Search results

Countries in Africa have a common goal policy of industrialisation that is expected to be driven by investing in innovation that yields efficiency. The purpose of this paper is to investigate the technical efficiency effects arising from innovation inputs including internal R&D, human capital development (HCD), and foreign technology adoption in manufacturing firms in Africa.

This study uses cross-sectional firm-level survey data from the 2013 World Bank Enterprise Survey and the linked 2013 Innovation Follow-up Survey. A heteroscedastic half-normal stochastic frontier is used for analysing the technical efficiency effects of innovation inputs of 418 firms.

This study reveals that internal R&D, and foreign technology have negative effects on technical efficiency. Notwithstanding, the combination of foreign technology and internal R&D, and foreign technology and HCD reinforce each other’s effects on technical efficiency.

This study provides evidence that whereas individual innovation inputs may not yield positive efficiency outcomes, the combination of absorptive capacity enhancing inputs comprising internal R&D and HCD with foreign technology is vital for enhancing technical efficiency in manufacturing firms in Africa. This study offers important lessons for managers in manufacturing firms in Africa.

This study is virtually the first to investigate the relationship between innovation inputs and efficiency in Africa. This study demonstrates that investing in foreign technology in isolation from absorptive capacity enhancing innovation inputs diminishes efficiency. HCD and internal R&D are imperative for building absorptive capacity that enhances efficiency outcomes arising from foreign technology.

The purpose of this paper is to incorporate risk in technical efficiency of ASEAN banks in a panel data framework for the period 2000 to 2015.

The directional distance function and semi-parametric framework are employed to estimate efficiency scores for two scenarios, one with only good outputs and the other with a combination of good and bad outputs.

The findings show there is no evidence of technological progress for banks in ASEAN and concerns about the outperformance of Vietnam’s banks. In addition, performance of Vietnam’s banks tends to be distorted by low level of loan loss reserves.

To reflect the true performance and shorten the period of removing bad assets, the State Bank of Vietnam can request banks in Vietnam to book more loan loss reserves.

By examining such a new approach, this study makes an early attempt to incorporate credit risk into the banking efficiency in ASEAN region.

This study aims to propose a solution to accelerate financing support low carbon (circular economy) transition. The authors developed a sustainability governance (SGOV) model and a sustainability governance (SGOV) index as a proxy for the diffusion of sustainability innovation. This study investigates the effect of SGOV practices on profitability with the mediating role of operational efficiency.

The SGOV index consists of 32 and 122 sub-items, constructed using content analysis of annual and sustainability reports published by banks listed on the Indonesia Stock Exchange (IDX) from 2010 to 2020 (404 bank-year observations).

Banks are at a moderate level of sustainability innovation. They are prioritizing the balance aspects of financial, social and environmental. SGOV practice negatively affects profitability. However, operational efficiency plays a positive mediating role that is robust.

The measurement of the SGOV index uses criteria that have not been tested in previous studies. There is the potential subjectivity in interpreting qualitative data, although this has been minimized by cross-checking the analysis of five raters.

This study gives feedback for the Indonesia sustainable finance (SF) journey phase I to proceed into SF journey phase II.

The SGOV model can be applied in other industry sectors to know the readiness for entering low carbon (circular economy) transition.

The uniqueness of the scoring technique assuming a step-by-step innovation model to sustainable finance.

This paper aims to understand the most efficient hotel system and why efficiency varies across years and between the two differing types of hotel businesses in Turkey.

A data envelopment analysis (DEA) analysis was used to characterise the efficiency of all-inclusive (AI) and bed and breakfast (B&B) hotel businesses with one output (total revenue) and three inputs (labour, food and capital costs). The Malmquist approach is then used to discern changes in total efficiency (TTE) and intertemporal shifts in the efficiency frontier (technological change (Tch)).

The results reveal that the AI hotel operates at 100% efficiency in the summer and year-round. The B&B hotel business operates at 89.6% with variable constant returns to scale during the summer and with 100% efficiency. The results of the Malmquist approach indicate that the total factor productivity grew in the years 2015, 2016, 2018 and 2019, while the other years were marked by inefficiency. Such increases were due to technical efficiency change (TEch) and Tch, which means that managerial and allocative efficiency (AE) were barely achieved. Slight differences were noted in the two time periods (all year and summer), suggesting that the scale of hotel businesses is prepared to operate all year round, and this calls for strategies to mitigate seasonality.

As to avenues for future research, the limitations of this study are threefold. First, the hotel businesses are not parallel in terms of the duration of their service offerings. Future research may consider including an AI hotel business that is in operation for the whole year. Second, businesses in Turkey are sceptical about sharing their data as it is considered confidential. However, to better generalise the results and encourage hoteliers to consider the positive outcomes of such analysis, the number of observations could be increased by considering more hotel businesses in both categories. Third, a mixture of data representing businesses operating in various countries may reflect if the efficiency scores vary internationally.

Overall, AI hotel businesses are more attractive but less efficient than B&B. Furthermore, the external crisis impacts the efficiency of hotel businesses meaning that hotel managers could keep on exploring AI, perhaps educating their hosts not to waste or not offer huge quantities. Hotel managers may also need to enlarge their seasonal activities to ensure more efficiency.

Despite the intentions of AI hotel businesses to increase their profitability with a lower level of service quality, this study shows that the AI hotel business is very attractive but not so efficient due to the higher propensity of guests to consume food and beverages in excess that compromises the definition of efficiency as zero waste. AI is very attractive for family groups or those seeking the pleasure of relaxation at seaside resorts and is also very popular in Turkey. On the other hand, the B&B hotel business is more efficient but less attractive.

The contributions of this paper are threefold. First, the authors analysed the efficiency and inefficiency of hotel businesses within nine years of operations. During this period, Turkey experienced first a tourism boom (2011–2014) followed by stagnation and subsequently a sharp decline due to political instability resulting in an (in)direct impact on tourism (2015–2019). Second, the authors compared the efficiency and inefficiency of AI and B&B hotel businesses. Third, the authors examined the effects of hotel management factors to ensure efficiency.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

This paper investigates the development of efficiency and the progress of banking integration in the European Union by checking for convergence among banks of European and Eurozone countries as well as contrasting the results with those of United States banks.

Initially, we employ the two-stage semi-parametric double bootstrap DEA method, which absorbs the effects of possible integration barriers in the measurement of efficiency. Afterwards, we apply a panel data model, in order to investigate the process of banking integration by testing for convergence and for convergent clusters in banking efficiency.

Our main findings show that the bank efficiency of the US is considerably higher than that of the Eurozone and the European Union. Although there is no evidence of convergence across the banking groups, our results indicate the presence of club convergence. We also conclude that the US banking system is closer to convergence than the Eurozone and the European Union banks. Nevertheless, this outcome is subject to change in the future due to the fact that Eurozone and European Union banks' speed of convergence is higher than that of US banks.

Our survey is unique in trying to check for convergence while controlling for country-specific and bank-specific factors that affect the efficiency of European and Eurozone banks. Moreover, recent literature does not compare the convergence of efficiency of Eurozone, European and US banking. Finally, in our paper special consideration was given to the comparison of commercial, cooperative and savings banks, as subsets of our banking groups.

The study examines the effect of macroeconomic risk, inflation uncertainty and instability associated with key macroeconomic indicators on the efficiency of financial institutions among economies in sub-Saharan Africa (SSA).

Data for the empirical inquiry were compiled from 35 SSA economies from 1996 to 2019. The empirical estimates were carried out using pooled ordinary least squares (POLS) with Driscoll and Kraay’s (1998) standard errors.

Reported empirical estimates show that macroeconomic risk and exchange rate volatility constrain the efficiency of financial institutions. Further results suggest that inflation uncertainty has a significant influence on the efficiency of financial institutions among economies in the subregion. Additionally, reviewed empirical estimates show that institutional quality positively moderates the nexus between inflation uncertainty and financial institution efficiency. At the same time, political instability is found to worsen the adverse effect of macroeconomic risk on the efficiency of financial institutions.

For policymakers and governments, improved institutional structures are recommended to ensure the operational efficiency of financial institutions, especially during an inflationary period. For decision-makers among financial institutions, the study recommends policies that have the potential to make their institutions less vulnerable to macroeconomic risk and exchange rate fluctuations.

The approach adopted in this study differs significantly from related studies in that the study examines and reviews interactions and relationships not readily found in the reviewed literature.

The study aims to summarize the 20 years of literature published in takaful between 2000 and 2019 and propose some key areas as the directions for future research.

The present study utilizes the systematic method of reviewing the literature. The SCOPUS database has been accessed, and 96 articles have been accounted for the analysis. The articles are grouped in their exclusive themes, such as consumer behavior, financial and nonfinancial performance, takaful models, human resources and governance.

Takaful research has widely covered marketing, finance, human resource, governance and stresses on its legal issues. Both qualitative and quantitative methodologies have been employed. The research gaps have been classified based on the respective areas. Large share of current body of takaful literature consists of the studies related to the application of behavioural theories to examine the behavioural intention to take up takaful services.

The study enriches the literature of takaful by reviewing articles according to their respective themes, thereby contributing to the significant findings missing from existing literature surveys.

This research investigates the effect of accessibility to points of tourist interest (buffer) and direct and indirect spatial spillover effects of agglomeration economies on tourism industry revenues in Spain.

Data were collected from the Bureau van Dijk's (BvD) Orbis global database. The data were analysed using a spatial econometric model and the Cobb–Douglas production function.

This study reveals that hotels located inside the buffer zone of points of tourist interest achieve better economic outcomes than hotels located outside the buffer. Furthermore, the results show that there is a direct and indirect spatial spillover effect in the hotel industry.

The results provide valuable information for identifying areas where the agglomeration of hotels will produce a spillover effect on hotel revenue and the area of influence of location characteristics. This information is relevant for hotels already established in a destination or when seeking a location for a new hotel.

The results of this study can help city planners in influencing the distribution of hotels to fit desired patterns and improve an area's spatial beauty.

The paper provides insights into how investment, structural characteristics, reputation and location affect hotel revenue.

The paper aims to enrich previous findings for an emerging banking industry such as Vietnam, reporting the difference between the parametric and nonparametric methods when measuring cost efficiency. The purpose of the study is to assess the consistency in issuing policies to improve the cost efficiency of Vietnamese commercial banks.

The cost efficiency of banks is assessed through the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA). Next, five tests are conducted in succession to analyze the differences in cost efficiency measured by these two methods, including the distribution, the rankings, the identification of the best and worst banks, the time consistency and the determinants of efficiency frontier. The data are collected from the annual financial statements of Vietnamese banks during 2005–2017.

The results show that the cost efficiency obtained under the SFA models is more consistent than under the DEA models. However, the DEA-based efficiency scores are more similar in ranking order and stability over time. The inconsistency in efficiency characteristics under two different methods reminds policy makers and bank administrators to compare and select the appropriate efficiency frontier measure for each stage and specific economic conditions.

This paper shows the need to control for heterogeneity over banking groups and time as well as for random noise and outliers when measuring the cost efficiency.