Search results

A literature review or review article is an integral part of a scientific body of research which synthesizes prior knowledge and provides a holistic overview of a subject domain. While several studies emphasize the significance of literature reviews and include the guidelines for conducting a review, limited studies demonstrated different types of literature review methodologies in a comprehensive way. Accordingly, this chapter presents various types of review methodologies which includes narrative, descriptive, systematic, meta-analysis, hybrid, umbrella, scoping, theoretical, and critical reviews. In addition, the authors' skills including logical reasoning, content analysis, literature mapping, critical writing, and ethical consideration are presented. Further, quality aspects of the literature review are discussed such as the rigor and relevance of the selected studies. Overall, this chapter provides implications for researchers in understanding types of literature review methodologies along with their objectives, strengths, and weaknesses which can assist them in selecting a suitable methodology while conducting a review.

The purpose of this manuscript is to provide a step-by-step primer on systematic and meta-analytic reviews across the service field, to systematically analyze the quality of meta-analytic reporting in the service domain, to provide detailed protocols authors may follow when conducting and reporting these analyses and to offer recommendations for future service meta-analyses.

Eligible frontline service-related meta-analyses published through May 2021 were identified for inclusion (k = 33) through a systematic search of Academic Search Complete, PsycINFO, Business Source Complete, Web of Science, Google Scholar and specific service journals using search terms related to service and meta-analyses.

An analysis of the existing meta-analyses within the service field, while often providing high-quality results, revealed that the quality of the reporting can be improved in several ways to enhance the replicability of published meta-analyses in the service domain.

This research employs a question-and-answer approach to provide a substantive guide for both properly conducting and properly reporting high-quality meta-analytic research in the service field for scholars at various levels of experience.

This work aggregates best practices from diverse disciplines to create a comprehensive checklist of protocols for conducting and reporting high-quality service meta-analyses while providing additional resources for further exploration.

This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.

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 study aims to map the “Desktop Research” (DR) output in Pakistan, as part of the growing field of research globally. It also ascertains the productive institutions and prolific authors along with their collaboration patterns.

Bibliometric techniques were used to quantitatively analyze the DR published in Pakistan. The publications from 1981 to 2021 were retrieved from Scopus. A total of 1,802 publications were retrieved and used for analysis.

Results indicated an unpredictable increase in DR output from approximately 100 to 400 records during the past five years. The year 2020 was most productive in DR research showing the excess use of secondary data by researchers in COVID-19. The focus of researchers towards DR was consistently rising. Medical journals were found to publish DR extensively. Majority of the publications were contributed by collaborative work and researchers of the USA were found as the most collaborative with Pakistani authors. Publications of single category journals, open access journals and international collaboration get more citations.

The results of the analysis rely only on a single database, Scopus, for retrieving the publication data.

The study has practical implications for the policymakers and higher education development organizations to introduce the DR as a course in academic schools.

To the best of the authors’ knowledge, this study is the first to review DR in the context of Pakistan through bibliometric analysis. This comprehensive overview provides a better understanding of the development of the field and possible practice implications.

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.

This study aims to analyze review research in hospitality, identifying the structure and most recent developments in current hospitality review studies while providing exploratory insights for future research in this research area.

Using bibliometric analysis, content analysis and a quantitative systematic literature review, this study provides a comprehensive review and critical analysis of 128 review studies published in leading hospitality journals (International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management and Journal of Hospitality Marketing and Management).

This paper presents a comprehensive and in-depth discussion based on the title, journal source, author contribution, year of publication, sample size, selected period, database selection, methodology, data collection methods, themes, regional selection, keywords, abstracts and results of the hospitality review studies analyzed. The findings provide new insights to advance the theoretical and practical implications of review studies in hospitality.

This research provides critical insights for both hospitality review studies and academic and industry hospitality personnel.

As a pioneering study in research on review studies, the results of this paper focus not only on a systematic overview and assessment of recent hospitality review works but also on the future agenda of hospitality and review studies.

The study aims to work on two objectives, first to provide a theoretical foundation along with ongoing trend in the field of green human resource management (GHRM) and employee green creativity (EGC) in the hospitality and tourism industry. Second, the study also proposes a conceptual research model to understand the dynamics of the relationship between GHRM and EGC for future studies.

The study uses multi-method approach, systematic literature review and bibliometric analysis is performed on published work on GHRM and EGC. This study initially shortlisted 52 publications from multiple databases, which was refined to 11 Scopus-indexed papers, which discussed both GHRM and EGC attributes in a hospitality context. VOSviewer and advance excel software's are being used to perform the analysis.

The systematic literature review concluded that very limited studies have been conducted on GHRM and EGC in the hospitality context and it has recently gained prominence during the covid pandemic. While bibliometric analysis also identified h-index authors with their co-authorship network, citations and keywords matrix and the changing trends in the domain of GHRM and EGC in hospitality and tourism industry. The analysis also highlights the individual and organisational factors influencing the relation between GHRM and EGC.

This study is the first to conduct a systematic literature review and bibliometric analysis on GHRM and EGC in hospitality and tourism sector. Moreover the paper also provides researchers with an in-depth summary of the available literature and a blue print for future studies on GHRM and EGC.

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.

With the intensification of market competition, there is a growing demand for weak signal identification and evolutionary analysis for enterprise foresight. For decades, many scholars have conducted relevant research. However, the existing research only cuts in from a single angle and lacks a systematic and comprehensive overview. In this paper, the authors summarize the articles related to weak signal recognition and evolutionary analysis, in an attempt to make contributions to relevant research.

The authors develop a systematic overview framework based on the most classical three-dimensional space model of weak signals. Framework comprehensively summarizes the current research insights and knowledge from three dimensions of research field, identification methods and interpretation methods.

The research results show that it is necessary to improve the automation level in the process of weak signal recognition and analysis and transfer valuable human resources to the decision-making stage. In addition, it is necessary to coordinate multiple types of data sources, expand research subfields and optimize weak signal recognition and interpretation methods, with a view to expanding weak signal future research, making theoretical and practical contributions to enterprise foresight, and providing reference for the government to establish weak signal technology monitoring, evaluation and early warning mechanisms.

The authors develop a systematic overview framework based on the most classical three-dimensional space model of weak signals. It comprehensively summarizes the current research insights and knowledge from three dimensions of research field, identification methods and interpretation methods.