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This paper aims to highlight the need to place focus on ensuring soft factors in construction projects’ design management and to discuss whether soft factors are hidden success factors.

The presented data is a result of findings from two master theses. The approach is qualitative research and consists of nine semi-structured interviews with design managers and two case studies involving document analyses, meeting observations and descriptions of seven interviews.

This empirical study demonstrates that soft factors are considered important for design managers’ achievement of a successful design process. Focus on soft factors promotes good communication and will improve team performances. Factors are hidden because they are invisible and immeasurable. Furthermore, soft factors are not defined as assigned tasks and are, therefore, easily neglected. Designers are hesitant to explore the possibilities of new technology owing to the fear that they will forfeit human interaction.

This paper is limited to the presentation of empirical findings. Therefore, theory is not a basis for the study but rather a framework for the discussion.

The results in this paper broaden the understanding of human behaviour during the design phase. This knowledge should be considered when the project’s delivery model is designed as it will safeguard actor concerns during the ongoing technological transformation.

This paper contributes knowledge of the view regarding soft factors among project actors. It expands the traditional understanding of value by adding soft factors to the traditional success measures of time, quality and cost.

Although MOOCs have become a pervasive online learning model, the problem of high dropout rates still persists. Gathering the reasons for the high dropout rate can help to improve the platform design and management of the MOOCs.

A total of 74 studies was extracted from the Web of Science and Scopus. Following the PRISMA (Preferred Reporting Items for systematic Reviews and Meta-Analyses) guidelines, the open-source program CiteSpace is employed to review and induce the studies on the antecedents of MOOC dropout.

The antecedents of the MOOC dropout rate are the psychological, social, personal, course-related, and time factors, and the unexpected hidden cost. Motivation and interaction, which have a decisive impact on the dropout rate of MOOCs, interact with each other. Interaction helps to strengthen the motivation, and appropriate course design enhances the degree of interaction.

From the perspective of a learner, the more knowledge and skills the learners acquire, the more likely they will complete the course. Possessing adequate foundational knowledge is one way to arrest the dropout rate. On the part of the MOOC platform, better course design eases the dropout rate. Further, the course duration and hidden cost in MOOCs contribute to the dropout rate.

Given the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China.

After verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis.

The results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies.

The findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types.

This study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.

Knowledge can be created by drawing inferences from what is already known. Often some of the requisite information is lacking and has to be gathered by whatever research techniques are appropriate, e.g. experiments, surveys etc. Even if the information has all been published already, unless it is retrieved no inferences will be drawn from it and consequently there will exist some knowledge that is implicit in the literature and yet is not known by anyone. This ‘undiscovered public knowledge’, as it is termed by Swanson, may exist in the following forms: (i) a hidden refutation or qualification of a hypothesis; (ii) an undrawn conclusion from two or more premises; (iii) the cumulative evidence of weak, independent tests; (iv) solutions to analogous problems; (v) hidden correlations between factors. Methods of classification may also play a direct role in the creation of original knowledge. Novel solutions to problems may be discovered by generating different combinations of the basic features of the solutions, as is done in morphological analysis. Alternatively a natural classification may identify gaps in existing knowledge. This paper reviews previous work on producing knowledge by information retrieval or classification and describes techniques by which hidden knowledge may be retrieved, e.g. serendipity in browsing, use of appropriate search strategies and, possibly in the future, methods based on Farradane's relational indexing or artificial intelligence.

The decision to buy a holiday home depends on a number of social, cultural, economic and demographic factors. These factors are related to home and environmental characteristics as well as demographic characteristics of buyers. The aim of this paper is to investigate the factors that shape the decision to purchase a holiday home in Greece.

This paper presents the results of a survey, involving a representative sample of potential buyers of holiday homes in Greece.

According to the research results, buying a holiday home in Greece is mainly an investment decision for the future and is determined by the value and characteristics of the house, the hidden costs and the factors that shape the external economic environment. (1) Further, the analysis has shown that there is a limited use of electronic channels in the real estate market in Greece with further potential of development.

The investigation focuses on the characteristics of the house, the variables of the external environment, (2) considering any obstacles or catalysts, such as the use of electronic channels. Even though similar studies have been conducted worldwide on the topic, very few have been carried out in Greece which lately has gone through major market changes.

The purpose of this study is to examine the relationships among knowledge attributes (complexity and implicitness), interpersonal distrust, knowledge hiding (KH) and team efficacy and second, to explore a new dimension of KH.

Data for this research were collected from more than 940 employees working in manufacturing, information technology (IT), finance and the purification industry. Structural equation modeling was used to test hypothesized relationships.

First, the research confirmed the existence of bullying hiding behaviors in the knowledge economy era based on “knowledge power.” Second, the findings suggest that knowledge attributes are an important predictor of KH behaviors in organizations. The findings implicate the mediating effect of interpersonal distrust and the moderating role of team efficacy, while team efficacy negatively moderated the relationships between interpersonal distrust with evasive hiding and playing dumb, but positively moderated the relationship between interpersonal distrust with rationalized hiding and bullying hiding.

This is the first study to propose bullying hiding, a behavior that has emerged in organizational knowledge transfer, and it is more detrimental to knowledge sharing than other KH behaviors. The results of research on the different regulating effects of team efficacy on KH behaviors enrich the boundary conditions of KH research.

The purpose of this paper is to develop a comprehensive framework to identify and classify key medical tourism enablers (MTEs) and to study the direct and indirect effects of each enabler on the growth of medical tourism in India.

In this paper, an integrated approach using interpretive structural modeling (ISM) and Fuzzy Matrice d'Impacts Croisés Multiplication Appliquée á un Classement (FMICMAC) analysis has been developed to identify and classify the key MTEs, typically identified by a comprehensive review of literature and expert opinion. The key enablers are also modeled to find their role and mutual influence.

The key finding of this modeling helps to identify and classify the enablers which may be useful for medical tourism decision makers to employ this model for formulating strategies in order to overcome challenges and to become a preferred medical tourism destination. Integrated model reveals enablers such as medicine insurance coverage, international healthcare collaboration, and efficient information system as dependent enablers. No enabler is found to be autonomous enablers. The important enablers like healthcare infrastructure facilities and global competition are found as the linkage enablers. Research in medicine and pharmaceutical science, medical tourism market, transplantation law, top management commitment, national healthcare policy, competent medical and para-medical staffs are found as the independent enablers. Integrated model also establishes the direct and indirect relationship among various enablers.

The research provides an integrated model using ISM and FMICMAC to identify and classify various key enablers of medical tourism in India. In conventional cross-impact matrix multiplication applied to classification analysis, binary relationship of various enablers is considered. FMICMAC analysis helps to establish possibility of relationship among various enablers so that low-key hidden factors can be identified. The low-key hidden factors may initially exhibit marginal influence but they may show significant influence later on during analysis. The uncertainty and fuzziness of relationship among various enablers can be conveniently handled by FMICMAC and expert opinions can easily be captured. This research will help medical tourism decision makers to select right enablers for the growth of medical tourism in India.

This study addresses a central research question: Is individuals’ propensity to hide knowledge a “political phenomenon” among researchers in the Indian higher education institutions? Drawing upon social exchange and uncertainty management theories, the authors examine how a three-way interaction effect of perceptions of organizational politics, political will and political skill contributes to knowledge hiding. In addition, this study aims to develop a nuanced understanding of the knowledge hiding phenomenon in the Indian higher education context.

This study adopts a mixed-method study design with an explanatory sequential approach. The authors gathered data through a cross-sectional survey of 286 researchers (Study 1) followed by two focus group discussions (Study 2) involving 13 academic researchers from five Indian universities. The sample includes full-time faculty members, postgraduate and full-time doctoral students engaged in research.

The results of Study 1 indicate that researchers’ perceptions of organizational politics positively relate to their knowledge hiding. The findings of this study also suggest that the positive relationship between perceptions of organizational politics and knowledge hiding turns negative for individuals with high political will and high political skill. The focus group discussions (Study 2) explore significant predictors of knowledge hiding. This study unveils various characteristics of knowledge, knowledge hider, knowledge seeker and interpersonal dynamics as the key drivers of knowledge hiding in Indian academia.

The significant contributions of this study are to provide new insights into the relationship between organizational politics and knowledge hiding and to unravel the various factors that incite knowledge hiding among researchers in the Indian higher education context. This study is one among the few in the knowledge hiding literature to adopt a mixed-method research design with an explanatory sequential approach.

This paper aims to explore the effectiveness of an artificial neural network (ANN) in predicting fraudulent financial reporting in small market capitalization companies in Malaysia.

Based on the concepts of ANN, a mathematical model was developed to compare non-fraud and fraud companies selected from among small market capitalization companies in Malaysia; the fraud companies had already been charged by the Securities Commission for falsification of financial statements. Ten financial ratios are used as fraud risk indicators to predict fraudulent financial reporting using ANN.

The findings indicate that the proposed ANN methodology outperforms other statistical techniques widely used for predicting fraudulent financial reporting.

The study is one of few to adopt the ANN approach for the prediction of financial reporting fraud.

Construction industry faces challenges in making objective decisions due to monetary value attached to quality. Among various quality management techniques available, cost of quality (COQ) is one such method used to address the concern. However, the absence of measurable COQ factors to monitor quality costs hampers the implementation of COQ framework in the construction industry. Therefore, this study aims to identify COQ factors focused on visible factors (VF) and hidden factors (HF) and the current requirements to achieve it.

This study is based on Preferred Reporting Items for Systematic Review and Meta-Analyses protocol guidelines. The present study identified 57 articles published between 1992 and 2023 in peer-reviewed journals.

The findings reveal 22 factors, which are grouped into four categories based on COQ. Through systematic review, the authors observed limited methodological and theoretical diversity. In fact, there are no quantitative frameworks to calculate COQ. The study, therefore, developed a framework comprising four major routes/paths of COQ factors within the framework.

The COQ routes developed through this study will enable the practitioners to meticulously categorise VF and HF, facilitating quantifying of quality throughout the lifecycle of project, which is currently absent from the existing quality assurance/quality control (QA/QC) approach. In addition, these COQ routes stand as essential construction strategies, significantly enhancing outcomes related to time, cost, quality, sustainability and fostering closer relationships within project frameworks.

The current study contributes significantly to the existing body of knowledge by developing various COQ routes and proposing future research directions to address gaps in the literature.