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This study models cost-efficiency against revenue for hotels in the Pearl River Delta (PRD) – in Guangzhou, Hong Kong and Macau – by considering regional differences and weight restrictions on revenue output.

The authors modified and applied a context-dependent assurance region data envelopment analysis (CAR-DEA) model in assessing the performance of 41 hotels in the PRD. The model considers the relationships among output variables and sets the revenue composition of the hotels as weight restrictions in accounting for the relative importance of different revenue sources.

When assessing the 41 hotels all together, those in Guangzhou outperformed the hotels in other two cities by showing better pure technical efficiency (PTE), while those in Macau had the best scale efficiency (SE). When the assurance region (AR) restriction was imposed, the hotels in Macau outperformed those in the other two cities by showing better SE. When considering regional differences, the Macau hotels ranked first in terms of both the average efficiency score and the overall ranking. All the sample hotels in Guangzhou and half of the sample hotels in Hong Kong and Macau exhibited increasing, constant and decreasing returns to scale.

The research results are limited by data quality and the variables included in the models.

The study helps hotel practitioners in the PRD better assess their cost-efficiency performance by considering regional differences and operational parameters so as to strategically improve their performance.

This study improves upon previous hotel efficiency studies by considering the influence of different operational parameters across different localities. It can be extended to examine the performance of different calibers of hotels, restaurants or tourism entities located in various localities and possessing different operational characteristics.

This paper aims to look into the new corporate reporting phenomenon, the so-called integrated reporting (IR), so as to assess the information level provided, identify trends and explore its determining factors.

This study looks into the IR disclosure level of the annual reports published by 91 companies in the International Integrated Reporting Council (IIRC)’s pilot programme. The authors’ empirical research focuses on four areas: the guiding principles of connectivity and materiality, as well as two content elements: the business model and governance. Following extant research on voluntary disclosure, a disclosure index is proposed and some hypotheses are put forward on its connection with some corporate variables.

The results point out that the disclosure levels of the IRs published by IIRC’s pilot programme members reach medium levels of disclosure. According to the authors’ index, the level of disclosure is significantly associated with the specific environment of organizations (i.e. region and industry), assurance of the report and publication in the IIRC website.

This study makes a relevant contribution, as it presents an innovative IR disclosure index and sheds some light on the disclosure practices of early adopters of IR. This evidence is valuable in understanding the trends in this field and could help the IIRC and other standard setters with a view to improving sustainable development and reporting.

Background: Most children in low-income countries complete their elementary education with low competency in essential reading, writing, and arithmetic skills. Besides, about 250 million students are not learning the basics, most of whom have spent at least four years in school, and this failure is coined the global learning crisis. This study aimed to examine educational quality management practices perceived by secondary school teachers.

Methods: The study employed a multilevel mixed-method design. Employing a simple random sampling technique, the researcher selected 251 teachers from 10 secondary schools in the research regions. He collected data through a researcher-designed questionnaire, school standards, and student achievement records from November 2018 to March 2019. He analyzed data from a questionnaire using frequency, percentage, mean, Pearson correlation, and exploratory factor analysis. The document review concerning quality management was analyzed using content analysis to triangulate the quantitative findings.

Results: At the school level, the study revealed the impracticality of laboratories. Besides, incompetent and unmotivated teachers and students ran the education business from the input side. At the same level, principals' management practices on staff development and encouraging parents to support their schools were low. The principals' management practices in the teaching-learning process were also undesirable at the classroom level. Overall, the study revealed incredibly insufficient input, process, and output management in the study context.

Conclusion: Hence, the study concluded that it is difficult to achieve the very objectives of producing creative, critical, and problem-solving individuals through this type of educational provision and its management. Due to this, it is not easy to achieve quality education for all goals.

This research complements the corporate reporting literature by exploring the different types of assurance, which companies are using to bolster the credibility of their integrated and sustainability reports. A composite quality measure is proposed and this study aims to provide evidence on how combined assurance quality (CAQ) varies among firms.

Content analysis is used to identify “elements” of combined assurance disclosed in integrated and sustainability reports and company webpages. Results are presented in tabular format and supported by non-parametric tests to evaluate differences in CAQ among firms in more detail.

Combined assurance is framed as a function of the responsibility of the board of directors to ensure accurate, complete and reliable reporting and the characteristics of different internal and external sources of assurance. Overall, combined assurance models are being designed conservatively. They focus mainly on specific disclosures and are guided by a limited number of assurance methodologies or frameworks instead of taking a more pluralistic approach to verification of integrated and sustainability reports as a whole.

The study is based on combined assurance practices by a sample of large listed companies in a single jurisdiction. An international comparison of combined assurance and the calibration of the proposed quality measure is deferred for future research.

Limitations in existing assurance practices are identified for the consideration of preparers and assurance providers. The quality schematic also offers practitioners, standard-setters and academics an easy-to-apply technique for examining the different elements of a company’s combined assurance model.

A better understanding of the quality of combined assurance is essential for users’ to place reliance on integrated and sustainability reports and for informing change to existing assurance practices.

The study is the first to examine the operation and quality of combined assurance. The method used to gauge assurance quality provides a useful basis for a more detailed empirical study on the relevance of combined assurance.

The purpose of this paper is to propose an optimal technology selection (OTS) method considering technology alternatives' required input levels of resource, to help companies select an optimal technology.

The proposed method clustered technology alternatives according to their required input levels of resource. After that, in each cluster, the proposed method used data envelopment analysis‐assurance region (DEA‐AR) and analytic hierarchy process (AHP) rating method to evaluate the efficiencies and priorities of the technology alternatives, respectively. Finally, combined scores of the technology alternatives were calculated. A company can choose a proper technology cluster, and then select the technology alternative with the highest combined score within the selected cluster as the optimal technology.

The results showed that the OTS method cannot only select suitable technology which accords with a company's actual input capabilities, but also provide a more accurate selection result.

Traditionally, technologies are evaluated without considering the technologies' required input levels, and simply ranked for selection. However, there are differences between a company's actual resource levels and a selected technology's required input levels of resource. This study proposes an integrated method to evaluate technology systematically and provides a more reasonable selection process for selecting optimal technology.

The purpose of this paper is to employ an efficiency analysis and compare the efficiency scores of publicly or privately operated airports in Turkey.

This study uses analytic hierarchy process, which is one of the widely known multi-criteria decision-making methods to calculate the relative weights of input and outputs. This study also uses data envelopment analysis and assurance region (AR) method to calculate the efficiency scores of airports at the empirical analysis stage.

The empirical results reveal that DEA-BCC and DEA-CCR methods produced almost the same efficiency scores, and 14 airports were found as efficient. Also, AR method was employed and under this method, it was only two airports operated by the private sector that were found as efficient. None of the publicly operated airports was found as efficient.

The main practical implication of this study is that publicly operated airports must improve their efficiency levels in Turkey. This situation indicates that the government policy for the aviation sector must be changed. It is not a coincidence that all publicly operated airports are inefficient. To cope with this situation, it may be a useful policy that establishes a regional airport system or applies the privatization process to all airports.

The most significant contribution of this study to literature is that the AR method, which was never used before in a single country’s airport performance evaluation study, was applied for the first time. Also, this technique was applied first time to Turkish airports for measuring their efficiency levels.

The purpose of this paper is to evaluate Chinese commercial banks efficiency based on different non-performing loans in the process. Moreover, we identified the difference among different types of banks (state-owned commercial banks, joint-stock commercial banks and city commercial banks) and different operation stages (deposit producing sub-stage, profit earning sub-stage and overall stage).

Assurance region (AR) restrictions are combined with a two-stage data envelopment analysis (DEA) model. The efficiency scores of 26 Chinese commercial banks (listed banks) are analyzed by a two-stage AR-DEA model in the study period of 2013–2017.

The results show that state-owned commercial banks had better performance than joint-stock commercial banks and city commercial banks over the five-year study period. The development of Internet finance has positive impact on deposit producing sub-stage and insignificant non-homogeneity existed among the different groups in the circumstances of considering different non-performing loans.

The research findings provide practical insights that help bank managers find the defects in operation process, which need to be improved.

Previous studies viewed non-performing loans as an integrated whole variable. The paper divides non-performing loans into three categories based on the risk and investigates the effect of different types of loans on bank efficiency scores.

Accreditation represents a quality of academic standards and validation, and its impact on business schools is multifaceted. Accredited institutions are widely acknowledged for their higher quality, financial stability, stakeholder acceptance and overall growth compared to non-accredited educational institutions. Given these positive outcomes, this study aims to explore the role of accreditation in fostering financial innovation and business sustainability.

The study used a qualitative design to understand this relationship, engaging 36 leaders from Advance Collegiate Schools of Business-accredited business schools in the Gulf Cooperation Council region as participants to collect data. Semi-structured interviews were conducted to gain an in-depth understanding of the topic. Data were analysed using the content analysis method.

That accreditation significantly influences the business sustainability of these schools. In addition, although the direct impact of accreditation on financial innovation may not be immediately apparent, it was observed that financial inflows experienced remarkable growth after obtaining accreditation.

While the effects of accreditation have been thoroughly researched, its influence on financial innovation and business sustainability remains unexplored. This study aims to discern if accredited educational institutions excel in financial innovation and maintaining sustainable business practices. These findings have important implications as they guide university administrators to maximise the benefits of accrediting their business schools.

The purpose of this paper is to consider the following problem: the authors consider a new constructed unit system to indicate the characteristics of the inputs and outputs of different decision-making units (DMUs) and propose several modified models to calculate their efficiencies based on overall value judgment and weight restriction in the production process.

This paper applies principal component analysis (PCA) to analyze the original value judgment information, and the key indices in the production process are extracted. The modified data envelopment analysis (DEA) models are proposed and DEA efficiencies and their projections are calculated.

By incorporate PCA and DEA, the authors propose new virtual DMUs composed of unique optimal multipliers of each DMU. Crucial indexes are extracted and the weights of inputs and output are ranked through using PCA by taking the preference and value judgments of all DMUs into consideration. Weight constraints from the ranking are utilized to improve the traditional CCR-DEA model. The empirical results validate the feasibility of the approach.

The method can be used in many organizations which have excessive amounts of inputs and outputs variables, such as banks, chain stores, car factory, etc.

This paper presents an integrated methodology of using PCA and DEA for considering the preferences of the inputs and outputs and value judgment of all DMUs and ranks the importance of the indicators from the overall perspectives.

This purpose of this paper is to present a tool for facilitating personnel selection when multiple heterogeneous human resource managers use multiple criteria. Two problems result from such a situation. First, when multiple criteria are applied, it is unusual for one candidate to dominate the other candidates in all areas, which requires assigning weights to the different criteria to be able to rank the candidates. Second, in a heterogeneous selection committee, finding weights that accurately reflect the individual preferences of all members is difficult.

To deal with the multidimensional setting of selecting personnel, this paper introduces data envelopment analysis with assurance region (DEA-AR) to determine individually optimal weights for each applicant.

DEA-AR leads to a score for each applicant that can serve as a signal for productivity and, thus, for evaluating the candidate. Based on linear programming, DEA-AR not only aggregates multiple dimensions into a single score but also incorporates managers’ preferences. In addition, the procedure is transparent and fair. It seems to be highly appropriate for selecting personnel. Based on a simulated dataset of applicants, the use of DEA-AR for selecting personnel is illustrated and discussed.

DEA-AR provides a tool for supporting personnel selection or pre-selection. This model is based on a mechanical procedure and considers managers’ ideas about weights.