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Data envelopment analysis (DEA) is based on the production possibility set that involves the process of converting resources or inputs to outputs. Accordingly, most DEA models include endogenous variables and need an additional step to find the influence of exogenous variables on the process. The purpose of this paper is to examine the relationship between the efficiency scores of DEA and the exogenous variables using truncated regression analysis with double bootstrapping along with two additional methods.

First, the authors employ DEA for benchmarking the comparative efficiency of the health care institutes. Next, the authors run and compare truncated, ordinary least square (OLS) and Tobit regression analysis using the double bootstrapping algorithm for finding the influence of exogenous variables on the efficiency of the health care institutes.

The authors confirmed the amount of bias for the Tobit and OLS regression models, which was caused by serially correlated errors. Accordingly, the authors chose results from the truncated regression model with double bootstrapping for examining the influence of exogenous or environment variables on the efficiency scores.

The study includes cross-sectional data on health care institutes in the state of Washington, USA. Collecting data in various states or regions over time is left for future studies.

In this study, three exogenous variables such as Medicaid revenues, locations of health care institutes and ownership types are significant for explaining the relationship between the efficiency scores and a group of the exogenous variables. Managers and policy makers need to pay attention to these variables along with endogenous variables for promoting the sustainability of the health care institutes.

The study demonstrates the usefulness of the truncated regression analysis with double bootstrapping for confirming the relationship between the efficiency scores of DEA and a group of exogenous variables, which is rare in the DEA literature.

A wetland is a place of tourist attraction, and tourism values play a key role in economic development. Among various services provided by a wetland, recreational services are increasingly valuable in the tourism sector. This paper aims to unfold the potential recreational values of the Dal Lake in Jammu and Kashmir, India.

The study uses individual travel cost methods (TCMs) and assesses its impact on regional development in terms of income and employment generation. A sample of 200 tourists is selected through an on-site survey on Dal Lake, and the demand for recreational visits and its value is estimated by employing the truncated Poisson regression model (TPRM) and un-truncated Poisson regression model (UTPRM). The consumers' surplus is estimated and tourists' benefit to visiting the wetland is explored.

On average, estimated consumers' surplus per visitor is Rs 6,250 (US$96.15) and Rs 25,000 (US$384.61) from respective models. The annual total recreational value of the lake is accounted for Rs 1713m (US$ 26m). This high consumer surplus (CS) and recreational values of the lake indicate large demand for its recreational facilities.

The study is based on primary data and thus, is original. The paper has implications for the policymakers to formulate sustainable management plans for the proper use of Dal Lake and tourism development.

The authors investigate cocoa farmers' willingness and motivation to participate in agritourism entrepreneurship in Ghana.

Primary data were obtained from 583 cocoa farmers. Contingent valuation method, ordered probit and truncated regressions were employed.

Cocoa farmers' willingness to participate in agritourism was high. The minimum fee farmers were willing to charge per tourist per day ranged from US$0.870 to US$6.957. Agritourism products farmers were willing to offer to tourists are interaction with rural folks, indigenous cuisine, quality locally stored drinking water, indigenous primary healthcare and on-site restrooms. Cocoa farmers' motivations to participate in agritourism are income generation, alternative livelihood strategy and education. Education, being a native, farm size, motorable roads to farm, and distance to farm influence minimum fee farmers were willing to accept to participate in agritourism.

Agritourism could be considered in rural and tourism development policies of developing countries.

The authors investigate cocoa farmers' participation in agritourism, motivations and determinants of willingness to participate.

The 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.

This 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.

Results 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.

Outcomes of this study are useful to identify strategies in minimizing the use of inputs while simultaneously maximizing PRRC production.

This 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.

Country of origin has profound effects on consumer behavior; yet few studies have examined an antecedent of these effects: why some countries enjoy a positive image while others suffer a negative one. Developing an institutional theory of country image, the authors argue that weak legal institutions at the country level increase firm opportunistic behavior that expropriates consumers and decrease the product quality of local brands, thus decreasing the country’s image regarding its products and brands.

This study measures country image for products and brands using the number of valuable brands (i.e. brands included in the top 500 brands from 2008 to 2016) in a particular home country. Data concerning the rule of law in each country come from the World Bank, and data on the efficiency of countries’ judicial systems comes from Djankov et al. (2007). We also collect patent data from the US Patent and Trade Office, national culture from Hofstede Insights and GDP and GDP per capita from the World Bank as control variables. Panel Poisson regression, Tobit regression and truncated regression are used in the analyses.

Supporting the institutional theory of country image, both the rule of law and efficiency of the judicial systems show positive and significant effects on country image, even when economy size (GDP), degree of economic development (GDP per capita), level of technology and skill (patents) and culture are controlled.

To improve their country’s image and the brand value of local firms, policymakers should strive to strengthen legal institutions aimed at punishing firm opportunistic behavior in their countries.

Previous research on the country-of-origin effect has not yet appreciated the role of legal institutions in developing the construct of country image.

After a brief glance at the global labour market after the financial meltdown the paper aims to explain some general mechanisms of short‐time work in Germany. Furthermore it seeks to present an overview of the costs of short‐time work for the establishments with respect to the latest labour market reforms in Germany. In the multivariate analyses with the IAB Establishment Panel the paper aims to identify the determinants of short‐time work and its intensity in Germany. Thus it's goal is to contribute to the discussion of the modified and amended legislative framework for short‐time work.

The microeconometric analysis is based on data from the IAB Establishment Panel, a representative survey of the labour demand in Germany. With data from the survey waves 2008‐2010 the probability of the use of short‐time work with probit regression models and its intensity with truncated regression models are explained.

The manufacturing industry as a German key industry was more affected than other sectors and suffered even harder. Despite the fact that the German labour administration has successfully reduced the bureaucracy of short‐time work, the programme is still rather adopted by bigger establishments. German establishments have utilized their flexibility reserves and complementary short‐time work to protect their core staff during the crisis. There is also some empirical evidence that the establishments tried to avoid brain drains. With the first signs of a recovery of the economy at the beginning of 2010 the establishments benefitted a lot from that strategy as they were instantly able to satisfy increasing demands in their markets again. Empirical evidence is also found that establishments made more intensive use of short‐time work the harder they were suffering from the crisis.

For the first time the latest data from the survey wave 2010 of the IAB Establishment Panel is used and compared with the 2009 survey wave. The structure of the panel questionnaire allows the implementation of some specific questions concerning the use of short‐time work. The IAB Establishment Panel has a sample size of approximately 16,000 cases.

The purpose of this paper is to evaluate the efficiency of Algerian banks and examine the effects of explanatory factors on their performance.

In this paper, a methodology of two-stage network data envelopment analysis (DEA) is used to explore the efficiency of a sample of 13 Algerian banks during the 2013–2017 period. In the first stage, the network DEA is used to assess the overall and stages efficiencies. In the second stage, the partial least squares (PLS) regression is conducted to determine the potential effects of explanatory factors on stages efficiency.

The main empirical results indicate that Algerian banks need an efficiency improvement in both stages. The overall efficiency of the Algerian banking system improves over the study period. The deposit producing efficiency is positively affected by bank size and bank age. The revenue earning efficiency is negatively associated with bank size and bank age. The domestic banks are more efficient than foreign banks in the deposit producing stage and the foreign banks are more efficient than domestic banks in the revenue earning stage.

The results might be used as guidelines for both managers and policymakers in order to improve banks and banking system performance.

To the best of our knowledge, this study is the first that uses the DEA in investigating the efficiency of Algerian banks by dividing the overall efficiency into deposit producing and revenue earning efficiencies. Unlike most studies that have usually used OLS regression, Tobit regression and bootstrapped truncated regression, this study is the first in the bank efficiency literature that uses PLS regression to investigate the potential effect of explanatory variables on deposit producing and revenue earning efficiencies.

The purpose of this paper is to explore two distinct subsets of dynamic capabilities that need to be deployed when pursuing innovation through inter-organizational activities, respectively, in the contexts of broad networks and specific alliances. The authors draw distinctions and explore potential interdependencies between these two dynamic capability reservoirs, by integrating concepts from the theoretical perspectives they are derived from, but which have until now largely ignored each other – the social network perspective and the dynamic capabilities view.

The authors investigate nanotechnology-driven R&D activities in the 1995–2005 period for 76 publicly traded firms in the electronics and electrical equipment industry and in the chemicals and pharmaceuticals industry, that applied for 580 nanotechnology-related patents and engaged in 2,459 alliances during the observation period. The authors used zero-truncated Poisson regression as the estimation method.

The findings support conceptualizing dynamic capabilities as four distinct subsets, deployed for sensing or seizing purposes, and across the two different inter-organizational contexts. The findings also suggest potential synergies between these subsets of dynamic capabilities, with two subsets being more macro-oriented (i.e. sensing and seizing opportunities within networks) and the two other ones more micro-oriented (i.e. sensing and seizing opportunities within specific alliances).

The authors show that firms differ in their subsets of dynamic capabilities for pursuing different types of inter-organizational, boundary-spanning relationships (such as alliances vs broader network relationships), which ultimately affects their innovation performance.

The authors contribute to the growing body of work on dynamic capabilities and firm-specific advantages by unbundling the dynamic capability subsets, and investigating their complex interdependencies for managing different types of inter-organizational linkages. The main new insight is that the “linear model” of generating more innovations through higher inter-firm collaboration in an emerging field paints an erroneous picture of how high innovation performance is actually achieved.

First, this study assesses firms’ efficiency of transforming intellectual capital (IC) components into firm performance. Second, this study examines (1) cubic S-curve relationship between board independence and IC efficiency and (2) how firm size moderates the cubic S-curve relationship.

This study employs a stochastic nonparametric envelopment of data (StoNED) framework to estimate IC efficiency, which is derived from the estimation process of transforming structural, relational and human capitals into accounting- and market-based performance indicators. This study conducts regression analyses on 1,104 firm-year observations of Taiwanese semiconductor firms over the period of 2011–2018.

StoNED results suggest that sample firms' IC efficiency can be relatively improved by approximately 80%. Regression results indicate that a cubic S-curve relationship between board independence and IC efficiency exists, and firm size moderates the nonlinear effects.

Overall, this study highlights the importance of examining the nonlinear effect of board independence on IC efficiency from the perspective of agency theory, and the moderating effect from firm size, which may suggest availability of resources from the resource-based view of the firm.

This study contributes to the literature through the innovative application of an efficiency-based tool for evaluating IC efficiency. The cubic S-curve relationship between board independence and IC efficiency also points to the policy concerning the appropriate number of independent directors on board.

The purpose of this study is to benchmark the performance of state-owned coal-fired power plants (CFPPs) and test whether plant-specific knowledge in terms of quality of coal, size, age and make of plant contribute to an improvement in plant efficiency.

The methodology that is utilized in the study follows a nonparametric approach of data envelopment analysis (DEA) with sensitivity analysis and Tobit regression model. The input-oriented DEA models are applied to evaluate the overall, pure technical and scale efficiencies of the CFPPs. Further, slack analysis is conducted to identify modes to improve the efficiency of the inefficient plants. Sensitivity analysis based on peer count and the removal of variables is carried out to identify the benchmark power plant. Through Tobit and bootstrap-truncated regression model, the paper investigates whether a plant's specific knowledge influences its efficiency.

The DEA analysis demonstrates that nine plants are technically purely efficient.The slack analysis reveals that reducing the consumption of oil is the most effective way to improve the efficiency of inefficient plants. Mattur plant is the benchmark for most of the inefficient plants. Regression result suggests that quality of coal and size of plant significantly affect the inefficiency of the sample plants. Bharat Heavy Electrical Limited MAKE plant achieved higher efficiency in comparison to mixed MAKE.

This study is one of the few published studies that benchmark the performance of state-owned CFPPs. This research carried out taking some new uncontrollable parameters of power plant utilities of India. Research work also identifies the possible causes of inefficiency and provides measures to improve the efficiency of the inefficient power plant.