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The use of unmanned aerial vehicles (UAVs) has significantly increased in the past decade and nowadays is being used for various purposes such as image processing, cargo transport, archaeology, agriculture, manufacturing, health care, surveillance and inspections. For this reason, using the appropriate image processing method for the intended use of UAVs increases the study’s success. This study aims to determine the most suitable one among the innovative methods that constitute the image processing system for a UAV to be used for surveillance purposes.

Analytical hierarchy process has been used in the solution of the decision problem to be handled in three stages, namely, platform, architecture and method. The most suitable alternative and the effect weights of these criteria results were determined at each stage.

As a result of this study, Jetson TX2 was determined as the most suitable embedded platform, ResNet is the optimum architecture and Faster R-convolutional neural networks was the best method in the image processing layer for a system that will provide surveillance with image processing method using UAV.

In UAV designs, where multiple hardware and software choices and system combinations exist, multi-criteria decision-making (MCDM) approaches can be used as a system decision mechanism.

The novelty of this work comes from the application of MCDM methods that are used as a multi-layered decision mechanism in UAV design.

With increasingly complex logistics information technology and dynamic logistics operations in a global setting, today′s logistics managers confront an overwhelming number of decision alternatives. Perhaps the most effective way of evaluating such a large number of alternatives is to utilize advanced information technologies. These technologies encompass decision support systems (DSS), artificial intelligence (AI), expert systems (ES), electronic data interchange (EDI), and barcoding. Since the performance of these technologies is greatly influenced by their supporting software, their success often hinges on the selection of proper software packages. In selecting proper logistics software, an analytic hierarchy process (AHP) is proposed which can effectively deal with both qualitative and quantitative factors in multiple‐criteria decision environments.

To provide an interesting approach for determining interval measures, through the analytic hierarchy process, for integration with social network analysis for knowledge mapping in organizations.

In order to develop improved organizational and business processes through knowledge management, a knowledge audit should be conducted to better understand the knowledge flows in the organization. An important technique to visualize these knowledge flows is the use of a knowledge map. Social network analysis can be applied to develop this knowledge map. Interval measures should be used in the social network analysis in order to determine the strength of the connections between individuals or departments in the organization. This paper applies the analytic hierarchy process to develop these interval measures, and integrates the values within the social network analysis to produce a meaningful knowledge map.

The analytic hierarchy process, when coupled with social network analysis, can be a useful technique for developing interval measures for knowledge‐mapping purposes.

The analytic hierarchy process may become tedious and arduous for use in large social network maps. More research needs to be conducted in this area for scalability.

As social network analysis is gaining more prominence in the knowledge management community, the analytic hierarchy process may be able to provide more valuable measures to determine the strengths of relationships between actors than simply using ordinal numbers.

Coupling the analytic hierarchy process with social network analysis provides a novel approach for future knowledge‐mapping activities.

The use of Analytical Hierarchy Process (AHP) is an effective way to deal with qualitative decision areas of operations management. Four published applications of AHP are briefly reviewed in forecasting, supplier selection, facility location, and choice of technology. Furthermore, four more potential applications are suggested in other areas of operations management, including product design, plant layout, maintenance frequency selection, and choice of logistic carrier. In addition, suggestions for other areas of research are discussed.

The purpose of this paper is to develop an analytical hierarchy process (AHP)‐based selection model for choosing a web analytics product/service that meets organizational needs.

The research objective is achieved through modeling and empirical validation.

While more criteria could be added, the proposed selection model provides a feasible approach to choosing a web analytics product/service. Cost‐ and risk‐related criteria are weighed heavier than those of technical capabilities. Tools based on the page tagging method are more popular than those based on transaction log file analysis. The level of technology savvy might play a role in the application of the selection model.

The development of web analytics products/service is still evolving. Thus, as the use of web analytics increases, more criteria might be identified and added to the model. The model is validated by groups for different sectors. In the future, it is suggested to conduct a similar study with one sector by different groups.

The selection model provides a process in which practitioners can systematically evaluate pros and cons of web analytics products/services. The selection model includes a comprehensive list of criteria that vendors of web analytics products/services can use to benchmark their products. Following this model, an organization contemplating the use of web analytics will more likely find one product/service that accommodates organizational and technological characteristics.

A sufficiently comprehensive list of qualitative and quantitative criteria for evaluating web analytics products/services was developed. Practitioners will be able to use the model to select a proper tool. In academia, the article fills a gap in literature that might bring academics' interests in this area.

Traditional procedures alone are not appropriate for justifying advanced manufacturing systems. It is necessary to consider the benefits of new technology in manufacturing systems since financial return is dependent on many factors outside manufacturing. An in‐depth examination is the foundation of the comprehensive comparative analysis presented here. The mechanism used to combine and synthesise tangible and intangible benefits of advanced technology is the analytic hierarchy process. A cost/ benefit analysis incorporates cashflows and benefits to determine the best manufacturing system choice. A detailed example is given to illustrate the procedure, and to compare the results with that of the traditional return on investment method.

The purpose of this paper is to develop an analytic hierarchy planning-based framework to establish criteria weights and to develop a school performance system commonly called school inspections.

The analytic hierarchy process (AHP) model uses pairwise comparisons and a measurement scale to generate the weights for the criteria. The validity of the approach is confirmed by comparing the outputs of school inspection and the outputs of the model in a sample of schools.

The framework proposed enables school management to address several issues pertaining to its competitive advantage with other schools, the two most important being establishing its performance ranking in the marketplace and identifying the service elements that most require improvement. This study develops a cohesive approach to identify which quality attributes or dimensions require attention.

For school inspections, the data collection and computational problems would increase with the increase in the number of criteria and sub-criteria, as well as the number of schools considered in the selection. Although the range of reported AHP applications is extensive in many disciplines, examples in school quality and inspection remain still rare; as a result, this study could not compare its results with other AHP applications in school inspection or assessment.

The AHP method has the distinct advantage that it decomposes a decision problem into its constituent parts and builds hierarchies of criteria. AHP enables assessors to capture both subjective and objective evaluation measures of school quality. By providing a useful mechanism for assessing the consistency of the evaluation measures and alternatives, the AHP reduces bias in decision making.

The AHP model also provides a more systematic evaluation of a given school’s qualitative performance criteria. The proposed AHP model is attractive to assessors and decision makers because its pairwise comparison procedure enables them to offer a relative (rather than absolute) individual criterion assessment on those qualitative factors.

The AHP model could become a sustainable component of overall school system quality improvement by maturing over time. The AHP annual scores could be used as realistic and measureable gauges for measuring school improvement.

The growth of tourism development in Malang makes some regions optimize their tourism potential, leading to economic growth in Indonesia. Malang regency has several tourism villages with the concept of sustainable tourism. Using leverage analysis from the multidimensional scaling approach (MDS), we find two sensitive attributes. An analytical hierarchy process (AHP) test was conducted, resulting in the best strategy for each tourism village: developing strawberry-picking tour for Pujon Kidul and new tourism packages related to water attraction for Sanankerto and developing Bromo volcano tourism package for Gubugklakah. These strategies are believed to increase the development of tourist villages without compromising their sustainability.

The purpose of this study is to develop an evaluation criteria system for search engines using the Delphi method and the analytic hierarchy process, and to conduct an empirical study on Chinese search engines to verify it. This is because the evaluation criteria in current research rarely considers expert opinions and experience, and seldom calculates the weight of each criterion by quantitative methods.

Expert investigation of the web‐based Delphi method was employed to develop the evaluation criteria, and the analytic hierarchy process based on an exponential scale was adopted to calculate the weight of each criterion. An empirical study was designed to test the evaluation criteria system. A total of 12 study participants were invited to evaluate six popular Chinese search engines by means of e‐mail questionnaires. All the calculation processes were executed automatically by Java programming.

The indexing structure and search method were the core criteria for evaluating the search engines. Google (using simplified Chinese characters) achieved the best performance among the six typical Chinese search engines.

The criteria for search engine evaluation were determined and weighted by the web‐based Delphi method and the analytic hierarchy process based on an exponential scale.