Analytic Hierarchy Process Model Research Articles

Solid mineral potential evaluation using integrated aeromagnetic and aeroradiometric datasets

The analytical hierarchy process (AHP) was employed to delineate the mineralisation potential across the notable schist belts in northwestern Nigeria. High-resolution aeromagnetic and aeroradiometric datasets were taken into consideration. This was achieved by using advanced signal enhancement techniques to study the structures, identify the hydrothermal alteration zones (that could serve as a pathway for mineralisation), and understand the geologic settings. Amongst the enhancement techniques are first vertical gradient, analytic signal, CET grid analysis and porphyry, Euler deconvolution, and K/Th ratio. The analytic signal reveals lithologic contact, structures and anomalous occurrences that aided the classification of the site into three magneto-lithologic zones: high (> 0.094 nT/m), intermediate (0.028 to 0.094 nT/m), and low magnetic zones (< 0.028 nT/m). The high magnetic zones (HMZ) were considered the main magnetic source outlines, which are inferred to be dominantly intrusive zones for hydrothermal activities. The 3-dimensional Euler deconvolution reveals highly magnetic and intrusive depth sources to be within the range of < 100 to 500 m. The Centre for Exploration Targeting (CET) grid technique revealed the structural distribution from which the lineament density map was produced. The orientations of the prevalent structural anomalies are E-W, NE-SW, WNW-ESE and NW–SE, with similar orientations observed from the first vertical gradient and the analytic signal. The highly dense structural zones coincide with the high magnetic zones and high-frequency amplitudes of the analytic signal and the vertical gradient map, respectively. Additionally, the CET porphyry detects the centres of the intrusive porphyries to be within zones of high lineament density. This reveals that the mineralisation potential of the area is structurally controlled. On the other hand, radioelement maps (eU, eTh, and K%) and ternary maps were used for lithological classification. The radiometric ternary map revealed the highly radioactive zones and the superior concentration of individual radioelements in their respective areas. The K/eTh ratio map delineates highly potassic alteration zones. The AHP model and weighted overlay tool were employed to integrate the analytic signal, lineament density, and K/Th ratio. Consequently, the mineralisation potential of the study site was revealed and classified into high, moderate, and low. This result was validated using known mine sites. There was a total agreement, with 87.5% of mines plotting within the high mineralisation potential class and 12.5% in the moderate class. Promising targets were identified for development.

AHP-based quantitative evaluation of radiation safety in nuclear technology utilization units

In order to protect human health from the hazards of nuclear radiation, it is necessary to standardize the management of irradiation equipment. According to the principle of “man-machine-management-environment” intrinsic safety, analytic hierarchy process (AHP) and cloud model method were adopted. A quantitative safety evaluation index system was established from four aspects: safety management, safety environment, irradiation equipment and experimental team. Based on the actual situation of an experimental institution, the safety grade of this experimental institution was systematically analyzed. The safety grade of this experimental organization was excellent, but it still needs to improve certain aspects. Corresponding management recommendations were put forward for nuclear technology utilization units of different safety levels.

Functional analysis of technological innovation systems enabling digital transformation: A semi-quantitative multicriteria framework applied in the olive sector

CONTEXTTechnological innovation systems (TIS) play a key role in facilitating digital transformation (DT) in various sectors. In agriculture in particular, traditional qualitative assessments of TIS fall short of providing actionable insights. The olive sector in Andalusia, a world leader in olive cultivation, is a case where DT is essential for long-term competitiveness and sustainability. OBJECTIVEThe objective of this article is twofold: 1) to provide a comprehensive methodological framework for the functional analysis of a TIS, which allows a semi-quantitative assessment of the performance of a TIS at subfunctional, functional and global levels; and 2) to illustrate the application of this framework to the case of the TIS for the DT of the olive sector in Andalusia. METHODSUsing the Analytic Hierarchy Process (AHP), the framework allows the performance of the TIS for the DT of the olive sector in Andalusia to be measured along different functions, providing a nuanced and actionable assessment. AHP is a multicriteria decision making methodology that allows the decomposition of a discrete decision problem into a hierarchical structure. Expert knowledge was used to evaluate the proposed AHP model of the performance of the TIS for the DT of the olive sector, in particular a panel of 34 experts. RESULTS AND CONCLUSIONSThe application of the framework identified the main weaknesses in the functions of knowledge transfer, business activities and resource mobilisation within the TIS for the DT of the olive sector of Andalusia. Conversely, strengths were identified, particularly in the areas of market formation and knowledge development. Policy recommendations are made to address these weaknesses and capitalise on the strengths identified, thereby accelerating the DT of the sector. SIGNIFICANCEThis study adds to the TIS literature by providing a semi-quantitative, multicriteria, replicable and adaptable framework for agricultural innovation policy. The framework provides actionable insights for policy makers and stakeholders in the olive sector to foster an environment conducive to DT and thereby steer agriculture towards an innovative, competitive and sustainable trajectory. Insights from the olive case offer lessons for DT in similar contexts.

A Prioritization Method to Optimize School Operational Assistance Fund by Using AHP Approach

In Indonesia, education funding provided by the central government is made up of the components of personnel costs, investment costs, and operating costs. Since its implementation in 2005, the program has found several obstacles. It’s crucial to have an optimization tool to overcome the complications. The main problems that have arisen in the allocation of these funds so far have been lacking in planning and the lack of participation of the school ecosystem, in particular in determining the planning, planning documents and the priority scale of the projects. Program and activity plans based on the School Operating Assistance (BOS) platform. The Analytical Hierarchy Process (AHP) model is a prioritization approach based on determining the priority scale on the comparison of one option with another. The AHP model is a powerful but simple method that is usually used to make decisions. This approach has been implemented in various sectors, business, government, management, and education. In this study, the AHP model was used to determine the priority scale on the criteria of BOS allocated funds in the current year so that it could be absorbed optimally and can be utilized properly in its implementation for Vocational School activities. The results of the study show that the use of AHP makes it easier for school residents to prioritize the use of funds for school activities. Using the AHP model allows managers to record strategic goals using weighted criteria as the basis for prioritizing the use of funds. AHP can also work among different stakeholders in the school (principals, treasurers, teachers, and committee, parents/guardians) to participate in decisions about the use of BOS funds, to improve the quality and form of decision support taken to improve school performance.

Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia

Drought continues to be the worst natural hazard in the world affecting ecosystems, economies and overall human welfare with severe consequences in developing countries. While drought is an unavoidable climatic phenomenon, actions can be made to improve preparedness and mitigate the impacts upon proper forecast on susceptibility. Drought susceptibility modeling plays a key role in determining how best to mitigate and adapt to drought occurrences. This research explores the application of geospatial techniques and Analytic Hierarchy Process (AHP) in drought susceptibility modeling for the drought-prone Bilate River watershed, located in the central Rift Valley drylands of Ethiopia. A total of 15 parameters were used including rainfall, temperature, evapotranspiration, soil moisture, normalized difference vegetation index, land surface temperature, soil texture, land use-land cover, topographic wetness index, modified normalized difference water index, drainage density, slope, elevation, population density and aspect to model drought susceptibility. Findings showed that nearly 70.2% of the area falls under the moderate drought category, followed by the severe (23.2%), mild drought (6.6%) and extreme (0.02%) drought categories in the watershed. Based on zonal administration, Wolayta Zone has a high spatial coverage of severe drought with 54.1% (659.3 km2) while Hadiya has a high spatial coverage of moderate drought with 24.6% (908.9 km2). The drought susceptibility model (DSM) receiver operating characteristic (ROC) curve was then created, and the area under curve (AUC) was calculated. The results of the analysis showed that the AUC is 0.701 (70.1%) indicating that the model is reasonably good model. Hence, geospatial approaches in conjunction with the AHP model improved the drought susceptibility modeling’s reliability, which has significant implications for drought adaptive management and preparedness planning.

Delineation of environmentally sustainable urban settlement using GIS-based MIF and AHP techniques

Choosing appropriate locations for built-up growth while maintaining natural balance has become necessary for sustainable urban planning. To this end, two multi-criteria decision-making (MCDM) approaches—the multi-influencing factor (MIF) and the analytical hierarchy process (AHP)—have been applied in this work. The MIF model results show that 23.546% of the study region was very highly suitable for newly built-up areas, and 18.786% was restricted for urban settlement, whereas, in the AHP model, 28.907% of the area was highly suitable, 17.619% was restricted for urban settlement. Finally, the dependability and efficiency of the two models used for the study area were assessed through the receiver operating curve (ROC) and area under curve (AUC) analysis. The comparative analysis demonstrates that the MIF approach (AUC 0.817) is more suitable and reliable than the AHP (AUC 0.783). The present work provides new insights to integrate GIS tools with MCDM for practical urban land suitability assessment.

Problem analysis of financial aspects of halal culinary micro enterprises

This research aims to recommend priority problems that must be resolved regarding the financial aspects of halal culinary micro-enterprises in Bangkalan Regency. Data on financial aspects of micro business problems was taken using interview, observation, documentation, literature study and questionnaire methods. A questionnaire instrument was used to obtain data on weighting problems regarding the financial aspects of micro businesses. The questions asked in the questionnaire are related to preferences and assessments of aspects of the financial problems of halal culinary micro-enterprises that are being evaluated. The research respondents were 12 people who were determined using a purposive sampling technique, with the criteria of understanding culinary micro businesses in Bangkalan which included academics, bureaucrats, business actors, culinary micro business associations and banking employees. The collected data is processed using Analytic Hierarchy Process modeling, starting from identifying goals, to analyzing results. Through the Analytic Hierarchy Process, it can be seen that the main challenge faced by halal culinary micro businesses in Bangkalan Regency is poor financial records which have an impact on business sustainability and growth. Therefore, improving financial records is a top priority that needs to be addressed with training, the use of applications that are simple and easy to use. The government must provide training and assistance as well as provide incentives or subsidies to micro businesses that implement a good financial recording system. Good financial records will encourage the growth of halal micro businesses in Bangkalan and will strengthen the regional and national economy.

Green Marketing Performance Statistics Based on AHP and BP Neural Network Models

In order to promote the development of circular economy, starting from green marketing is the best means. Combining artificial neural network technology and hierarchical analysis subjective evaluation method, the key factors affecting green marketing performance were analyzed by constructing an evaluation index system for green marketing performance statistics, and the relative weights of each performance indicator were calculated by using analytic hierarchy process (AHP) and the relative importance ranking was given. Then the evaluation results were introduced into the neural network model as input variables. The evaluation results are trained and tested by using the inverse inverse propagation neural network. Finally, the simulation results show that the model can not only reduce the defects of subjective randomness, but also improve the predictability, accuracy and effectiveness of green marketing performance statistics. The calculation results are accurate, the method is feasible, and the errors are controllable, which has theoretical scientific significance and practical guiding significance.

Corporate governance for sustainable development in Vietnam: Criteria for SOEs based on MCDM approach.

This research explores the nexus between corporate governance and sustainable development, focusing on State-Owned Enterprises (SOEs) in Vietnam. Recognizing the pivotal role of SOEs in the national economy, this study employs a Multi-Criteria Decision-Making approach (MCDM) to assess and enhance the corporate governance frameworks of these entities. First, the Data Envelopment Analysis (DEA) model is employed to identify the most qualified prospective SOEs firms based on several quantitative criteria. Then, the spherical fuzzy analytic hierarchy process (SF-AHP) model is used to identify priority weights for a given set of qualitative criteria, the Evaluation based on distance from average solution (EDAS) model is implemented to rank enterprises in the SOEs sector. To validate the proposed models, a case study conducted within the Vietnamese electric power industry is utilized. The MCDM methodology integrates diverse factors such as business management, corporate social responsibility, and corporate governance shareholder to construct a comprehensive evaluation framework. By applying this approach, the study aims to identify the key drivers and barriers influencing corporate governance practices within Vietnamese SOEs. The study's findings illustrate the efficacy of the suggested approach in evaluating corporate governance performance, providing valuable insights for policymakers, corporate leaders, and stakeholders involved in shaping the governance landscape of SOEs in Vietnam. By aligning corporate governance with sustainable development principles, the research aims to contribute to the ongoing discourse on responsible business practices, offering practical recommendations to enhance the performance and resilience of SOEs in the pursuit of long-term socio-economic and environmental sustainability.

Mapping and prediction of the level of Land Use Conflict using Analytical Hierarchy Process and Celluar Automata-Markov Model in Benue, Nigeria.

Mapping and prediction of the level of Land Use Conflict using Analytical Hierarchy Process and Celluar Automata-Markov Model in Benue, Nigeria.

Software Quality Assessment Approach using Analytical Hierarchical Model: Applied in SMEs

Continuous software quality evolution is crucial albeit challenging due to tight budgets and timelines. In fact, neglecting software quality in favour of customer satisfaction; either by reducing internal or external defects or by adding technical features shall place much pressure on project managers and stakeholders to find a balance between project budget and schedule. The increasing demand for high-quality software among stakeholders emphasizes the need for comprehensive approaches that can evaluate and rank quality metrics to maximize their benefits. In this research paper, we introduce an assessment approach developed using key quality metrics integrated from Cost Of Software Quality (COSQ) metrics, reliability metrics, and cost of defects metrics based on quantitative multicriteria decision analysis capabilities of the Analytic Hierarchy Process (AHP) model applied with a real case study for the software development team in Small and Medium Enterprises (SMEs) since most of them do not follow standards nor adopt well-structured quality methods. The evaluation is established based on the integrated AHP assessment approach as a practical solution for organizations seeking a critical examination of the relative significance of software metrics in terms of their utility in enhancing business performance. As a result, an evaluation of these quality metrics has been conducted to highlight the percentage of weight for each quality metric based on interviews with subject matters experts. The ranking of software quality metrics greatly helps stakeholders in selecting the most appropriate attribute for evaluating the developed software to identify high-impact quality initiatives and measure their effectiveness in the Software Development Life Cycle (SDLC)

Supply Chain Management Strategies Approach for the UK Textile Industry

This study focuses on the specific types of supply chain strategies throughout the UK textile industry as extant literature has either emphasised on the fashion apparel industry or on sub-industry of fast fashion. A combination of normalised local priority weights of criteria and sub-criteria is used with respect to successive hierarchical levels which modelled in an Analytical Hierarchy Process (AHP) at different levels. This helped in obtaining global composite priority weights for all the sub-criteria at third level of AHP model. The changes in different factors are observed with respect to digitalisation in sensitivity analysis at different levels of variations in the weight for which marginal changes are noted in the following variables: development of key suppliers, supplier capability auditing, and long-term orientation with suppliers. Supply base optimisation and purchasing integration showed changes at all levels of variations. Purchasing and production strategy was crucial as primary criteria for accomplishing the goal of the supply chain management future. There was substantial evidence from the three companies participating in the research that purchasing and production strategies play equally significant roles in successful digitalisation, identification, and delivery.

Safe utilization evaluation of two typical traditional Chinese medicinal materials in Cd-contaminated soil based on the analysis of Cd transfer and AHP model

Due to the increasing scarcity of wild resources, most traditional Chinese medicinal materials (TCMMs) in the market are produced via artificial cultivation. The widespread pollution of cadmium (Cd) in soil limits the safe cultivation and use of TCMMs. This study investigated Cd accumulation, distribution, and the medicinal component content under simulated field conditions to clarify the differences in the Cd absorption, transfer and detoxification mechanisms of Polygonatum cyrtonema Hua and Bletilla striata, and provide the preliminary safe utilization conditions of TCMMs based on the analytic hierarchy process (AHP). The results showed that the Cd content of P. cyrtonema Hua was lower than the safety threshold under a high soil Cd concentration of 0.91 mg/kg (Cd-L), while B. striata was safe only at a low Cd concentration of 0.25 mg/kg (CK). Cd at 0.91 mg/kg induced hormesis affecting the net increase in biomass and medicinal component content for both TCMMs, while P. cyrtonema Hua showed better potential for safe utilization. Additionally, P. cyrtonema Hua had stronger resistance to Cd stress, exhibiting superior characteristics for synergistic absorption of Cd with mineral elements, transfer to nonmedical part and safer fixation forms in subcellular components. In contrast, B. striata showed insufficient Cd tolerance, and Cd was easily accumulated in organelles to inhibit plant growth. Our findings may attract more attention to the safe cultivation of TCMMs and provide insight into guidance for the safe utilization of slightly Cd-contaminated soil.

Establishment and application of rural domestic sewage treatment evaluation system based on analytic hierarchy process

AbstractAlthough numerous rural domestic sewage treatment facilities are constructed with the aim of improving the rural environment, the actual treatment effect is still difficult to evaluate. In this study, an evaluation system of rural domestic sewage treatment was established based on the analytic hierarchy process (AHP) model and a county in Zhejiang Province was selected as an example for empirical analysis. According to the results, planning issues have the greatest impact on rural sewage treatment, accounting for 56.8%, while equipment issues, personnel issues and management issues account for 27.3%, 9.7% and 6.2%, respectively. Also, the results demonstrated that terminal planning, location selection, treatment process selection and construction design should be paid attention to among the 11 secondary indicators. The establishment of the evaluation system clarifies the different influencing factors and weights during the operation of the completed facilities, which is conducive to the scientific and effective management of sewage treatment.

Delineation of groundwater potential zone using geospatial tools and analytical hierarchy process (AHP) in the state of Uttarakhand, India

Groundwater plays a vital role in global climate change and substantial human needs. However, the groundwater potential zone (GWPZ) delineation is essential for fulfilling livelihood needs. In recent years, studies based on geographic information systems (GIS) have acquired much attention in groundwater exploration. Thus, in order to determine the groundwater potential zone in the state of Uttarakhand, we employ a multi-criteria decision analysis (MCDA) based analytical hierarchy process (AHP) model with overlay weighted linear combination approach in this study. For groundwater potential zone demarcation, nine thematic layers such as geology, geomorphology, LULC, drainage density, slope, rainfall, soil, TWI, and curvature were created using remote sensing (RS) images and conventional data for a geographic information system (GIS). Furthermore, the weight of the parameters has been determined using AHP technique and overlay analysis was determined using GIS tools. A thematic map was categorized as “very poor,” “poor,” “moderate,” “good,” “very good,” and “excellent” in order to determine the groundwater potential zone. According to the results, the area covered by the 'very poor' categories is 187.43 km2 (0.16 %) followed by 'poor' 2109.66 km2 (3.99 %), 'moderate' 29024.06 km2 (54.78 %), 'good' 15151.13 km2 (28.67 %), 'very good' 6537.19 km2 (12.37 %), and 'excellent' 814.84 km2 (1.55 %) with the accuracy of 89.9 %. The 'very poor' and 'moderate' groundwater potential zones were observed as 0.16 % and 54.78 %, respectively, and the possibility for GPZ gradually increased from the northeast to the southwest. The findings of this study have implications for future research on sustainable groundwater use, basin management of agriculture, and the link between groundwater and climate change.

Multi-Criteria Decision Analysis on the Preference of Courier Service Providers with Analytic Hierarchy Process Model

The rising interest in E-commerce has increased the reliance on courier service providers in Malaysia. However, the logistical performances of the courier service providers in Malaysia still require improvement especially in the enhancement of information system adoption as the providers are suffering from bottlenecks in some hubs and centres which affect the satisfaction of clients and the reputation of the online retailers. Online retailers place high concern in the performances of the courier service providers as their services affect the sales and revenues of the online retailers. Therefore, the goal of this study is to propose a framework to determine and rank the factors that affect the selection of courier service providers among online retailers in Malaysia with Analytic Hierarchy Process (AHP) model. This study found that real time notification, cost and timeliness are the three most important factors of consideration while GDEX is the highly preferred courier service provider among the online retailers. This study can serve as a guide to the courier service providers to improve based on the top factors that influence the selection of their services.

Modelling on assessment of flood risk susceptibility at the Jia Bharali River basin in Eastern Himalayas by integrating multicollinearity tests and geospatial techniques

AbstractClimate change and anthropogenic factors have exacerbated flood risks in many regions across the globe, including the Himalayan foothill region in India. The Jia Bharali River basin, situated in this vulnerable area, frequently experiences high-magnitude floods, causing significant damage to the environment and local communities. Developing accurate and reliable flood susceptibility models is crucial for effective flood prevention, management, and adaptation strategies. In this study, we aimed to generate a comprehensive flood susceptibility zone model for the Jia Bharali catchment by integrating statistical methods with expert knowledge-based mathematical models. We applied four distinct models, including the Frequency Ratio model, Fuzzy Logic (FL) model, Multi-criteria Decision Making based Analytical Hierarchy Process model, and Fuzzy Analytical Hierarchy Process model, to evaluate the flood susceptibility of the basin. The results revealed that approximately one-third of the Jia Bharali basin area fell within moderate to very high flood-prone zones. In contrast, over 50% of the area was classified as low to very low flood-prone zones. The applied models demonstrated strong performance, with ROC-AUC scores exceeding 70% and MAE, MSE, and RMSE scores below 30%. FL and AHP were recommended for application among the models in areas with similar physiographic characteristics due to their exceptional performance and the training datasets. This study offers crucial insights for policymakers, regional administrative authorities, environmentalists, and engineers working in the Himalayan foothill region. By providing a robust flood susceptibility model, the research enhances flood prevention efforts and management, thereby serving as a vital climate change adaptation strategy for the Jia Bharali River basin and similar regions. The findings also have significant implications for disaster risk reduction and sustainable development in vulnerable areas, contributing to the global efforts towards achieving the United Nations' Sustainable Development Goals.

Sustainable Banking–A Quantitative Case in the Middle East Using MCDM and SEM Methods

Purpose: This study aims to explore the influence of green management standards on decision-making in the Lebanese banking sector.It seeks to uncover the dynamics of decision-making among key stakeholders as businesses navigate the challenge of aligning with environmentally conscious frameworks. Theoretical reference: The theoretical framework underpinning this research is rooted in the imperative for businesses to undergo a transformative shift towards sustainability, colloquially referred to as the "green shift." This shift is anticipated to be an unavoidable phenomenon, exerting pressure on businesses, including those in the Lebanese banking sector, to align their operations with environmentally sustainable practices. Method: Mixed methods Multi-criteria decision-making (MCDM) via the Analytic Hierarchy Process (AHP) and Structural equation modelling (SEM) via AMOS software were employed. Results and Conclusion: The results suggest internal stakeholders play a significant role in decision-making regarding green management in the banking sector. In contrast, external stakeholders rank second in their significance to green management in the banking industry. We note green products are significant to most top bank stakeholders. Implications of research: Researching the banking sector limits the possibility of generalizing the results to other types of business sectors as well as other geographical areas. The results could be improved by including additional stakeholders. The results help the Managers, CEOs, and strategic thinkers in the banking sector to target green managerial practices to the right stakeholders to maximize their green competitive advantage. Originality/value: This research investigated one of the rare studies in the banking sector where we could calculate the significance of the managerial parameters that govern the decision-making of bank stakeholders.

Optimization of engineering for the salt cavern oil storage (SCOS) during construction in China

Salt cavern oil storage (SCOS) is a mature underground energy storage method which is widely used in the EU and US. The construction of SCOS is a complex system that involves all kinds of engineering. In this paper, four typical problems of SCOS engineering are analyzed: economical evaluation, pipeline laying, stability analysis, and operation method. To solve these four typical problems, five mathematical optimization models (fuzzy comprehensive evaluation model, analytic hierarchy process model, grey prediction model, simulated annealing model, and systematic clustering model) are implemented. The key findings show that the investment weight of SCOS is 0.5834, which is the best investment storage method, an improved stability evaluation criterion of the SCOS is adopted based on evaluation score: 0.72–1.0 is stable; 0.54–0.72 is more stable; 0.23–0.54 is a little unstable; 0.01–0.23 is very unstable, and a new salt cavern sediment void oil storage (SVOS) operation method is proposed. The research has a significance for the implementation of large-scale SCOS in China.

Competency Model: A Study on the Cultivation of College Students’ Innovation and Entrepreneurship Ability

Objectives: This study was designed to analyze entrepreneurial competency and enhance college students' abilities in innovation and entrepreneurship. Methods: Ten relevant factors were summarized based on the interview records. Relevant data were collected through questionnaires and tested for reliability and validity. The effectiveness of the ten factors on entrepreneurial competency was tested using the regression analysis method. Then, an analytic hierarchy process model of entrepreneurial competency was established to calculate the relevant weights. Findings: The data collected from the survey questionnaire had sufficient reliability and validity. The ten relevant factors were effective in developing entrepreneurial competence. The weight distribution in the analytic hierarchy model indicated that entrepreneurial knowledge was most important, followed by entrepreneurial ability, and intrinsic potential was least significant. Novelty:The novelty of this article lies in not only verifying the effectiveness of relevant factors through regression analysis but also further analyzing the weight of these factors through an analytic hierarchy process. Doi: 10.28991/HIJ-2023-04-04-011 Full Text: PDF