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The rising concern for the accuracy of residential valuations in Nigeria has created the need for key stakeholders in the residential property markets in the study areas to know the level of accuracy of valuations in order to make rational residential property transactions, amongst other purposes.

A blend of descriptive and causal designs was adopted for the study. Data were collected via structured questionnaire administered to 179 estate surveying and valuation (ESV) firms in the study areas using census sampling technique. Analytical techniques such as median percentage error (PE), mean and relative importance index (RII) analysis were employed in the analysis of data collected for the study.

The study found that valuation accuracy is greater in the residential property market in Abuja than in Minna, with inappropriate valuation methodology as the most significant cause of valuation inaccuracy.

The practical implication of this study is that a reliable databank should be established for the property market to provide credible transaction data for valuers to conduct accurate valuations in these cities. Strict enforcement of national and international valuation standards by the regulatory authorities as well as retraining of valuers on appropriate application of valuation approaches and methods are the recommended corrective measures.

No study has comparatively examined the accuracy of valuations in two extremely different residential property markets in the country using actual valuation and transaction prices.

This chapter will identify readily accessible existing sources of public data. Thechallenges of using that data are considerable and require extensive time to ensure validity for reporting purposes. Summaries of data field selection and data wrangling requirements are presented in conjunction with data aggregation strategies.

Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in the case of calibrated items, determine the required test length given number of respondents.

Empirical results have been obtained on computerized or multistage adaptive implementation. Simulation studies and classroom/experimental results show that adaptive tests can measure test subjects’ ability to the same quality over half the test length compared to linear versions. Due to the complexity of the problem, the authors discuss a closed mathematical formula: the relationship between the length of the tests, the difficulty of solving the items, the number of respondents and the levels of ability.

The authors present a closed formula that provides a lower bound for the minimum test length in the case of adaptive tests. The authors also present example calculations using the formula, based on the assessment framework of some student assessments to show the similarity between the theoretical calculations and the empirical results.

With this formula, we can form a connection between theoretical and simulation results.

This paper aims to focus on the assessment of a domestic property's energy performance status by a domestic energy assessor (DEA), to ascertain the possible underlying reasons for variability in the results of Energy Performance Certificates (EPCs). By variability, the authors mean discrepancies in assessment between different DEAs on similar properties. This is important because the uses for the EPC have been extended beyond their original function as an asset rating system, to include themes encompassing building policy decisions, building performance and the distribution of incentives and grants. Consequently, inaccuracies in EPC reporting will have a greater impact than may have been the case at the outset.

A case study approach involving the conducting of semi-structured interviews with 20 practicing DEAs was carried out, with transcribed recordings of the interview material subjected to thematic analysis. This formed part of a wider mixed methods study.

The results identify a wide range of underlying reasons for variability driven by issues in both practice and process, including conflicts of interests, the EPC auditing process, the default inputting of missing data by RdSAP where information may not be available/discoverable by the DEA, the quality and perception of EPCs and DEA training and experience.

The sample size of 20 is by definition limiting, and it is possible that different results would have been obtained from a different sample. Although thematic saturation from the analysis of the responses on the key question of whether EPCs are considered variable does mitigate this. The respondents were all in possession of five years or more experience and of carrying out EPCs for different purposes. Less experienced DEAs may inevitably have responded to questions differently. The thematic analysis gives the researcher control over the presentation of the results, and it is noted that this creates a potential for bias. The researcher is immersed in the world of construction and property, with regular contact with DEAs and EPCs, which may influence the perspective of the results.

The research identifies risks to the accuracy of EPCs. To this end, and with the specific research findings in mind, this research may be of interest to construction professionals with respect to EPC practice and procurement, to the Accrediting Bodies who audit EPCs, to the creators of RdSAP with respect to automated EPC inputs, to academics either at face value or for use in further research and to policy makers who may wish to consider RdSAP data in future with qualifiers or margins of error, or may even look to review the EPC as the instrument of choice for some applications.

There is much literature analysing the shortcomings and nuances of RdSAP results, and the software model that generates the EPC, but only very limited literature extending the discussion about RdSAP to its operator: the DEA. At the time of writing, there is no literature focusing directly on the DEA and its role within the EPC production process. Their role is more important now, given the expanding use of EPCs, and increased reliance on EPC data.

Small and medium contractors (SMCs) play a significant role in socioeconomic development. Their strong links with other sectors of the economy have a multiplier effect on any country’s growth. However, the construction business, especially for SMCs, is not an easy business as several roadblocks affect their sustenance. This study aims to examine the factors affecting the sustainable competency of SMCs emerging from the business environment in which the Ethiopian construction industry (CI) operates.

A literature review was conducted to identify 39 factors arising from five core sources (i.e. government policies, regulatory frameworks, industry networks, competitive bidding culture and construction technology and innovation). A questionnaire survey was conducted to gather industry stakeholders’ perceptions of the identified factors, and the results were analyzed using descriptive statistics.

Findings indicate 37 significant factors affecting sustainable competency arising from five sources, and the top factors from their respective sources were unfavorable financial policy; unfavorable economic regulatory framework; lack of trust between parties in the industry; inability of SMCs to compete with bigger construction companies; and poor linkages between CI and research and development institutions. Furthermore, factor analysis identified 12 components, and the top ones were competition and uncertainties in the supply chain; unsuitable bidding environment; and ineffective industry networks.

The findings will contribute to the body of knowledge on the factors affecting the sustainable competency of SMCs in the Ethiopian CI. They also indicate priority areas of competitiveness improvement and have implications for decision-makers.

Usage of learning management systems (LMSs) has become widespread with the disruption of face-to-face educations after the COVID-19 pandemic. There are several software products, usually named as LMS to enable and support distance education. However, selection of a suitable LMS is a complex multiple criteria decision making (MCDM) problem that requires consideration of many criteria and inputs from different parties like students, academicians, education managers, etc. Usability evaluation of LMS is one of the critical steps in deciding which LMS system to be adapted. There are several studies related to usability evaluation of LMS in the literature, but utilization of MCDM methods and real life case studies are very rare. Based on this motivation, perceived usability evaluation of SAKAI-LMS that is in use at an academic department is performed by employing axiomatic design procedure (ADP). This paper aims to discuss the aforementioned issues.

ADP is considered as a suitable MCDM method for perceived usability evaluation as it allows an easy approach to data fusion and setting performance targets for decision makers. A questionnaire is developed to collect data from three types of system users about predetermined usability criteria and their importance. After detailed statistical analyses and weighting criteria via analytical hierarch process (AHP), ADP is carried out to evaluate usability of the LMS.

It is found that the proposed ADP based approach is easy to apply in practical circumstances and able to quantify perceived usability of the LMSs.

The proposed approach provides an easy and practical evaluation of perceived usability of the LMSs for decision makers who are responsible for the implementation of LMSs. The developed novel and practical MCDM-based perceived usability approach for LMS in this study has been verified through a real life case study at an academic department. Perceived usability results, therefore, reflects only the views of this focus group and are not generalizable.

First time in the literature, a comprehensive ADP based MCDM approach is proposed based on the analyses of the related literature and information gathered from the system users.

This paper aims to find out if there is a relationship between access to climate change information and student activism.

Exploratory study focused on the survey of 400 [n = 400] students from 10 universities in Spain from April to May 2022. A questionnaire with 19 questions was divided into blocks of knowledge, awareness, and action and bivariate analysis with a margin of error of ±5% and a confidence level of 95%.

The greater the degree of information received, the greater the activism of university students, who tend to use digital media and social networks to get informed. However, they perceive that the university generates little information and a low number of activities related to climate change. Students demand that universities implement informal, formal, and service-learning environmental education strategies on sustainable consumption.

Given the results of previous studies showing the variable “type of degree” does not show differences at the beginning and end of studies, it has not been considered in this research. Nevertheless, it would be convenient to introduce it in future investigations to confirm if this may have an impact on informational habits.

This paper urges universities to act as sources of environmental education, given the relationship between the information received and the pro-environmental attitudes of students.

The universities are powerful social actors that can shape public and political discourses for eco-social transition.

This research adds the variable access to information in studies on pro-environmental attitudes. Furthermore, this research provides data about student perceptions of the university, government, industry, and NGO climate actions.

There is an ever-increasing number of patients suffering from various forms of acute and chronic pain and getting treatment for such ailments is a basic human right. Opioid analgesics remain one way of managing and attending to such patients. However, due to the prevalence of opiophobia, many doctors avoid prescribing opioid-based medicines, even at the cost of patients suffering leading to a hindrance in providing optimal health care. Up till now, there has been no reliable and valid instrument to measure the severity of opiophobia in doctors. For this reason, the purpose of this study is to represent the construction of a precise and reliable instrument for measuring opiophobia along with its validation for doctors in Pakistan.

Interviews and theoretical knowledge relating to opiophobia were used as the basis for the purpose of generating an item pool. The generated item pool was evaluated by subject matter experts for content validity and inter-rater reliability, followed by Velicer’s minimum average partial method and maximum likelihood factor analysis for establishing the factorial structure of the scale. As opiophobia in doctors prevails the most and causes a lower ratio of prescription of opioid analgesics. The present sample selected for the study was that of n = 100 doctors (men = 50; women = 50) from various hospitals, treating patients with chronic pain, in Rawalpindi and Islamabad.

A two-factor structure was suggested by Velicer’s minimum average partial method and maximum likelihood factor analysis, which were labeled as fear of opioid analgesics and justified acceptance of opioids. The developed opiophobia questionnaire along with its subscales displayed appropriate levels of reliability α = 0.733, α = 0.760 and α = 0.725, respectively, suggesting the scale to be reliable.

Like any other study, this study also tried to address every essential aspect, but still lacked at some places which should be considered and catered for in future studies. In the first place the sample size was very limited which was due to the fact, the study was conducted during a pandemic and physically going for data collection was unavailable, thus leading to consequent sample size. It is recommended a correspondent study can be conducted with larger sample size, so they can get more reliable results with greater precision and power. Then, they will have the advantage of a small margin of error. The second limitation was the study involved only doctors as that was the main focus of the present study. However, other hospital staff such as nurses should also be incorporated to assess their level of opiophobia. The current scale suggests the severity of opiophobia with higher scores though no cutoff point has been suggested. Future studies should try and incorporate a cutoff point to assess the difference between doctors who have conventional levels of reservations against opioids and those suffering from opiophobia. Another limitation was that the present scale did not establish additional validities such as convergent and divergent validity. Future studies should collect data from a larger sample to establish these validities to further refine the scale.

This instrument can be immensely effective in identifying doctors who have concerns and fears about prescribing opioids to patients with chronic pain. The findings acquired on such a scale can help in developing appropriate academic and psychological interventions which can help such doctors to overcome their opiophobia. This can enable more doctors to prescribe appropriate medicine to their patients instead of letting them suffer from pain. Additionally, researchers can equally benefit from the instrument as it can enable them to investigate opiophobia with other possible variables.

Developing such a scale about the fear faced by doctors while treating patients would be very useful as it is not possible to take such fear when it comes to a patient’s life. This fear is also common among patients where they have a fear about the undesirable effects, addiction of drugs and fear of dying. Better awareness should be given to them which will be helpful for successful and less painful treatment in hospitals.

This scale is an original work with the aim of accessing opiophobia among doctors toward (chronic) patients with severe pain. There was a lot of research work that has been done on opiophobia in developed countries and few Pakistani researchers have also worked on opiophobia and its impact on pain management but still, no scale has been developed to measure the extent or tendency of opiophobia among doctors or patients. This scale can be used globally on both men and women doctors to access the tendency of opiophobia among them.

Experiments are the backbone of the development process of data-driven predictive models for scientific applications. The quality of the experiments directly impacts the model performance. Uncertainty inherently affects experiment measurements and is often missing in the available data sets due to its estimation cost. For similar reasons, experiments are very few compared to other data sources. Discarding experiments based on the missing uncertainty values would preclude the development of predictive models. Data profiling techniques are fundamental to assess data quality, but some data quality dimensions are challenging to evaluate without knowing the uncertainty. In this context, this paper aims to predict the missing uncertainty of the experiments.

This work presents a methodology to forecast the experiments’ missing uncertainty, given a data set and its ontological description. The approach is based on knowledge graph embeddings and leverages the task of link prediction over a knowledge graph representation of the experiments database. The validity of the methodology is first tested in multiple conditions using synthetic data and then applied to a large data set of experiments in the chemical kinetic domain as a case study.

The analysis results of different test case scenarios suggest that knowledge graph embedding can be used to predict the missing uncertainty of the experiments when there is a hidden relationship between the experiment metadata and the uncertainty values. The link prediction task is also resilient to random noise in the relationship. The knowledge graph embedding outperforms the baseline results if the uncertainty depends upon multiple metadata.

The employment of knowledge graph embedding to predict the missing experimental uncertainty is a novel alternative to the current and more costly techniques in the literature. Such contribution permits a better data quality profiling of scientific repositories and improves the development process of data-driven models based on scientific experiments.

This paper examined the factors influencing the participation of rice processors in short supply chains and the participation impact on the amount of rice processed, per capita expenditure of household and value of sales.

The Seemingly Unrelated Regression and Doubly Robust Augmented Inverse Probability Weighting Model (AIPW) were used to analyse the determinants of short supply chain participation and the impact of short supply.

From the results, the mean value of rice processed was GH₵18385 (US$ 3,069.28), with the minimum value being GH₵ 25 (US$ 4.17) and the maximum GH₵ 67200 (US$ 1,1218.70) per annum. Processed rice aroma and grade characteristics positively influence the value of processed rice sold via short supply chains as well as the expertise rate of the processor, Farmer-Based Organisation membership, and marketing information availability. Women rice processors' per capita expenditure, total sales value and the value of processed rice was positively influenced by the short supply chain participation.

Even though the sample size was appropriate, a larger sample size could further support the study's finding since a limited geographical area with predominant domestic rice processors was studied. Again, future studies should consider behavioural theories, such as the Theory of Planned Behaviour, amongst others, in understanding the reasons for the choices of short supply chains compared to other sales outlets.

Although there is a growing body of literature on rice, most of the studies focussed on the marketing outlet of rice producers, rice processing, constraints and opportunities faced by rice farmers and processors and an out-grower scheme involving rice processors amongst rice producers with none of these on the choice of short supply chains amongst women processors. Also, amongst all the studies on rice producers, none applied a theory; however, the Women in Development (WID) Theory was used to analyse the impact of the short supply chain on the impact on household per capita expenditure (poverty), the value of sales and amount of rice processed, a modest theoretical contribution of the paper to literature.