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Being an efficient mechanism for the value of money, public–private partnership (PPP) is one of the most prominent approaches for infrastructure construction. Hence, many controversies about the performance effectiveness of these delivery systems have been debated. This research aims to develop a novel performance management perspective by revealing the causal effect of key performance indicators (KPIs) on PPP infrastructures.

The literature review was used in this study to extract the PPPs KPIs. Experts’ judgment and interviews, as well as questionnaires, were designed to obtain data. Copula Bayesian network (CBN) has been selected to achieve the research purpose. CBN is one of the most potent tools in statistics for analyzing the causal relationship of different elements and considering their quantitive impact on each other. By utilizing this technique and using Python as one of the best programming languages, this research used machine learning methods, SHAP and XGBoost, to optimize the network.

The sensitivity analysis of the KPIs verified the causation importance in PPPs performance management. This study determined the causal structure of KPIs in PPP projects, assessed each indicator’s priority to performance, and found 7 of them as a critical cluster to optimize the network. These KPIs include innovation for financing, feasibility study, macro-environment impact, appropriate financing option, risk identification, allocation, sharing, and transfer, finance infrastructure, and compliance with the legal and regulatory framework.

Identifying the most scenic indicators helps the private sector to allocate the limited resources more rationally and concentrate on the most influential parts of the project. It also provides the KPIs’ critical cluster that should be controlled and monitored closely by PPP project managers. Additionally, the public sector can evaluate the performance of the private sector more accurately. Finally, this research provides a comprehensive causal insight into the PPPs’ performance management that can be used to develop management systems in future research.

For the first time, this research proposes a model to determine the causal structure of KPIs in PPPs and indicate the importance of this insight. The developed innovative model identifies the KPIs’ behavior and takes a non-linear approach based on CBN and machine learning methods while providing valuable information for construction and performance managers to allocate resources more efficiently.

The purpose of this study is to evaluate the knowledge and practices of selected group of Polish children in early school age in terms of issues such as: (1) the principles of food preparation, storage and eating meals; (2) personal hygiene; and (3) basic information about microorganisms.

The auditorium survey method was used. The questionnaire consisted of 15 questions related to the children's knowledge of personal hygiene, the principles of food preparation and storage and the physiology of microorganisms and 13 questions related to the children's personal and food hygiene practice. In total, 169 questionnaires were collected. The study group of children had incomplete knowledge and often reported inappropriate food hygiene practices.

The subjects of food preparation and storage and knowledge of microbes were particular problem areas. By contrast, aspects related to handwashing, the appropriate practices while coughing or sneezing and washing fruit before consumption were positively evaluated. The children demonstrated the most knowledge in the field of personal hygiene. However, a very low percentage of correct answers was noted for the question about handwashing at school. None of the 13 questions related to this practice received more than 90% correct answers. The boys and girls demonstrated a comparable level of knowledge and practice in the area of food safety. It was showed that the place of school influenced answers to a greater extent compared to gender.

The results of the study play an important role in the prevention of food poisoning and are useful for the teachers, staff of training institutions and parents. They can also inspire institutions in countries with a high incidence of food poisoning to search for the causes in the inappropriate hygienic practices of young children.

In the paper we provide new evidence on the predictability of Scandinavian stock returns, when utilizing the determinants of global capital asset pricing. Three factors are extracted by principal components factor analysis. The VARIMAX‐rotated factor loadings matrix clearly suggests the presence of geographically distinguished returns generating factors: Europe, Asia and America. The corresponding factor price series are used as driving forces for the Finnish and Swedish market returns. The results indicate that the predictability of Scandinavian stock returns is significantly improved by the world factors.

This study aims to validate the English version of a WHO-adapted questionnaire: Zika infection awareness/knowledge questionnaire using a unique dual-approach validation model.

A cross-sectional pilot study of 30 adult respondents in Malaysia completed the self-administered questionnaire on knowledge and perception to Zika infection. Construct validity was assessed by exploratory factor analysis (EFA) of SPSS and Rasch partial credit. Reliability is tested using pKR20 and Cronbach’s alpha.

Knowledge construct was unidimensional, good model fit, easy to endorse and well discriminative. Five-rating Likert scale for perception domain was appropriate. Knowledge domain should be separated into 6 level of difficulties. Perception domain should remain as one construct. Knowledge domain was highly reliability (pKR20 = 0.96), perception domain was fairly reliable (Cronbach’s alpha = 0.641). Respondent's ability to answer knowledge domain and perception domain were separated into 3 and 4 levels.

Small sample size may affect factor analysis.

The questionnaire has good psychometric properties to measure the knowledge and perception of Zika infection among Malaysian community.

The questionnaire helped to gauge knowledge and perception of the general community in Malaysia to aid preparation of health education tool for Zika infection.

This paper validated questionnaire with two biostatistical software programs in bidirectional approach – items difficulty and respondents' ability – is the first field test of WHO questionnaire among general population in Southeast Asia.

In recent years, there has been considerable interest in corporate governance literature as a result of massive corporate scandals. In today’s world, almost all companies are exposed to the danger of fraud. Much work on the business risk of corporate fraud has been carried out; however, researchers still have tough discussions on the most effective methods to adopt to tackle fraud. In accordance with previous studies, it is possible to say that companies which obey the corporate governance codes to the letter can minimize the risk of fraud. The importance of this chapter lies in that it helps to explain the evidence that although the deterrent measures company can undertake may well, to a certain extent, work out the problem of fraud, they are way far from eliminating corporate crimes in establishing “corporate governance.” The latter is the key term that defines the public responsibility of corporates binding themselves to the rule of law. Corporate governance has been discussed as one of the effective ways of calling the attention of large firms to social problems and urging them to take necessary actions. The reason that companies cannot eliminate fraud is strictly linked to the evidences of critical organization studies that question the epistemic assumptions of mainstream strand of the same field. Some studies show that the subject is not rational decision-making, neither does it follow the interest, nor is it a pure homo economicus so that rationality is effective in deterring corporate frauds to a certain extent.

The profession of judicial advisory is a profession with a larger scope, which creates solutions for legal problems by harmoniously blending principles, theories, and standards that relate to many areas of expertise such as accounting, auditing, and law. The legists need expert information on the matters of accounting, finance, and taxation regarding the files that they handle. In such cases, experts who perform the profession of judicial advisory provide their consultancy services to the legists before and during the cases.

The purpose of this study is to create awareness regarding the profession of judicial advisory and put forward the prospects of this profession in Turkey. The study includes four provinces located in the Eastern Black Sea Region (Trabzon, Rize, Ordu, and Giresun). There are a total of 1,339 lawyers who are registered to the bar associations of the indicated provinces; out of them, 600 lawyers have been communicated, but a questionnaire was conducted on 354 lawyers by employing face-to-face interviews. The data obtained from the questionnaires have been subjected to difference in means (unpaired t-test) and descriptive statistical analyses by using the statistical packet software of SPSS 10.0.

In the consequence of the conducted analyses, it has been determined that the lawyers thought that the members of the profession of accounting working as experts were inadequate. In the event of establishing judicial advisory institution besides the institution of expertise, it is believed that a more beneficial system would be created. It is seen that this thought has not changed among the lawyers in terms of different characteristics except level of education. Additionally, it has been determined that the level of awareness of the lawyers regarding the profession of judicial advisory was insufficient.

This study aims to investigate the perceptions of Iranian English teachers about their teaching efficiency through a specific practicum course, namely, language teaching methodology. Drawing on a marketing education perspective, the researchers sought to measure the service quality offered in universities by examining teachers’ satisfaction with the curriculum.

Using quantitative gap analysis, the study evaluated the knowledge and skills of teachers in their preservice education regarding the perceived importance of knowledge and skills required in practice. The study involved 120 English as a foreign language teachers holding a BA degree from two universities in Iran, each with two to four years of teaching experience in the private sector. Data were collected using a 40-item semantic differential Likert scale developed by the researchers. The scale incorporated two components that assessed teachers’ perceived importance of knowledge and skills and their preservice educational preparation.

The findings revealed that most participants were overprepared in various items. However, there were some gaps in content knowledge and skills. Reasons for these gaps mainly included having adequate experience of and/or familiarity with course content, having completed relevant courses beforehand and imitating role model teachers. Teachers’ underpreparation was attributed to their lack of preparation in some specific subjects due to limited skill, practice, motivation, experience and familiarity with that content area.

This study explores the perceived knowledge and skills of Iranian English teachers and provides empirical insights into higher education service quality and customer satisfaction.

The study is an attempt to explore much talked but less understood issue of “blockchain in logistics industry” in modern perspective. The customers' acceptance of blockchain technology in logistics and supply chain is tested through “Technology Acceptance Model” by using attitude, perceived usefulness (PU), perceived ease of use (PEOU), behavioral intention and use behavior.

Data has been collected through online and offline medium, where active 240 responses have been collected finally using convenience sampling. Confirmatory factor analysis with structural equation modeling (SEM) was carried out for data analysis.

The customers' acceptance of blockchain technology in logistics and supply chain is tested through “Technology Acceptance Model.” The findings reveal model fit where PEOU, PU and attitude are the major constructs of the model to realize the substantial gains in logistics process efficiency.

Convenience sampling has been considered for the study to collect the data of online users of various technology applications for tracking and shipment detail, whereas a more specified method sampling can be considered for the future research. The study has been conducted in the Indian context, which has been considered as the limitation pertaining to generalization across countries and industries.

The findings of this study will be helpful for market practitioners to build transparency between customers and industry to overcome the frictions in logistics. Blockchain will help in monitoring the performance history and previous commitments of logistics professionals resulting in selecting a responsible logistics solution provider. Access to critical data by the authorized member of the supply chain will reduce unsubstantiated disputes.

Blockchain technology will be available to everyone on the network. This will bring transparency and help logistics professionals such as carriers, shippers and brokers to detect early frauds and prevent thefts. It will increase customer trust toward any financial transaction for tracking the ownership of titles.

Blockchain technology is envisioned to be a technology that could be a game-changer for decentralizing infrastructure, introducing transparency and building trust in the supply chain. The current study is a novel addition to the literature where blockchain technology enables the indisputable storage of verified data that was previously kept in safeguarded silos.

Libraries need to develop information processing systems for evaluation, budgeting, planning, and operations. Electronic spreadsheets lend themselves to a variety of applications, but are time‐consuming to create. A model template and macros that can be used in many different types of library data analysis have been developed here. The procedures demonstrated here can build an essential set of tools for meeting fundamental goals of administrative efficiency, effective use of library resources, staff motivation, and rational policy making.