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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.

Background: The annual average daily traffic (AADT) data from road segments are critical for roadway projects, especially with the decision-making processes about operations, travel demand, safety-performance evaluation, and maintenance. Regular updates help to determine traffic patterns for decision-making. Unfortunately, the luxury of having permanent recorders on all road segments, especially low-volume roads, is virtually impossible. Consequently, insufficient AADT information is acquired for planning and new developments. A growing number of statistical, mathematical, and machine-learning algorithms have helped estimate AADT data values accurately, to some extent, at both sampled and unsampled locations on low-volume roadways. In some cases, roads with no representative AADT data are resolved with information from roadways with similar traffic patterns.

Methods: This study adopted an integrative approach with a combined systematic literature review (SLR) and meta-analysis (MA) to identify and to evaluate the performance, the sources of error, and possible advantages and disadvantages of the techniques utilized most for estimating AADT data. As a result, an SLR of various peer-reviewed articles and reports was completed to answer four research questions.

Results: The study showed that the most frequent techniques utilized to estimate AADT data on low-volume roadways were regression, artificial neural-network techniques, travel-demand models, the traditional factor approach, and spatial interpolation techniques. These AADT data-estimating methods' performance was subjected to meta-analysis. Three studies were completed: R squared, root means square error, and mean absolute percentage error. The meta-analysis results indicated a mixed summary effect: 1. all studies were equal; 2. all studies were not comparable. However, the integrated qualitative and quantitative approach indicated that spatial-interpolation (Kriging) methods outperformed the others.

Conclusions: Spatial-interpolation methods may be selected over others to generate accurate AADT data by practitioners at all levels for decision making. Besides, the resulting cross-validation statistics give statistics like the other methods' performance measures.

Over the past decade, researchers have witnessed an exponential growth in the number of publications on IR. This paper aims to understand the state of the art of the research field and to highlight the areas where further academic research is needed, guiding developments in theory, research, policy and practices.

The authors apply the dynamic literature review method called “Systematic Literature Network Analysis”, which combines systematic literature review and bibliographic network analysis. Furthermore, to overcome some of the limitations connected to the methodology, the authors integrate the literature with a manual content analysis of papers.

IR adoption and practices and their determinants represent the most analyzed aspects of literature. Over time, attention has been paid to more specific issues, such as the relationship between IR and other disclosure mechanisms, IR quality and its assurance, the critical analysis of the IR framework and principles and difficulties in IR adoption. Although the literature on IR can be considered to be in its mature stage, many aspects are still under-researched, so there is plenty of space for future research.

The authors propose the following main issues as subjects to be investigated in future studies: IR is not simply an evolution of sustainability reporting, but an innovative communication tool; the debate on who the recipients of value are (shareholders or stakeholders) and on what the definition of value adopted by IR is still remains an open issue; more attention should be given to the role of IR as a managerial tool, which could support strategy formation and communication, and influence internal processes of performance measurement and evaluation; what the future of IR will be in light of recent EU Corporate Sustainability Reporting Directive and new ISSB's standards is still an open question. From a methodological perspective, little is known about structured approaches in accounting studies. The authors confirm how methodologies, such as that of this paper, may be exploited as a tool to support dynamic analysis for setting the agendas for future studies in the accounting field.

The growing complexity of consumer engagement (CE) due to the impact of Internet of things (IoT) has been attracting significant attention from both academics and industry practitioners especially in recent times. Hence, understanding this phenomenon remains very crucial to the body of knowledge. This study conducted a systematic review on IoT and CE with the aim of proposing future research opportunities using the TCCM model.

Extant literature studies were systematically examined by sourcing high ranking ABS journals from EBSCO, ScienceDirect and Emerald. A total of 58 articles were included in the final analysis of this research.

The analysis established the need to conduct more research on CE due to the impact of new technological implementation in retail. The results further suggest the need for extensive research across African countries and emerging markets to enable broader empirical generalizations of research outcomes. Using the TCCM framework, the authors indicated directions for future empirical research.

This study exposes the current trends in CE and IoT. The results and analysis are both compelling and verifiable, hence, establishing a firm base of reference for future research in related fields.

The field of scientific research on small and medium-sized family businesses has been growing exponentially and the aim of this paper is to systematize the body of knowledge to develop an agenda for the future.

Adopting comparative bibliometric analyses on 155 articles (from 1989 until 2018) the authors provide a systematic assessment of the scientific research about small family firms, unveiling the structure and evolution of the field. Bibliographic coupling, co-citation analysis and co-occurrence analysis are adopted to identify the most influential studies and themes.

Four clusters of research are reviewed: succession in family SMEs, performances of family SMEs, internationalization of family SMEs and organizational culture of family SMEs.

This paper contributes to the field of family SMEs by providing a systematic analysis of the scientific knowledge. Reviewing those clusters allows to providing avenues and reflections for future research and further practice.

Tourism may have important positive and negative economic, socio-cultural and environmental impacts. However, cultural and natural resources are also the base to the development of competitive destinations and changes in these resources can have an important impact on tourism development. Despite the considerable literature regarding the impacts of tourism, a limited number of studies examine the impact of the environment on tourism, specifically the impact of air quality (AQ). Therefore, this paper aims to review what is known about the impact of AQ on tourism demand, analysing the different methods and approaches used, as well as the results obtained.

A systematic literature review method was used to examine the state of the art in this topic and identify research gaps and new research directions. Only 26 papers were identified that examine the impact of AQ on tourism demand.

The majority of the studies were carried out in China and investigate the impact of AQ on tourism from the perspective of tourism demand. Both global (tourism demand) and individual (tourist perceptions) approaches have been used to investigate the impact of AQ on tourism.

This is the first systematic literature review on the impact of outdoor AQ on tourism demand. Moreover, this paper analyses the methods and approaches that have been used in the literature to examine the impact of outdoor AQ on tourism demand. The paper ends with a discussion on the identified research gaps concerning the influence of AQ on tourism development.

This paper aims to provide a multidisciplinary framework that allows an integrated understanding of reasons of success or failure in equity crowdfunding (ECF), a Fintech digital innovation of the traditional entrepreneurial finance, defining a future research agenda.

A systematic literature review (SLR) has been conducted on 127 documents extracted from two multidisciplinary repositories (Elsevier’s Scopus and Clarivate Analytics Web of Science) for the period between 2015 and early 2022. After a systematized series of inclusion and exclusion criteria, in line with the objectives and conceptual boundaries, a final list of 32 peer-reviewed articles written in English was analyzed by the authors through a meta-synthesis and thematic analysis to identify the key themes and dominant concepts.

Results show that the body of literature is recent and fast growing. The proposed integrative framework of existing research indicates that the outcome of an ECF campaign is related to signals conveyed by entrepreneurs in the form of hard information (firm characteristics, financial information, business characteristics and project description) and soft information (intellectual capital, human capital, social capital and social media network), catalyzed by digital media that facilitate also personal interactions between entrepreneurs and investors. Similarly, external factors (investors and campaign characteristics, with the fundamental role of ECF platform managers in building trust between entrepreneurs and investors) allow for the alleviation of information asymmetries. The present study sheds light on which signal mechanisms are decisive in improving the outcome, taking into consideration various disciplines which follow different but complementary perspectives.

Entrepreneurs should adapt to the transition toward the digital era, exploiting alternative financial instruments and learning effective signaling strategies, within a large variety of skills requested. Platform managers can obtain more focused information on selected entrepreneurial projects more efficiently.

Although it is fast-growing, the field of research is very recent, still fragmented and limited to the perspective/discipline followed. This SLR is, to the best of the authors’ knowledge, the first multidisciplinary and integrative analysis of reasons that motivates success, or failure, of an equity-based crowdfunding campaign. The digital nature of ECF encourages future research to move toward more pioneering and unconventional theories and research methods. Hence, the authors add to the existing literature by proposing future patterns of research based on an integration of highly technological skills and behavioral/psychological approaches.

Given the cryptocurrency market boom in recent years, this study aims to identify the factors influencing cryptocurrency pricing and the major gaps for future research.

A systematic literature review was undertaken. Three databases, Scopus, Web of Science and EBSCOhost, were used for this review. The final analysis comprised 88 articles that met the eligibility criteria.

The influential factors were identified and categorized as supply and demand, technology, economics, market volatility, investors’ attributes and social media. This review provides a comprehensive and consolidated view of cryptocurrency pricing and maps the significant influential factors.

This paper is the first to systematically and comprehensively review the relevant literature on cryptocurrency to identify the factors of pricing fluctuation. This research contributes to cryptocurrency research as well as to consumer behaviors and marketing discipline in broad.

This study analyses the literature on artificial intelligence (AI) and its implications for the agri-food sector. This research aims to identify the current research streams, main methodologies used, findings and results delivered, gaps and future research directions.

This study relies on 69 published contributions in the field of AI in the agri-food sector. It begins with a bibliographic coupling to map and identify the current research streams and proceeds with a systematic literature review to examine the main topics and examine the main contributions.

Six clusters were identified: (1) AI adoption and benefits, (2) AI for efficiency and productivity, (3) AI for logistics and supply chain management, (4) AI for supporting decision making process for firms and consumers, (5) AI for risk mitigation and (6) AI marketing aspects. Then, the authors propose an interpretive framework composed of three main dimensions: (1) the two sides of AI: the “hard” side concerns the technology development and application while the “soft” side regards stakeholders' acceptance of the latter; (2) level of analysis: firm and inter-firm; (3) the impact of AI on value chain activities in the agri-food sector.

This study provides interpretive insights into the extant literature on AI in the agri-food sector, paving the way for future research and inspiring practitioners of different AI approaches in a traditionally low-tech sector.

Literature shows that corporate governance matters more in countries with weak legal environments. The purpose of this study is to synthesise and map research that has been done so far on corporate governance in Zimbabwe, a country that has been characterised by weak legal systems and lack of respect for property rights.

A systematic review and bibliometric analysis of 20 articles indexed in the Scopus and Web of Science databases was carried out to establish the trends and evolution of corporate governance in Zimbabwe.

The articles reviewed looked at the association between corporate governance attributes and firm performance, disclosure of information and economic growth. The proportion of independent directors was found to significantly affect firm performance and information disclosure in most of the studies. The majority of the studies used descriptive statistics and simple regression in their methodologies. The stakeholder theory is the most used in the studies reviewed.

The study highlights the need to strengthen the state infrastructure that enhances corporate governance at the firm level. When state-owned companies adhere to good corporate governance practices, this can cascade to the private sector.