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The study seeks to identify and document definitional challenges that hamper the delineation of the scope of real estate as a discipline and as an industry. Through literature review the article distils the perception of body of knowledge (BOK) of real estate within the academia. Two main issues are flagged up: the problem of undefined BOK and the collegiate dilemma. Later the study looks at the standard economic classification documents to capture the occupational domains of real estate professionals or real estate activities. These steps are necessary to help define an alternative academic, practical and social meaning of real estate that is sufficient and precise.

The study uses literature review and, as primary method, qualitative document analysis (QDA). The study has made a special appeal for the application of qualitative strategy in real estate research other than following the methodological orthodoxy of quantitative causal research designs. Further, it has argued for the recognition of QDA as a legitimate research method in the context of real estate studies. Consequently, the study performed QDA procedures on international economic classification standards.

From literature review and QDA, the study identified five definitional problems in the meanings or understandings of real estate: undefined body of knowledge, collegiate dilemma, inadequate classification of real estate occupations, inadequate industry classification and inadequate economic sector positioning. These are aspects that lead to misconceptions of the true boundary of knowledge in society and in the academia. The paper offers clarity and insights for the redrawing of these boundaries to give real estate its rightful place in the academia and in the real world.

The article follows up on the academic and social misconceptions on the BOK of real estate as a discipline and an economic activity domain to identify the contribution of real estate to the welfare of mankind. Ontology or the organization of academic or social knowledge is used to map out or catalogue real estate against competing domains and to show that the role of real estate is grossly understated and misunderstood. From the findings, the study makes recommendations to university curriculum developers, and international organizations like ILO, and UN-DESA to revise their conceptions of real estate to give the discipline its rightful position in society.

The purpose of this paper is to determine the classic (static) and dynamic sensory profile of different bottled mineral water samples, and to evaluate the consumer’s liking of the products.

Classic quantitative descriptive analysis (QDA) and temporal dominance of sensations (TDS) were applied to four brands of bottled mineral water and the liking of the products was evaluated by consumers.

The dissolved mineral concentration is highly correlated to the liking and influences the sensory profile of the samples in a substantial way. The higher the mineral content, the lowest is the liking. Refreshing, residual plastic taste, musty, metallic taste, medicine taste and viscosity were relevant attributes to the samples differentiation through the static evaluation, while refreshing and viscosity were dominant in the dynamic monitoring. Some information might have been lost by the nature of the TDS method, based on dominance concept. Sweet taste contributed positively and musty taste negatively to the acceptance.

This paper demonstrated that TDS can be used as a complementary tool to the QDA, contributing to a deeper comprehension of the differences among samples, even in products with low differences, such as bottled mineral water.

People are increasingly concerned about food and health and seek for functional and sugar-free products. However, there are technological challenges when adding functional components and substituting sugar in foods. Thus, the purpose of this paper is to evaluate the influence of packaging and storage time on the sensory profile of functional diet guava preserve added with prebiotics, supporting the development of functional and sugar-free products and contributing to the product variety in the market.

A two-factor full factorial design was conducted in triplications that evaluated transparent and opaque packaging vs storage time (six months). The products were stored in packages with different light permeability (transparent and opaque). Quantitative descriptive analysis (QDA) and acceptance tests were performed.

The packaging material did not affect the sensory changes of functional diet guava preserve during the six months of storage. QDA test showed that from three months of storage the original characteristics of the product were lost and a slight decrease in overall acceptance was observed after four and six months. However, during the six months the products had good acceptance; consequently, it was not possible to establish their rejection before this period.

More detailed studies regarding a longer storage period, including the physical and chemical measurements must be done to clarify other points about the influence of packaging and storage time on the sensory profile of functional diet guava preserve added with prebiotics. Therefore, researchers are encouraged to test the proposed propositions further.

The development of a functional and sugar-free preserve is a good alternative to provide a product that meets the actual consumer desires and adds value to the product. However, there are technological challenges when adding functional components and substituting sugar in foods. Thus, this study provides important information for the development of sugar-free and functional products, and to prolong their shelf life.

There are few studies with respect to the sensory aspects during the storage of functional preserves. Thus, this work will aid future studies, supporting the development of functional and sugar-free products and contributing to the product variety in the market.

Purpose: This chapter aims to examine machine learning (ML) models for predicting credit card fraud (CCF).

Need for the study: With the advance of technology, the world is increasingly relying on credit cards rather than cash in daily life. This creates a slew of new opportunities for fraudulent individuals to abuse these cards. As of December 2020, global card losses reached $28.65billion, up 2.9% from $27.85 billion in 2018, according to the Nilson 2019 research. To safeguard the safety of credit card users, the credit card issuer should include a service that protects customers from potential risks. CCF has become a severe threat as internet buying has grown. To this goal, various studies in the field of automatic and real-time fraud detection are required. Due to their advantageous properties, the most recent ones employ a variety of ML algorithms and techniques to construct a well-fitting model to detect fraudulent transactions. When it comes to recognising credit card risk is huge and high-dimensional data, feature selection (FS) is critical for improving classification accuracy and fraud detection.

Methodology/design/approach: The objectives of this chapter are to construct a new model for credit card fraud detection (CCFD) based on principal component analysis (PCA) for FS and using supervised ML techniques such as K-nearest neighbour (KNN), ridge classifier, gradient boosting, quadratic discriminant analysis, AdaBoost, and random forest for classification of fraudulent and legitimate transactions. When compared to earlier experiments, the suggested approach demonstrates a high capacity for detecting fraudulent transactions. To be more precise, our model’s resilience is constructed by integrating the power of PCA for determining the most useful predictive features. The experimental analysis was performed on German credit card and Taiwan credit card data sets.

Findings: The experimental findings revealed that the KNN achieved an accuracy of 96.29%, recall of 100%, and precision of 96.29%, which is the best performing model on the German data set. While the ridge classifier was the best performing model on Taiwan Credit data with an accuracy of 81.75%, recall of 34.89, and precision of 66.61%.

Practical implications: The poor performance of the models on the Taiwan data revealed that it is an imbalanced credit card data set. The comparison of our proposed models with state-of-the-art credit card ML models showed that our results were competitive.

Performance appraisal (PA) is an organizational practice whose ultimate goal is to improve employee performance. This goal can be achieved using two approaches: the administrative approach, which emphasizes materialistic incentives and rewards excellent performers, and the developmental approach, which focuses on employee personal and professional development. The literature points out that organizations cannot utilize both approaches at the same time, but the reason for this is vague. Therefore, the research purpose is to bridge this gap by exploring the basic assumptions behind the administrative and developmental PA approaches as part of the hidden layers of organizational culture.

A qualitative document analysis (QDA) was used to analyze 124 Israeli organizations' PA forms and employee reports.

The organization's PA approaches were diagnosed as a first step in revealing the reason for the inability to use both approaches simultaneously. In the next step, it was revealed that organizational culture assumptions are the reason for the contradiction of the PA approaches. Eventually, McGregor's theory X is the basic assumption behind the administrative approach, and theory Y is the assumption behind the developmental approach. Since these two approaches contradict each other, it explains the difficulty of using both approaches simultaneously.

This study dives into the hidden levels of organizational culture and attempts to bridge a long-standing but still current research gap, as well as extend and refine organizational culture and performance appraisal theories.

The purpose of this study is to assess how intergovernmental panel on climate change’s (IPCC’s) sixth assessment report of Working Group I (WGI), a Summary for Policymakers (SPM), has evaluated the current climate change situation. The author uses the qualitative content analysis (QCA) method (i.e. summative content analysis [SCA]) to identify critical points of the SPM.

To better understand the WGI report and its SPM, the author uses the thematic analysis, often called the QCA method. This study takes more steps and uses one of the main qualitative content analysis approaches (i.e. SCA). Therefore, QCA (SCA) can help the author count the occurrence of certain words using computer-assisted qualitative data analysis software that quantifies the words in the data. This process helps the author to understand codes and patterns (e.g. the concept in the results section).

Interestingly, the AR6 says more about adaptation for policy makers in sections C (Climate information for risk assessment) and D (Mitigation of future climate change) than in sections A and D. Finally, this study concludes that the IPCC WGI SPM has addressed evidence on global climate change policymaking for SPMa, SPMd (mitigation-based strategies and mitigation policy [MP]) and SPMb, SPMc (adaptation policy and adaptation-based strategy).

First, this study refers only to the contribution of WGI, a SPM. The findings of this study do not necessarily provide a full understanding of what the AR6 WGI SPM says about climate change. It points out that the QDA Miner software and Voyant tool do not include all variables and examples where mitigation and adaptation-based strategies are discussed. The guidance for coding is based on the approved version of IPCC AR6 WGI SPM. The final limitation is that the relatedness of key words (e.g. confidence, high and warming) is sometimes ambiguous; even experts may disagree on how the words are linked to form a concept. Thus, this method works at the keyword level. A more intelligent method would use more meaningful information than keywords.

This study used qualitative data analysis (SCA) to explore what was said about climate change in four sections of the IPCC AR6 WGI SPM, which may influence current and future global climate change policymaking.

Restates the case for accounting and management research from a grounded theory perspective, and advocates its informed and more frequent application. Examines the intellectual foundations and key tenets of grounded theory in the context of researchers’ theoretical assumptions and methodological characteristics, discussed in relation to Laughlin’s (1995) classification schema. Pays particular attention to grounded theory assumptions and methods in relation to other interpretive paradigms such as symbolic interactionism, ethnomethodology and hermeneutics. Describes the basic principles and methods of grounded theory research, and presents potential applications to the accounting and management research arenas. Argues that rigorous grounded theory research can offer the accounting and management literatures unique understandings that provide additional perspectives to those already being offered by major schools of thought, and discusses implications of grounded theory for informing contemporary professional practice.

The objective of this study is to evaluate the quality of Coalho cheese produced using two different strains of Lactococcus spp. that were isolated from artisanal Coalho cheese in Bahia, Brazil.

Three different batches of cheeses were produced using lactic acid Lactococcus spp. strains named “LA‐02”, “RE‐02” and “Blend” (LA‐02 plus RE‐02). To study the quality of these products the paper uses quantitative descriptive analysis (QDA), a test of acceptability and an analysis of physical‐chemical parameters.

For the flavor attribute, the highest acceptabilities were for LA‐02 (7.38) and Blend (6.92). The panelists found that 13 attributes were important to describe Coalho cheese. The Blend cheese was characterized by its yellow color, hardness, consistency, chewiness, typical Coalho cheese aroma and flavor. The LA‐02 cheese was characterized by its acid flavor, homogeneity and softness. All the samples analyzed showed values of moisture and fat that were in line with Brazilian legislation.

Coalho cheese is a typical Brazilian artisanal cheese that is normally produced with raw milk, even though legislation does not allow this. Pasteurization of the milk used to produce cheeses guarantees the microbiological safety of the product and, in this case, the cheese needs the addition of lactic acid bacteria in order to improve the sensorial quality and to give typical characteristics.

Coalho cheese, as produced in the artisanal form, is widely appreciated for its sensorial characteristics. The Coalho cheese proposed in this research retains the typical sensory characteristics by using different strains of Lactococcus spp. that were isolated from artisanal Coalho cheese but according to the specification of good manufacturing practices (GMP).