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This paper investigates state auditors’ decisions regarding the isolation or projection of sample misstatements to underlying sample populations. Seventy-eight state auditors completed four treatment cases that incorporate the complete 2×2 manipulation of intentional/unintentional and systematic/non-systematic misstatements in different case scenarios, enabling a test of the independent variables both across and within case scenarios.

The results indicate that both across and within case scenarios, auditors tend to project systematic misstatements more often than they project non-systematic misstatements. However, the auditors’ isolation/projection decisions are generally not influenced by whether the sample misstatements are intentional or unintentional.

This article aims to provide a bibliometric and systematic literature analysis of studies published in the Journal of Intellectual Capital (JIC) from 2014 to 2018 in order to highlight emerging themes and future trends.

The analysis focused on 187 papers published on JIC over a period of five years. A scientometric approach to data mining enabled the detection of patterns in the dataset. Precisely, the investigation was conducted by integrating a bibliometric analysis on VOSviewer with a systematic literature review.

Four main streams of research on JIC emerged in the years of the analysis: reporting and disclosure of intellectual capital; intellectual capital research in universities, education and public sector; knowledge management; intellectual capital, financial performance, and market value.

The study offers valid insights to the topics covered by the Journal of Intellectual Capital by identifying the main research gaps and trends, along with future research avenues.

Prior scholars mostly focused on systematic literature reviews, whilst the use of bibliometric methods generally seems to be a missing tile in the research domain. Also, none of the extant studies has focused on the Journal of Intellectual Capital with reference to the 2014–2018 period. The use of both bibliometric and systematic approaches to literature review delivered extremely fine-tuned results in terms of factors such as citations, contents and evolution of clusters over time.

The purpose of this study is to map the intellectual structure of the research concerning conflict and conflict management in virtual teams (VT), to contribute to the further integration of knowledge among different streams of research and to develop an interpretative framework to stimulate future research.

A data set of 107 relevant papers on the topic was retrieved using the Web of Science Core Collection database covering a period ranging from 2001 to 2019. A comparative bibliometric analysis consisting of the integration of results from the citation, co-citation and bibliographic coupling was performed to identify the most influential papers. The systematic literature review complemented the bibliometric results by clustering the most influential papers.

The results revealed different intellectual structures across several types of analyses. Despite such differences, 41 papers resulted as the most impactful and provided evidence of the emergence of five thematic clusters: trust, performance, cultural diversity, knowledge management and team management.

Based on the bibliometric analyses an interpretative research agenda has been developed that unveils the main future research avenues. The paper also offers important theoretical contributions by systematizing knowledge on conflict in identifying VTs. Managerial contributions in the form of the identification of best practices are also developed to guide conflict management in VTs.

The uniqueness of this paper is related to its effort in studying, mapping and systematizing the knowledge concerning the topic of handling conflicts in VTs. Considering the current contingencies, this research is particularly timely.

This paper aims to study the connection between the systematic equity risk of US tourism industry companies and a set of information from inside these firms and the market. The authors sought to identify which information explains equity risk to estimate patterns of behavior – especially for those companies that cannot have a beta – in terms of the cost of share capital.

To carry out the research, the authors used a panel data technique and combined accounting information from the selected companies with macroeconomic information to develop independent variables. The sample consisted of 79 firms of the arts, entertainment and recreation and accommodation and food services sectors in the USA for 2004-2013. The authors incorporated two dummy variables into the analyses. The first one was used to find out if a difference exists between the two sectors, and the other was used to examine differences before and after 2008, when the current economic and financial crisis began.

The results reveal that equity risk is explained by businesses’ size and growth, along with three indicators of business efficiency, consumer price and Stoxx Europe 50 indices. The 2008 financial crisis did not alter the behavior of the estimated model, and no difference was found between the two sectors in question.

The study’s most important limitation is the number of companies and years that make up the sample, although a broader set of data was analyzed in this work compared to previous studies.

The research results are quite useful to tourism enterprise management in the US market as they provide information that explains companies’ equity risk. Knowing this information could facilitate more efficient management, and an understanding of which information determines company risk can help to quantify risk objectively without access to betas.

The authors studied the US market as an important financial market and the tourist industry, in particular, for its economic significance, as shown by the direct contribution of travel and tourism to the US gross domestic product. Although this type of research in the tourism sector is not new, the present study answers the need identified by Park and Jang (2014) to continue this line of research by using a more interdisciplinary approach that combines hospitality research with finance and/or accounting studies.

This paper aims to bring together research on housing market area, submarket and household migration into a systems approach that helps us gain a better understanding of the structure and dynamics of a housing market and identify housing problems for a large metropolitan area.

The paper uses a geographic information system (GIS)-based method with simple quantitative techniques, including spatial analysis, location analysis, house price clustering and cross-tabulation. The analysis is based on migration data from the 2011 Census, house price data from the Land Registry in 2011 for Greater Manchester at the ward level and the output areas level.

The results show that different submarkets and housing market areas had different patterns of spatial migration and connections with other areas. Through a systematic analysis of migration and house price in combination, it also found a close connection between destination submarkets and the ages of migrants and identified specific problematic patterns for a large metropolitan area.

The interactions between the owner-occupied sector and the social and private rented sectors are arguably an important omission from the analysis. Also, it is acknowledged that clustering ward units based on price differentials is subject to distortions in terms of specification, size and shape. Moreover, the use of the large samples may result in very small p-values, leading to the problem of the rejection of the predefined hypothesis.

A systematic analysis of migration and house price in combination may be used to gain a better understanding of the housing market dynamics and identify housing problems systematically for a large metropolitan. It may help to identify low-demand areas, high-demand areas and assist planners with decisions in allocating suitable land for new housing constructions.

The GIS-based method introduced in the paper could be considered as an effective approach to provide a better basis for determining policy interventions and public investment designed to allocate land resources effectively and improve transport systems to change existing problematic migration patterns.

This paper fills a gap in the international literature in relation to adopting a systems approach that analyses migration and house price data sets in combination to systematically explore migration patterns and linkages and identify housing problems for a large metropolitan area. This systems approach can be applied in any metropolitan area where migration and house price data are available.

This paper aims to close gaps in the current literature according to whether there are differences regarding the relationship between corporate social performance (CSP) and systematic risk when diverse regions of the world are considered, and what the respective drivers for this relationship are. Furthermore, it tests the robustness to alternative measures for CSP and systematic risk.

This study focuses on the impact of corporate social responsibility on systematic firm risk in an international sample. The authors measure CSP emerging from a company's social responsibility efforts by utilizing a CSP rating framework that covers a variety of dimensions. The instrumental variable approach is applied to mitigate endogeneity and identify causal relationships.

The impact of overall CSP on systematic risk is most distinct for North American firms and, in descending order, weaker in Europe, Asia–Pacific and Japan. Risk mitigation applies across all four regions. However, the magnitude of impact differs. While the most critical drivers in North America and Japan include product responsibility, Europe is affected most by the employees category and Asia–Pacific by environmental innovation.

The findings help firms to control their cost of equity and investors may identify low-risk stocks by considering certain aspects of CSP.

This study distinguishes itself from previous literature addressing the connection between systematic risk and CSP by focusing on regional differences in an international sample, using the very transparent CSP measures of Asset4, identifying underlying impact drivers, and testing for robustness to alternative measures of systematic risk.

This study aims to conduct a systematic review and critically analyze the sentiment analysis literature in hospitality and tourism from methodological (data sets and analyzes) and thematic (topics, theories, key constructs and their relationships) perspectives.

Qualitative thematic review and quantitative systematic review were performed on 70 papers obtained from hospitality and tourism categories of two databases, namely, Web of Science and Scopus.

A total of 5 topics and 27 sub-topics were identified and the major theme is market intelligence. Sentiment variables were investigated not only as independent but also as dependent variables. The customer rating is the most investigated dependent variable, whereas moderators and mediators were rarely tested. Most reviewed studies did not use theory. The findings from the methodological review show that analysis of big data was rare. Moreover, testing the performance of sentiment analyzes was uncommon, and only one paper tested the performance of aspect/feature extraction.

This study extends prior review studies by providing a comprehensive view of how knowledge and methodologies of sentiment analysis have developed. The identified themes and key constructs serve as a solid base for future knowledge advancement. Future research directions on sentiment analysis are also provided.

To the best of the authors’ knowledge, this study is the first comprehensive methodological and thematic review of sentiment analysis in hospitality and tourism. Based on the identified findings, the authors propose several directions for future research.

The purposes of this study are to synthesize the current research findings reported in major hospitality and tourism journals and to discuss the knowledge gaps where additional research endeavors are needed.

A systematic review approach was adopted to analyze 67 research articles about online reviews that were published between January 2000 and July 2015 in seven major hospitality and tourism journals.

This study presents a thematic framework of online review research, which was advanced by integrating the interactions among quantitative evaluation features, verbal evaluation features, reputation features and social features of online reviews with important outcomes of consumer decision-making and business performance. The thematic framework helps researchers identify the areas in extant hospitality literature of online reviews and point out possible directions for future studies.

The systematic review approach has a qualitative nature, where relevant literature was interpreted based on the authors’ domain knowledge and expertise.

Practitioners can gain a comprehensive understanding of the dynamic relationships among the key influential factors in online reviews, as presented in the thematic framework of online review research. Accordingly, managers will be able to develop effective strategies to leverage the positive impacts of online reviews to the business outcomes.

This systematic review synthesizes the findings reported in most recent publications (January 2000-July 2015; also including “Online First” articles) in seven major hospitality and tourism journals and develops an integrated research framework, anchoring on four meta-research questions and showing the dynamic relationships among the key players/factors/themes in online review research. This framework provides a visual diagram to practitioners for a better understanding of the relevant literature and assists researchers in developing new research questions for future studies.

This study aims to identify the trends that have changed in the field of construction management over the last 20 years.

In this study, 3,335 journal articles published in the years 2000–2020 were collected from the Web of Science database in construction management. The authors applied bibliometric analysis first and then detected topics with the latent Dirichlet allocation (LDA) topic detection method.

In this context, 20 clusters from cluster analysis were found and the topics were extracted in clusters with the LDA topic detection method. The results show “building information modeling” and “information management” are the most studied subjects, even though they have emerged in the last 15 years “building information modeling,” “information management,” “scheduling and cost optimization,” “lean construction,” “agile approach” and “megaprojects” are the trend topics in the construction management literature.

This study uses bibliometric analysis. The authors accept that the co-citation and co-authorship relationship in the data is ethical. They accept that honorary authorship, self-citation or honorary citation do not change the pattern of the construction management research domain.

There has been no study conducted in the last 20 years to examine research trends in construction management. Although bibliometric analysis, systematic literature reviews and text mining methods are used separately as a methodology for extracting research trends, no study has used enhanced bibliometric analysis and the LDA topic detection text mining method.

For better mapping the path of intellectual capital (IC) research, the purpose of this paper is to selectively review empirical studies of IC published, and identify theories, components and three dimensions of analysis: national IC (NIC), regional IC (RIC) and organizational IC (OIC).

The systematic literature review (SLR) subject to analysis is based on empirical studies made between 1960 and 2016, and focuses on three dimensions of analysis: NIC, RIC and OIC. Four research questions were designed, using the following databases, namely, Web of Science, Scopus and Google Scholar, for data collection purposes.

The SLR unveils a multidimensional taxonomy for measuring and classifying the type of IC applicable to the different levels of analysis and provides some recommendations for future studies of NIC, RIC and OIC, by outlining the need for clear definitions of components and measures of IC and identifying strengths, limitations and future research avenues.

In order to fill the gap found in the literature and the non-existence of a study clarifying the multiple dimensions of analysis of IC, this SLR makes a twofold, original contribution to the literature on management: providing an SLR of the main empirical studies dealing with different units of analysis; and identifying a multidimensional taxonomy for measuring and classifying the type of IC applicable to the different levels of analysis.