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The aim of this paper is to identify the factors that influence rice farmers' decisions to adopt crop insurance and premium payments (willingness to pay [WTP] amounts). The paper also demonstrates the usefulness of the complementary log-log (cloglog) truncated Poisson double-hurdle model as an alternative hurdle model.

The study first investigated the nature of the dependent variable, which had non-normal residuals and was overdispersed. The probit truncated normal regression double-hurdle model was tried but it failed the normality and homoscedasticity tests; hence, the cloglog truncated Poisson double-hurdle model was employed in the study.

An estimated 61% of respondents would purchase crop insurance, despite farmers not having prior experience with this product. Amongst others, the factors that influence insurance adoption amongst rice farmers are the share of rice in total income, reliability perception of crop insurance schemes and the probability of failure to achieve target yields. The latter helps the authors to address adverse selection, a central issue to the viability of such an insurance programme. The determinants of farmers' WTP are also identified.

Sampling was limited to farmers using irrigation and living in one region of Ghana, which may limit the study’s wider applicability.

As far as the authors are aware, this study is the first to select the appropriate hurdle model based on established properties of the dependent variable on this topic – crop insurance decisions.

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.

This study focuses on the banking systems evaluation in Portugal, Italy, Ireland, Greece and Spain (known as the PIIGS) during the financial and post-financial crisis period from 2009 to 2018.

A conditional robust nonparametric frontier analysis (order-m estimators) is used to measure banking efficiency combined with variables highlighting the effects of Non-Performing Loans. Next, a truncated regression is used to examine if institutional, macroeconomic, and financial variables affect bank performance differently. Unlike earlier studies, we use the Corruption Perception Index (CPI) as an institutional variable that affects banking sector efficiency.

This research shows that the PIIGS crisis affects each bank/country differently due to their various efficiency levels. Most of the study variables — CPI, government debt to GDP ratio, inflation, bank size — significantly affect banking efficiency measures.

The contribution of this article to the relevant banking literature is two-fold. First, it analyses the efficiency of the PIIGS banking system from 2009 to 2018, focusing on NPLs. Second, this is the first empirical study to use probabilistic frontier analysis (order-m estimators) to evaluate PIIGS banking systems.

The purpose of this paper is to examine the effect of funding structure on technical efficiency of banks in Ghana, between 2011 and 2016.

Employing the random-effect and the truncated panel data of 25 banks, the results present new evidence.

The findings reveal that Ghanaian banks are less technically efficient, as the average efficiency scores generated is below the threshold of 1. Furthermore, the results show that banks in Ghana finance their operations mainly with deposit source of funding. The results reveal a significantly positive relationship between funding structure and technical efficiency. However, internally generated source of funds was negatively linked with technical efficiency. This is not surprising because banks that rely on external funds attract higher costs than internally generated funds, and this puts pressure on managers to perform. The results are relevant to emerging economies when the authors use additional macroeconomic factors.

Thus, a proportionally larger deposit base funding would typically lead to an overall increase in technical efficiency of banks in Ghana. Shareholders should put pressure on managers to plough back earnings in order to increase the use of internally generated funds, thus, increasing technical efficiency. Banks that are inefficient should make some adjustments to their weights of inputs and/or outputs combinations by following their benchmark banks (efficient banks) to improve their efficiency.

The results of this study have important implications for regulators, investors and policy makers, particularly an emerging economy. The implication of the study to investors is that investors should be able to identify an appropriate source of funds that can be used efficiently to maximize their wealth in emerging markets. It is important for regulators and managers of banks to improve technical efficiency by considering the role that macroeconomic and monetary environment play when identifying and using various sources of funds as a strategy to improve bank efficiency.

Consequently, future research should investigate the impact of funding structure on technical efficiency for other regions and considering their interactions with institutional quality, macroeconomic factors and financial stability.

To the best of the authors’ knowledge, the study is the first to fulfill an urgent need to explore a robust approach of measuring technical efficiency and funding structure within the context of banks over six-year period, prompting insightful avenues to the survival, growth and performance of financiers in emerging economy.

The purpose of this paper is to evaluate and compare bank efficiency between the two Maghreb countries, Tunisia and Morocco, over the period 2005–2014.

The authors follow the stochastic frontier analysis, where the preferred cost model is determined via various hypothesis tests based on the maximum likelihood estimation. Then, the first and the second derivates of the cost function are employed to determine scale elasticities, scale inefficiencies and technological progress.

Specification tests indicate that the Fourier Flexible form provides better fit to the data set. Further, the estimated model shows that Tunisian and Moroccan banks’ efficiency is positively affected by banking service quality, but negatively influenced by both bank capitalization and GDP growth. Overall, Moroccan banks are found to be the most efficient despite the decrease of efficiency levels in both countries. Additionally, foreign banks have a higher scale inefficiency and, therefore, a lower cost efficiency. Equally, the technical progress raises banking costs in both countries, providing a decrease in efficiency scores.

The findings of this study provide novel insights to Tunisian and Moroccan policy makers on the relevance of the smaller banks’ consolidation to improve bank efficiency by achieving unrealized economies of scale. Also, more reforms should be implemented in Tunisia to reduce non-performing loans.

To the best of the authors’ knowledge, this study is the first which offers a comparison between Tunisian and Moroccan banks to clarify the sources of inefficiency and to make strategic decisions.

The purpose of this paper is to investigate the technical efficiency (TE) of micro and small enterprises (MSEs) and its determinants in the Indonesian manufacturing sector covering comprehensive subsectors.

This research uses the data from the micro and small industry survey sourced from the Indonesian Bureau of Central Statistics for the period 2010–2015. The TE is estimated using data envelopment analysis (DEA) with bootstrapping approach. The TE is also estimated at the firm-level survey data, classified at the five-digit level of the International Standard Industrial Classification system. In addition, a truncated regression model is applied to estimate the effects of the determinants on the TE.

This research finds that there is a low average TE of the MSEs for the subsectors investigated. It is also found that the TE is associated with firm size, location, export orientations on domestic and world markets, firm age, level of technology, and owner education.

The literature investigating the TE of the MSEs and its determinants is still rare in Indonesia. Most of the previous research limited the studies for specific subsectors and/or specific small regions. Therefore, this research has a contribution in measuring the TE of the MSEs for comprehensive subsectors as well as its relation with the determinants in the Indonesian manufacturing sector. Also, the DEA with bootstrapping approach is applied to estimate the TE of the firms based on each relevant subsector, which is rare in the previous research of the Indonesian MSEs.

The purpose of this paper is to provide a total factor productivity index for the African banking industry. It also investigates the impact of some internal and external determinants affecting bank productivity.

The biennial Malmquist productivity index and various regression models (ordinary least squares, Tobit and truncated bootstrapped regression) are employed in analyzing data from 120 banks in 24 African countries from 2007 to 2012.

The results indicate a general decline in productivity of banks in Africa, largely due to inadequate technological progress. State banks are found to be more productive than foreign and private banks. The regression analyses showed that non-executive directors, leverage, management quality, credit risk, competition and exchange rate have significant impact on bank productivity, but ownership and CEO-duality do not.

The results have implications for management of banks, governments and regulators. It shows the need for policy and investments that improve state-of-the art technology. The findings also seem to suggest poor management practices in input usage, especially in operational management, as well as costs emanating from non-interest sources. Bank managers need to address these deficiencies to improve productivity in African banking markets.

A major contribution of this paper is the productivity index provided for the African banking industry. This study is also the first to apply the biennial Malmquist to analyze productivity in the African banking industry.

The purpose of this paper is to examine museum visitors’ experience. The objective of the research is to explore preferences, behaviour, overall. This study experience and the determinants on repeated visits to two heritage sites. In particular, a more comprehensive regression approach is introduced and employed to compare results at two regional museums.

First, a factor analysis identifies a set of orthogonal factors related to visitors’ perceptions on their positive and negative experiences at two different museums. Second, a two-step cluster analysis is implemented to identify specific demand segments. Third, a regression analysis reveals the key determinants that influence visitors’ perceptions on the quality of services provided at the cultural sites. The empirical data were collected at two archaeological museums located in Sardinia and Trentino Alto Adige (Italy).

On the whole, some homogeneous findings have been obtained for the two cultural sites, regardless of the different levels of attractiveness exerted by these two museums. Moreover, the outcomes highlight that the two museums need to be reinterpreted and reorganised with the provision of supplementary services, able to satisfy a broader audience, and enriching their traditional mission that is to collect, preserve and exhibit the archaeological heritage.

The methodological approach presented in this paper is for practitioners and curators to deepen their understanding of their consumers and to improve the overall quantity and quality of services offered.

This paper presents a novel and integrated approach to investigate customers’ experience and their needs with the aim of improving the overall quality of the services provided at the museum. The proposed methodology is used to analyse multidimensional aspects of the visit to a cultural site. Within the literature on museum marketing and management, this methodological framework can be regarded as an alternative approach to analyse visitors’ experience, characteristics, behaviour, preferences and to elicit specific characteristics of different segments of demand.

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.