Traditional Appraisal Research Articles

Machine learning models in mass appraisal for property tax purposes: a systematic mapping study

The use of machine learning models in mass appraisal of properties for tax purposes has been extensively investigated, generating a growing volume of primary research. This study aims to provide an overview of the machine learning techniques used in this context and analyze their accuracy. We conducted a systematic mapping study to collect studies published in the last seven years that address machine learning methods in the mass appraisal of properties. The search protocols returned 332 studies, of which 22 were selected, highlighting the frequent use of Random Forest and Gradient Boosting models in the last three years. These models, especially Random Forest, have shown predictive superiority over traditional appraisal methods. The measurement of model performance varied among the studies, making it difficult to compare results. However, it was observed that the use of machine learning techniques improves accuracy in mass property appraisals. This article advances the field by summarizing the state of the art in the use of machine learning models for mass appraisal of properties for tax purposes, describing the main models applied, providing a map that classifies, compares, and evaluates the research, and suggesting a research agenda that identifies gaps and directs future studies.

Public archives determination of social memory in appraising local government records in South Africa

A hybrid version of macro-appraisal is used by South African public archivists when separating records of enduring value from ephemeral records. This appraisal function should occur immediately after the filing systems have been approved by the national and provincial archivists. However, in most cases, this function only occurs two years after the filing system has been approved. In the 1990s, the South African National Archives changed its traditional appraisal methodology from a Schellenberg approach to formulate a sound appraisal policy based on the macro-appraisal model. One of the key elements identified was the need to identify gaps in the written records that could be filled during the appraisal process. These gaps could be complemented by the collection of oral history. This study used qualitative data obtained through content analysis and literature to review the appraisal policy guidelines and approaches of the National Archives and the Gauteng Provincial Archives in relation to the process of appraisal, issuing of disposal authorities and capturing of oral history projects in relation to Gauteng local governments. This study used a case study design and specifically focused on the appraisal of Gauteng local government records. Interviews were held with officials of the National Archives and Gauteng Provincial Archives involved in the function of appraisal of public records. This study indicated that there were gaps in archival collections, which should be supplemented by the collection of oral history testimonies. The oral history testimonies collected from individuals and communities affected by socio-economic and socio-political events are not captured by the country’s public archivists. These narratives of post-apartheid South Africa are being lost and may not be captured by the national and provincial archives services. The key recommendation of this study is that there should be clear policy guidelines relating to the process of appraisal and transparency on how these processes are undertaken in South African public archives.

Investigating flood resilience perceptions and supporting collective decision-making through fuzzy cognitive mapping.

Improving flood resilience of communities requires a holistic understanding of risks and resilience options as well as the preferences and priorities of different stakeholders. Innovations in risk and resilience assessment have helped communities to identify gaps in their flood risk management strategy but selecting and implementing resilience solutions remains a big challenge for many decision-makers. In addition to traditional appraisals and cost-benefit assessments this also calls for a participatory process in which various stakeholders are encouraged to adopt a system-level approach in identifying interventions that can maximise a range of benefits and co-benefits. In this study, we investigate how a combination of modelling and measurement methods can help decision-makers with their flood resilience strategies. We apply a participatory system thinking approach combining Fuzzy Cognitive Mapping (FCM) with a flood resilience measurement framework called Flood Resilience Measurement for Communities (FRMC). We first investigate stakeholders' biases on flood resilience interventions, and then lead them through a system thinking exercise using FCM and FRMC to elicit mental models representing important aspects of flood resilience and their interrelation. These are then aggregated, representing the collective perceptions and knowledge of stakeholders, and used to identify the most beneficial resilience actions in terms of direct and indirect impacts on flood resilience. We apply this approach to the case of Lowestoft, a coastal town in England exposed to significant flood risk. Developed in close collaboration with the local authorities, the ambition is to support decision-making on flood resilience interventions. We find that this combination of methods enables system-level thinking and inclusive decision-making about flood resilience which can ultimately encourage transformative decisions on prioritization of actions and investments.

Construction and Empirical Study of Show Analysis Model of Enterprise Mankind Resource Management Based on Deep Learning

Owing to the rapid expend of the global economy and the increasingly fierce competition among enterprises, scientific and modern management has been gradually adopted in the transaction processing of enterprises. Especially for the show appraisal of enterprises, the traditional appraisal has a lot of subjective influence of managers, so the traditional show appraisal methods cannot meet the need for survival and expend of enterprises. The pressure of talent demand is increasing, which makes many enterprises pay more attention to whether their own mankind resource management system supports the company’s strategic spend and can win advantages in the competition of talent structure, organizational structure, and management process. Numerous foreign enterprises use mankind resource audit to achieve this goal, but at present, there is little practice in China that enterprise show evaluation is an important basic work and core content of mankind resource management and expend. Improving the effectiveness of enterprise show evaluation is of great significance to increase the core competitiveness of enterprises and promote the sustainable expend of enterprises. Therefore, this paper designs a model based on collaborative filtering algorithm to analyze the show of mankind resource management of enterprises and has achieved good results. Compared with the original algorithm, the model designed in this paper has a 65.4% improvement in algorithm, which will greatly simplify the calculation process and improve the model processing efficiency. The numerical results show that there is an inevitable linear correlation between mankind resource management and enterprise show. This index can reflect that the accuracy of the model has been enhanced by 74.3%.

Does Automated Collateral Evaluation Lower Mortgage Credit Risk Relative to Home Appraisal Valuations?

Automated valuation models (AVMs) are increasingly being used as a substitute for home appraisals in mortgage origination. This article examines whether there are differences in the credit risk of mortgages originated using AVMs relative to traditional appraisals. This question is explored through modeling the conditional default rates of loans originated through Freddie Mac’s automated collateral evaluation (ACE) program relative to those originated with appraisals. We show that ACE loans have about a 9.6% lower default risk in comparison to otherwise similar loans originated with appraisals. This superior default performance can be explained by the ACE decision logic employing data beyond that found in a traditional appraisal and the more efficient utilization of available information through statistical modeling. These findings are limited to Freddie Mac’s use of its AVM, the Home Value Explorer®, and the algorithmic decision logic in the ACE program.

Employee Performance Assessment of PT.Satria Manunggal Petrolindo Using 360-Degree Feedback Method

PT Satria Manunggal Petrolindo is one of the partners in PT. Pertamina is engaged in the business of trading fuel oil. In running its business, PT Satria Manunggal Petrolindo has employees who are dedicated to their work. Employee performance at this company is one of the important aspects that need to be assessed related to efforts to improve performance and quality in achieving the company's business goals and objectives, where so far the assessment of employees is still using traditional appraisal methods. This assessment method causes some employees to feel uncomfortable and unmotivated at work so that employee productivity can decrease. With these problems, the authors conducted research on the performance of employees at PT Satria Manunggal Petrolindo. The method that will be used in measuring employee performance appraisal in the company is the 360-degree feedback method. This method uses comprehensive feedback from all levels around employees to assess performance according to work behavior which consists of five assessment components, namely: Self Appraisal, Manager Review, Peer Review, Subordinates Appraising Manager (SAM) and Customer/Client Review. The results of the research and evaluation of the problem in this study were the use of the 360-degree feedback method in evaluating employee performance. It is expected to be able to overcome the problems of employee performance appraisal so as to increase the comfort and work motivation of PT.Satria Manunggal Petrolindo which will have an impact on increasing the achievement of the company's business goals.

Research on Enterprise Human Resource Performance Management Innovation in the Era of Big Data

With the rapid development of Internet information technology, big data has become an important feature of today's era. Under the background of the big data era, the popularity of the Internet, the development of artificial intelligence and the application of information technology help to tap the potential of employees, optimize the enterprise organizational structure and realize the informatization and systematization of enterprise human resource performance management, so as to improve the work efficiency of enterprise human resource performance management and help enterprises achieve strategic objectives. The traditional human resource performance appraisal methods have some problems, such as strong subjectivity, low intelligence, insufficient application of performance management achievements and so on. Based on the era background of big data, this paper explores the innovation path, influence mode and application methods of enterprise human resource performance management, so as to further promote the development of research in relevant fields and provide reference for the practical application of enterprise management in improving evaluation methods, designing evaluation system, optimizing the key links and so on.

From the Chair

From the Chair

Reinventing Performance Management

Performance appraisals have traditionally been conducted annually or semi-annually. Recently, many companies are transitioning to ongoing feedback and coaching, either in addition to periodic appraisals, or lieu of them. There have also been calls for completely reinventing performance management systems, as the result of an abundance of research that indicates performance processes are over-engineered and time-consuming, and they tend to demotivate employees while hindering candid and honest conversations. This paper examines the common problems with attribution error and rater bias in traditional performance appraisal systems. Five mini-case studies are then presented by exploring how five large companies (Netflix, Adobe, Deloitte, IBM, GE), have reinvented the way in which performance management is implemented. The paper examines why these companies moved away from traditional performance appraisal and what processes replaced it. The paper also identifies emerging trends that will impact the future of performance management and offers suggestions for the road ahead.

Participatory multi-criteria analysis methods: Comprehensive, inclusive, transparent and user-friendly? An application to the case of the London Gateway Port

The topic of how major transport projects should be assessed continues to generate disputes amongst academics, infrastructure specialists, investors and governments alike. Over the past decades, an increasing number of scholars have started to regard participatory multi-criteria analysis (MCA) as an approach capable of producing more comprehensive, transparent and democratic assessments than traditional appraisal techniques. However, whereas a number of participatory MCA methods have been devised, the large majority of them seem to have enjoyed limited practical application and there are very few studies examining their effectiveness. In order to assess the presumed benefits and the potential drawbacks of such methods, this paper considers the case of the London Gateway Port and compares the actual planning and decision-making process of this port development programme with the results of a multi-actor multi-criteria appraisal exercise, involving several project stakeholders and experts. As a result of this analysis, the paper contends that the contribution that participatory MCA procedures can potentially provide to the improvement of decision-making for large-scale transport infrastructure seems limited at best.

Quantitative Appraisal Model for Infrastructure Stock Assets of Port City Based on GMM

Han, B. and Yu, J., 2020. Quantitative appraisal model for infrastructure stock assets of port city based on GMM. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 6–10. Coconut Creek (Florida), ISSN 0749-0208.The traditional quantitative appraisal model for infrastructure stock assets of port city has large appraisal error. To solve this problem, a quantitative appraisal model for infrastructure stock assets of port city based on GMM method is designed. First of all, the paper puts forward the main forms, basic principles, appraisal elements, basic assumptions, appraisal purposes and principles for quantitative appraisal of the infrastructure stock assets of port cities, then determines the spatial relevance of the infrastructure stock, and finally establishes the quantitative appraisal index system for the infrastructure stock assets of port cities, so as to complete the quantitative appraisal of the infrastructure stock assets of port cities based on GMM method. The experimental results show that the quantitative appraisal model based on GMM is less error than that of the traditional model.

Comparison between traditional project appraisal methods and uncertainty analysis applied to mining planning

Abstract Long-term mining planning is a complex process which involves a large number of variables and uncertainties. Traditional discount cash flow (DCF) is usually used in the evaluation of mining projects. DCF includes net present value (NPV), internal rate of return (IRR), and profitability index (PI). A sensitivity analysis is usually carried out to evaluate the impact of the main variables on the project. Another way to measure uncertainties is through the Monte Carlo simulation (MCS). The objective of this study is to evaluate and compare the DCF methods and measure uncertainties through sensitivity analysis and MCS in the evaluation of mine sequencing. A case study of a phosphate mine project was used to chart the comparative study. In the results, NPV and uncertainty analysis through MCS were more consistent.

A New Appraisal Model of Second-Hand Housing Prices in China’s First-Tier Cities Based on Machine Learning Algorithms

The accurate appraisal of second-hand housing prices plays an important role in second-hand housing transactions, mortgages and risk assessment. Machine learning technology, gradually applied to finance and economics, can also be used to upgrade the traditional appraisal methods of second-hand housing. A large number of appraisal indicators and price data on second-hand housing in Beijing, Shanghai, Guangzhou and Shenzhen, four first-tier cities in China, can be obtained by using crawler technology. Then, the geographical location information of second-hand housing can be visualized by GIS technology, and the descriptive text of second-hand housing can be processed by natural language processing. Finally, combined with other numerical and classification indicators, the second-hand housing appraisal model based on a two-tier stacking framework is constructed by using random forest, adaptive boosting, gradient boosting decision tree, light gradient boosting machine and extreme gradient boosting as base models and back propagation neural network as the meta-model. The result of model training shows that the machine learning models improve the accuracy significantly compared to linear multiple regression and spatial econometric models, and the performance of the stacking model is better than that of standalone machine learning models.

Innovative non-invasive assessment of structures

This paper provides details for a new and innovative methodology for the understanding, appraisal and testing of existing building structures. Assessment of structures requires knowledge and experience, combined with a practical understanding of how structures work. When existing structures need to be inspected and assessed, the structural engineer or building surveyor is often expected to have X-ray eyes. Lacking such a gift, and despite what clients may assume, they draw instead on knowledge and experience to make value judgments in many situations, with appropriate margins of safety and consideration of appropriate risk incorporated along the way. Codes of practice and British Standards provide a useful reference to assist with this process, but often sound judgment needs to underpin decisions made. This paper introduces the technique of non-invasive dynamic testing for assessing existing structures and provides examples of its use. The technique can be used on a range of applications to provide an understanding of how existing structures are actually behaving, rather than using more traditional conservative assessments that rely on a range of assumptions made on material properties, member interaction and support conditions. As a non-invasive option to traditional appraisal techniques it has wide ranging benefits in the heritage sector, but additionally provides significant economic benefits compared to existing solutions.

Fuzzy Driven Decision Support System for Enhanced Employee Performance Appraisal

Employee performance appraisal is often considered a core management task in most standard organizations because it could potentially inspire an employee towards the pursuit of organizational goals and objectives. Meanwhile, issues such as delay in appraisal processes, inevitable human error, and emotional status of the appraiser, are common with the traditional appraisal methods. Hence, this research proposes a fuzzy decision-support system based on Henri Fayol's 14 principles of management for the appraisal of employees' performance. A questionnaire consisting of 44 structured questions was designed based on these principles and administered to the employees of Babcock University, Ilisan-Remo, Ogun State, Nigeria. Fuzzy inference system that incorporates Mamdani computational technique was built based on the feedback extracted from the questionnaires, and used for appraising the employee performance. Experimental results show that the proposed system could predict the appraisal status of an employee with 75% accuracy in comparison to the conventional appraisal method.

Performance Appraisal Systems in Hiram Hospital and its Relationship with Employees’ Performance: Empirical Study

Purpose: This study aims to investigate the relationship between different performance appraisal methods and employees’ performance in a private hospital in South Lebanon. Three main appraisal methods were selected for this study including traditional appraisal, self-appraisal and customer appraisal methods. In addition, the employees’ performance was measured at different levels including task, adaptive and contextual performance.
 Design: Based on a quantitative approach and using self-administered questionnaires, primary data was collected randomly from 125 employees of the target hospital.
 Findings: The results obtained showed that employees are generally performing in an adequate level and they are pleased with the current applied performance appraisal systems at this hospital and especially at the level of customer appraisal methods.
 Originality: This study showed how private hospital in Lebanon use performance appraisal systems in managing their human resources through measuring employees’ performance, motivating them and most commonly, making critical administrative decisions related to training and development or even rewarding and coercive actions.
 Future suggestions: Future studies are recommended to expand the research geographically and comprise variety of hospitals in terms of size or type. Also, studying different performance appraisal systems would enrich the literature especially at the empirical level.

Impact of glass ceiling on women career development in non-state banking sector in Colombo

Despite banking industry having more female employees than males, women are still underrepresented in management and senior management levels. This study focused on the effect of glass ceiling factors (GCFs) on women’s career development in non-state banking industry in the Colombo district. Five glass ceiling factors, namely individual, childcare and spouse care, elder care and housework, organizational and cultural factors were considered. The study was guided by three objectives, namely to identify the current level of women’s career development, assess the existing level of GCFs and identify the effect of GCFs on career development of female executives. All female executives employed in the Head Offices of four non-state, licensed commercial banks in Colombo, Sri Lanka were selected for the study. This study revealed significant positive and negative effects of individual factors and organizational factors, respectively on career development of women. Other three factors, namely child care and spouse care, elder care and housework and cultural factors did not show significant relationship on women career development. This study recommends developing self-efficacy by encouraging management to use social modelling, verbal encouragement and constructive feedback. Furthermore, conducting developmental performance appraisals, instead of traditional performance appraisals to increase their personal growth initiatives is suggested.

The Challenges of the IS/IT Projects in the Healthcare Sector

Essentially, the purpose of investment in information systems and information technology (IS/IT) is to improve the operational efficiency of the organizations, reducing costs and improving levels of quality. Thus, many traditional appraisal techniques are used to evaluate tangible benefits, which are based on direct project costs. Since the 1980s, IS/IT has positioned itself as a strategic tool that through flexibility and innovative ways can produce superior performance. The health sector has sought to improve its effectiveness and efficiency by adopting IS/IT solutions to increase the quality of services, namely patient safety, organizational efficiency, and end-user satisfaction. Hospitals are complex organizations, and this complexity magnifies the opportunity for inevitable human errors. A poorly integrated system can decrease operational efficiency and reduce the quality of healthcare services. The issue remains controversial, as evidenced by several articles. The authors noticed that emergent technologies may offer opportunities to those who can exploit them effectively.

Talking about the Employee Performance Appraisal System

With the development of economic globalization and integration, enterprises should survive and develop in the fierce market competition environment, need to enhance their own competitive ability, and human resources is the fundamental and key of enterprise competitiveness. In order to achieve the objectives of enterprise organization, we need to establish a sound performance appraisal system for employees and departments, and with effective incentive mechanism to fully mobilize the enthusiasm of the staff and create potential to continuously improve the performance level. The traditional staff performance appraisal method cannot meet the needs of modern enterprises, the establishment of a basic sound, with enterprise characteristics, to a full range of staff performance appraisal method as the core of the performance management system, from different levels of personnel to collect evaluation information, multi-angle, the whole perspective of the staff to conduct a comprehensive performance appraisal, comprehensively enhance the level of human resources management. This paper mainly elaborates how the enterprises implement the performance appraisal, the performance to achieve the effect and properly handle the enterprise and the staff assessment and assessment of the relationship between the performance appraisal for the enterprise staff put forward some ideas and suggestions.

Implication of Class-Based Assessment on Teachers: A Case Study

In Fiji, assessment has always been guided by curriculum through examination and tests which merely enclosed students’ aptitude of recalling conception skills. Supplementary categories of skills like application, analysis, synthesis and evaluation are barely incorporated in the traditional appraisal. Some of the indispensable qualities are not included in the customary assessment system. This makes learners rely extremely on their memorization skill leading them to become helpless, deficient required excellence to contribute fruitfully to the society. The government of Fiji has a sensible vision for the stipulation of its education organization and has impartially arbitrated the Class-Based Assessment (CBA) aspirant for learners’ holistic development. CBA has been implemented in secondary schools in 2009, through a pilot project. This research reveals the current status of the implemented assessment scheme through a study of a group of teachers of secondary schools and CBA resource personnel’s from the Ministry of Education. It discusses the issues emerging from the arguments of the scholars regarding CBA and its potentiality in Fiji. Despite the popularity and wide acceptance of Class-Based assessment in the western countries and Fiji itself it has often been criticized for several reasons, most of them related to the utilitarian perspective and related ethical considerations. CBA seems to be very difficult to maintain within the stipulated time of teaching. It is difficult for the teachers to switch from summative assessment to formative one as it seems an extra assessment together with a final examination.