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The purpose of this paper is to present a refined framework providing clarity in terms of the components of profitability and productivity change from the perspective of the firm level.

The literature is analysed with a scoping study and a systematic literature review. Productivity measurement approaches are compared using data at the product level.

The definition of total factor productivity (TFP) in the literature negatively affects the accuracy of profitability and productivity measurement. In the usual case of a dynamic output mix, TFP change encompasses biasing output mix effects relating to profitability, but not to productivity change. Therefore, this paper defines changes of a ratio of output quantities to input quantities not as TFP change, but as quantitative profitability (QP) change. A framework is proposed decomposing profitability change into price recovery and QP change, whereas the latter comprises of valid productivity change (encompassing technological, technical efficiency and productivity-related scale effects) and output mix change (encompassing proportion, quality, output switching and profitability-related scale effects).

Future research should include literature from the industrial organisation field of economics. The presented framework should be transferred to the standard production function framework used in economics.

The paper can help preventing faulty decision making or distrust due to the use of biased profitability or productivity indicators. TFP-based productivity indicators are unsuitable for most firms. To measure productivity meaningfully, firms should use adequate approaches (e.g. standard input- or adjusted total factor productivity-based ones).

The paper contributes to a more accurate performance measurement approach, as researchers and practitioners better understand the components of profitability and productivity change.

The purpose of this paper is to analyse the performance of the Indian non-life (general) insurance sector in terms of total factor productivity (TFP) over the period 2005–2016.

This study utilises Färe‒Primont index (FPI) to access the change in TFP and its components: technical change, technical efficiency and mix and scale efficiency over the observation period. Moreover, it employs the Mann–Whitney U-test to scrutinise the difference between the public and the private insurers in terms of growth in productivity.

The results reveal that the insurance sector possesses a very low level of TFP. Also, the results divulge an improvement of 11.98 per cent in TFP of the insurance sector at an annual average rate of 12.41 per cent over the observation period. The growth in productivity is mainly attributable to the improvement of 10.81 per cent in the scale‒mix efficiency. The progress in scale‒mix efficiency is mainly the result of improvements in residual scale and residual mix efficiency. The results also show that the privately owned insurers have experienced a high productivity growth rate than the state-owned insurers.

The results hold practical implications for the regulators, policymakers and decision makers of the Indian non-life insurance companies.

This study is the first of its kind to use FPI, which satisfies all economically relevant axioms and tests defined by the index number theory to comprehensively access the change in TFP of the Indian non-life insurance sector.

The purpose of this paper is to identify the effects of recent demographic transition and rising labor costs on agricultural production structure and pattern in China during 1998-2012.

The authors, first, theoretically discuss the effects of changing relative input prices due to rising labor cost on producers’ decisions regarding input mix (substitution effect), output level, and product quality (output effect). A logarithmic mean Divisia index decomposition method is then applied to empirically identify these effects at aggregated levels, followed by an analysis based on the visualization of land use indicators on changing cropping patterns across Chinese provinces.

The authors find that tightened effective agricultural labor supply and rises in rural labor costs are associated with divergent changes in input mixes and output choices across products. Producers of land-intensive products focusing more on input mix adjustment, while those of labor-intensive products seem to more likely to adjust output choices. Producers’ adaption strategies also varied across Chinese provinces due to natural conditions, leading to shifts and concentrations in the regional distribution of agricultural products, with lower-value bulk products concentrating in the plain areas, whereas higher-value horticulture products increasingly prevailing in sloped areas.

This paper illustrates how adjustments in input mixes and output choice in Chinese agriculture counteracted disadvantages caused by rising labor costs and how such adjustments are product and region specific. Based on these observations, implications regarding further innovations in production technology and institutional arrangements needed within China’s agricultural sector are highlighted in the paper.

Total factor productivity (TFP) change is an important driver of long-run economic growth in the construction sector. However, examining TFP alone is insufficient to identify the cause of TFP changes. Therefore, this paper employs the infrequently used Geometric Young Index (GYI) and stochastic frontier analysis (SFA) to measure and decompose the TFP Index (TFPI) at the firm-level from 2009 to 2018 based on Malaysian construction firms' data.

To improve the TFPI estimation, normally unobserved environmental variables were included in the GYI-TFPI model. These are the physical operation of the firm (inland versus marine operation) and regional locality (West Malaysia versus East Malaysia). Consequently, the complete components of TFPI (i.e. technological, environmental, managerial, and statistical noise) can be accurately decomposed.

The results reveal that TFP change is affected by technological stagnation and improvements in technical efficiency but a decline in scale-mix efficiency. Moreover, the effect of environmental efficiency on TFP is most profound. In this case, being a marine construction firm and operating in East Malaysia can reduce TFPI by up to 38%. The result, therefore, indicates the need for progressive policies to improve long-term productivity.

Monitoring and evaluating productivity change allows an informed decision to be made by managers/policy makers to improve firms' competitiveness. Incentives and policies to improve innovation, competition, training, removing unnecessary taxes and regulation on outputs (inputs) could enhance the technological, technical and scale-mix of resources. Furthermore, improving public infrastructure, particularly in East Malaysia could improve regionality locality in relation to the environmental index.

This study contributes to knowledge by demonstrating how TFP components can be completely modelled using an aggregator index with good axiomatic properties and SFA. In addition, this paper is the first to apply and include the GYI and environmental variables in modelling construction productivity, which is of crucial importance in formulating appropriate policies.

China and India have made significant strides in transforming their agricultural sectors to cut hunger and poverty for the masses through improved agricultural productivity. Given limited land and shift of labor to non-agricultural sector, increasing productivity will continue to be central in agricultural growth in the twenty-first century. The purpose of this paper is to provide comparative analysis of the agricultural total factor productivity (TFP) growth in the two countries. It complements existing literature by examining the evolution and drivers of TFP at disaggregated sub-national level. Richer data allows a deeper understanding of the nature and drivers of TFP growth in the two countries.

This paper applies different analytical framework to address different research questions using data since 1980. China study estimates a parametric output-based distance function using a translog stochastic frontier function. Productivity growth index and its multiple components are calculated using parameters derived from the parametric approach to identify the characteristics of technology such as structural bias. India study first applies data envelopment analysis to estimate the aggregate productivity growth index, technical change (TC), and efficiency change. Next productivity indexes by for traditional crops are estimated using growth accounting framework at state level. Finally, a panel regression links TFP on its determinants.

Several common themes emerge from this comparative study. Faced with similar challenges of limited resources and growing demand, improving productivity is the only way to meet long-term food security. Agriculture sector has performed impressively with annual TFP growth beyond 2 percent in China and between 1 and 2 percent in India since the 1980s. The TFP growth is mainly propelled by technological advance but efficiency had been stagnant or even deteriorated. This study provides a granular picture of within country heterogeneity: fast growth in the North and Northeast part of China, South and East of India.

The study suggests some possible policy interventions to improve agricultural productivity, including investment in agricultural R & D to create advanced production technology, effective extension programs and supportive policies to increase efficiency, and diversification from staple crops for sector-wide growth. The India study suggests certain policies may not be contributing much to productivity growth in the long run due to a negative impact on environment. Further studies are needed to expand the productivity analysis to take into consideration of the negative externalities to the society. Data enhancement to account for quality-adjusted inputs could improve the estimation of productivity growth.

Each country study reveals certain prospects of the agricultural sector and production technology. China analysis statistically confirms the existence of technical inefficiency and technology progress, suggests the translog form is appropriate to capture the production technology and satisfies conditions stipulated in theoretical models. The results indicate TC does not influence the contribution of output or input to the production process. India study pinpoints the lagging productivity growth of traditional crops, which still derives growth from input expansion. Although different states benefited from different crops, sector-wide productivity gain is primarily the result of diversification to high-value crops and livestock products.

Universities face incredibly difficult, complex decisions concerning the degree to which they participate in the process of commercializing research. The U.S. government has made an explicit policy decision to allow funded entities to obtain patents and thereby has encouraged participation in the commercialization of federally funded research. The Bayh-Dole Act enables universities to participate in the commercialization process, but it does not obligate or constrain them to pursue any particular strategy with respect to federally funded research. Universities remain in the driver's seat and must decide carefully the extent to which they wish to participate in the commercialization process.The conventional view of the role of patents in the university research context is that patent-enabled exclusivity improves the supply-side functioning of markets for university research results as well as those markets further downstream for derivative commercial end-products. Both the reward and commercialization theories of patent law take patent-enabled exclusivity as the relevant means for fixing a supply-side problem – essentially, the undersupply of private investment in the production of patentable subject matter or in the development and commercialization of patentable subject matter that would occur in the absence of patent-enabled exclusivity.While the supply-side view of the role of patents in the university research context is important, a view from the demand side is needed to fully appreciate the role of patents in the university research context and to fully inform university decisions about the extent to which they wish to participate in the commercialization process. Introducing patents into the university research system, along with a host of other initiatives aimed at tightening the relationship between universities and industry, is also (if not primarily) about increasing connectivity between university science and technology research systems and the demands of industry for both university research outputs (research results and human capital) and upstream infrastructural capital necessary to produce such outputs.In this chapter, I explore how university science and technology research systems perform economically as infrastructural capital and explain how these systems generate social value. I explain how the availability of patents, coupled with decreased government funding, may lead to a slow and subtle shift in the allocation of infrastructure resources.

The purpose of this paper is to attempt to measure the performance of the Indian banking sector in terms of efficiency and productivity levels and their determinants during the post-reform period.

The present study is a novel attempt as it has used pooled data for a duration of 15 years (i.e. 1997/1998-2010/2011) from 59 selected banks for estimating the Hicks-Moorsteen (HM) total factor productivity (TFP) index.

Poor technical efficiency has experienced with scale efficiency change exerting dominant factors; whereas relatively better productivity growth has been experienced by the banks with major contributions from technical change components. The study found relatively underestimated efficiency and productivity levels by traditional data envelopment analysis-based Malmquist index. Additionally, the study brings into account the results for external and environmental determining factors contributing to the TFP growth.

Using HMTFP indices has helped to eliminate certain drawbacks of data envelopment and provided the more elaborative decomposition of productivity growth along with their components so as to have lucid and multidimensional insights about the performance of the Indian banking industry after the initiation of financial reforms.

There are two main dimensions in which the performance of a production unit can be assessed. The first is the dimension of time. The basic question here is: how is this or that production unit doing over time? Assessing a unit's performance over time is called monitoring. The second dimension is characterized by the question: how is this or that production unit doing relative to other, similar units? To answer this question one needs to specify the reference set of units and one needs sufficient information on each of the members of this set. This activity is usually called benchmarking. A combination of the two dimensions in the setting of a panel is also possible.

This study investigates the nature of the substitutability relationships among capital, labor, and imported inputs in the context of a production function for Spain, with estimates obtained from an aggregate cost function. The results are consistent with the hypothesis that all of the inputs are substitutes for one another. The findings with respect to domestic inputs and imports are particularly important as the internationalization of the Spanish economy continues since, in the short run and ceteris paribus, further removal of import restrictions may have a negative impact on the demand for domestic factors. The estimates obtained here are also consistent with the hypotheses that: a decrease in the price of imports will have a proportionately larger impact on the price of domestically‐produced investment goods than on consumption goods; and second, that the elasticity of demand for each input with respect to consumption goods production is considerably higher than for investment goods production.

The purpose of this paper is to identify the efficiency scores of branches and districts, the sources of inefficiency for branches and projections of variables for inefficient branches. It measures the comparative performance of branches of a credit union for internal benchmarking.

The paper measures the performance of 35 branches of a credit union in the USA and suggests managerial insights. Data envelopment analysis is used for measuring the relative performance of the branches and districts of the credit union. The paper also compares performance differences among the districts using non-parametric statistical analyses.

Parts of the findings indicated that branches should focus on cost containment by reducing operating expenses and increasing their loan balances. In addition, districts were operated in different market conditions, which were evidenced by scale efficiency. The major contributions of the study are filling the void of benchmarking studies at a branch level in the credit union sector, suggesting a framework for internal benchmarking, and providing practical insights to managers of credit unions. The framework of this study can be applied to similar financial institutions with minor revisions.

The limitation of this study is found in the use of cross-sectional data, which is mainly due to the sensitivity of information disclosure of the credit union.

The paper includes implications for the development of benchmarking studies at a branch level in the credit union sector.

This paper fulfills an identified need to study how to identify source of inefficiencies so as to further improve the efficiency of branches.