region during the financial year 2017–2018. In addition, the study also identifies the responsible factors determining the financial and operational performances of MFIs operating in the ECA region.Design/methodology/approachThe study employs two-stage bootstrap data envelopment analysis (DEA). In the first stage, the authors incorporate the bootstrap procedure in the DEA framework as suggested by Simar and Wilson (2000) to estimate the bias-corrected efficiency scores of 67 sample MFIs. In order to identify the drivers of efficiency level, the study deploys the bootstrap truncated regression model following the Simar and Wilson (2007) guidelines in the second stage of analysis.FindingsThe authors note from the empirical results that MFIs operating in the ECA region are relatively more financially efficient (0.588) than socially efficient (0.496). However, none of the MFIs were found to be operating at best-practice frontier while considering the bias-adjusted efficiency estimates. Further, the results of second stage of analysis confirm that corporate governance, that is, board size has positive and statistically significant impact on MFIs’ performances. In addition, the bad credit quality deteriorates both financial revenue and operational efficiency. Moreover, the MFIs’ size, profit status and debt-to-equity ratio were also found to be statistically significant to determine the operational and financial efficiency of MFIs in the ECA region.Practical implicationsThe study provides the robust efficiency estimates and factors responsible to determine the financial and operational efficiency of MFIs operating in the ECA region. Further, the empirical results of the study provide the inputs and further direction to the policymakers, regulators, practitioners and managers in framing the policy and optimal operating strategies for ECA MFIs industry.Originality/valueThe study extends the DEA analysis by incorporating the bootstrap procedure in DEA model to estimate the bias-adjusted efficiency scores which are more reliable and robust. In addition, bootstrap truncated regression has been applied to identify the drivers of efficiency. Moreover, in the literature there is no single study which has deployed the double bootstrap DEA framework to examine the financial and operational efficiency estimates and its drivers.

This paper discusses and explores the different effects of contractual forms on the satisfaction with public transport (PT) at different urban scales. Using public transport systems in 12cities in China as the focus (four large-I-sized cities, four large-II-sized cities, and four medium-sized cities), a measurement model of the passenger satisfaction index (PSI) is constructed and estimated on the basic of the adjusted European Customer Satisfaction Index (ECSI) and Partial least square-structural equation model (PLS-SEM), respectively. Then, a two-stage truncation regression bootstrap model is proposed to assess the different effects between them. The major findings of this study are summarized as follows: (1) different effects of contractual forms on PT satisfaction in large- and medium-sized cities are confirmed. (2) In large-I-sized cities and lager II sized cities, operators supervised by management contracts incite higher PT satisfaction levels than those supervised by gross and net cost contracts. (3) In medium-sized cities, operators supervised by gross cost contracts provide incentives to be the satisfaction compared to those of management and net cost contracts. According to different urban scales, different and appropriate contractual forms and supervision mechanisms should be chosen to regulate public transport services.