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Future is rarely explicitly addressed or problematized in business network research. This study aims to examine the possibilities of developing a business actor’s future orientation to network studies and imports ideas and concepts from futures research to support the development.

The study is conceptual and interdisciplinary. The authors critically analyze how extant studies grounded in the sensemaking view and process research approach integrate future time and how theoretical myopia hinders the adoption of a future orientation.

The prevailing future perspective is restricted to managers’ perceptions and actions at present, ignoring the anticipation and exploration of alternative longer-term futures. Future time is generally conceived as embedded in managers’ cognitive processes or is seen as part of the ongoing interaction, where the time horizon to the future is not noticed or is at best short.

To enable a forward-looking perspective, researchers should move the focus from expectation building in business interaction to purposeful preparation of alternative future(s) and from the view of seeing future as enacted in the present to envisioning of both near-term and more distant futures.

This study addresses the growing need of business actors to anticipate future developments in the rapidly changing market conditions and to innovate and change business practices to save the planet for future generations.

This study elaborates on actors’ future orientation to business markets and networks, proposes the integration of network research concepts with concepts from futures studies and poses new types of research questions for future research.

The study provides the emergence and evolution of the socioemotional wealth (SEW) concept in the family business field from 2007 (the inception date) until 2021. To provide a better overview of this notion, the study unfolds a deeper understanding of this term throughout the systematic literature review (SLR).

The study applies a systematic literature review (SLR) by analyzing the sample of 185SEW articles extracted from the Scopus database. To identify all relevant studies, the article selection process was carefully designed and divided into two phases with clear steps: identification of studies via databases and identification of studies via previous studies' reference lists. Selected studies were analyzed using the Bibliometrix R-tool, resulting in an analysis of the evolution of the trends in the SEW literature, citation analysis, and network analysis. Finally, this SLR included the content analysis of the 25 most-cited SEW articles.

The study provides a relevant and comprehensive overview facilitating empirical and theoretical research in this field and paving the way to develop new themes. The bottom line of the important findings is that the SEW concept is relatively new, alluding to a wealthy venue for future works. Other results and implications are discussed on the family business and SEW theme. Additionally, the study provides suggestions which could be used for future works in this area.

This is the first article related to the SEW concept in the family business. It portrays a clear picture of this field, providing relevant information on what has been done, as well as what the future possibilities are that might bode the future horizons in family businesses.

This paper aims to conduct a systematic review of the literature on the quality of integrated reports (IR) and highlight the gaps in the existing research to provide directions and suggestions for future research.

This study was conducted through a systematic literature review using content analysis based on 40 papers from the Scopus, Web of Science and EBSCOhost databases on IR quality. While reading the full-text papers, the authors found six additional papers referenced by the literature being reviewed that were relevant to IR quality. Thus, there were 46 papers in the final review. The analysis begins with the definition and dimension of IR quality and theoretical lenses. Furthermore, this study outlines constructs or variables used in the previous literature.

The authors found that most studies used the quantitative method (41 papers or 89%). Five papers in the literature used qualitative methods (11%). Most researchers (34 papers or 72%) defined IR quality as consistent with the International Integrated Reporting Council framework, specifically the eight content elements. In particular, with the constructs that make up the quality of the IR, variations between researchers were found. Furthermore, there were some gaps that could be the directions for future research.

The literature that provides academic knowledge about IR quality is still limited, and research on IR is still growing. The literature review conducted by this study can provide an overview of the current research positions on the quality of IR and directions for future research in this area.

This study intends to show corporate executives a framework demonstrating the quality of corporate reporting. It can impact not only investors as a specific stakeholder group but also other stakeholder groups.

To the best of the authors’ knowledge, this study is the first literature review to examine the quality of IR, thus providing a map of current research to suggest directions for future research. Most of the previous literature reviews have been focused on integrated reporting (IR) in general and not quality.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.

This paper aims to conduct a systematic literature review of the research in the field of Artificial Intelligence (AI) and Big Data Analytics (BDA) in Supply Chain Risk Management (SCRM). Finally, future research directions in this field have been suggested.

The papers were searched using a set of keywords in the SCOPUS database. These papers were filtered using the Title abstract keywords principle. Further, more papers were found using the forward-backward referencing method. The finalized papers were then classified into eight categories.

The previous papers in AI and BDA in SCRM were studied. These papers emphasized various modelling and application techniques for AI and BDA in making the supply chain (SC) more resilient. It was found that more research has been done into conceptual modelling rather than real-life applications. It was seen that the use of AI-based techniques and structural equation modelling was prominent.

AI and BDA help build the risk profile, which will guide the decision-makers and risk managers make their decisions quickly and more effectively, reducing the risks on the SC and making it resilient. Other than this, they can predict the risks in disasters, epidemics and any further disruption. They also help select the suppliers and location of the various elements of the SC to reduce the lead times.

The paper suggests various future research directions that fellow researchers can explore. None of the previous research examined the role of BDA and AI in SCRM.

This paper aims to present the findings from a European study on the digital skills gaps in tourism and hospitality companies.

Mixed methods research was adopted. The sample includes 1,668 respondents (1,404 survey respondents and 264 interviewees) in 5 tourism sectors (accommodation establishments, tour operators and travel agents, food and beverage, visitor attractions and destination management organisations) in 8 European countries (UK, Italy, Ireland, Spain, Hungary, Germany, the Netherlands and Bulgaria).

The most important future digital skills include online marketing and communication skills, social media skills, MS Office skills, operating systems use skills and skills to monitor online reviews. The largest gaps between the current and the future skill levels were identified for artificial intelligence and robotics skills and augmented reality and virtual reality skills, but these skills, together with computer programming skills, were considered also as the least important digital skills. Three clusters were identified on the basis of their reported gaps between the current level and the future needs of digital skills. The country of registration, sector and size shape respondents’ answers regarding the current and future skills levels and the skills gap between them.

The paper discusses the digital skills gap of tourism and hospitality employees and identifies the most important digital skills they would need in the future.

The purpose of this article is to discuss how the mastery of resilience in operations and supply chains plays a significant role in the transition to a more sustainable future. Furthermore, it is supposed to propose avenues for future research on operational and supply chain resilience, interacting with the sustainability literature in our field.

A conceptual review of resilience and sustainability themes within operations and supply chain management research is conducted. Reflections on the topic are informed by relevant literature published over the last decade.

The major conceptual contributions are threefold: (1) This article elaborates on the understanding of operational resilience and supply chain resilience concepts and reviews their respective primary research streams. (2) It proposes resilience as the missing element in the pursuit of excellence in organizations that want to contribute to a more sustainable future. (3) The article offers a research framework that provides a future research agenda at the intersection of resilience and sustainability in operations and supply chain management research.

The article highlights gaps in current research and illustrates further areas of research that need to be addressed to maximize the contribution of operations and supply chain management research in supporting practitioners to achieve a more sustainable future.

This study aims to answer the following research question: What are the opportunities for future research concerning the Frugal Innovation (FI) phenomenon? To address this, the authors propose a novel approach to literature review on the topic. They do so in view of synthesising scholars’ recommendations for subsequent studies. They also advocate that it is time to contribute to the establishment of the FI field by mapping the future of this approach.

The authors conducted a systematic literature review (SLR) to connect past and future research on FI. After the screening process of the documents extracted from multiple databases, they performed a bibliometric analysis to provide an overview of the field. Furthermore, the lexical analysis and descending hierarchical analysis were generated through the IRAMUTEQ software to identify the clusters for future research on FI.

This research not only demonstrates the current state of the art of FI literature but also identifies a research agenda with six categories of opportunities for further studies on the topic: frugal consumer behaviour; establishment of the field; sustainable impact; approaches to different contexts; implementation processes; and challenges for value creation.

The FI phenomenon is receiving increasing attention from scholars in the management field due to its socioeconomic and managerial implications, especially after the Covid-19 outbreak. Therefore, the findings benefit scholars striving to expand the scope of FI research, as well as entrepreneurs, managers and organisations aiming to enhance their social responsibility to reduce their environmental impact.

Augmented reality (AR) has emerged as a new interactive technology, swiftly transforming the field of marketing. Driven by its rapid uptake in marketing practices, academic research on AR has proliferated. This study aims to offer a holistic view of the past, present and future of augmented reality marketing (ARM) scholarship by analyzing its current and evolving research profile as well as its social and conceptual structures to inspire further research.

This study enriches the ARM scholarship by integrating a quantitative bibliometric analysis with a chronological-thematic review and a qualitative content analysis to develop a more comprehensive understanding of this novel area and suggest future research courses.

The bibliometric analysis reveals the key performance indicators as well as the social and conceptual structure of the ARM research field. The chronological-thematic review exhibits the advancement of ARM research over time and forecasts the emerging trends for the domain. Finally, the content analysis of recent articles reveals the current research hotspots and provides future research directions.

The database limits the selection of literature, as the information in databases such as Scopus is updated regularly, resulting in alterations in the number of articles and citations.

AR developers and brand managers may use this study’s findings to understand the current ARM landscape better and make strategic decisions based on AR adoption and consumption patterns.

This study is singular in using a mixed methods approach by integrating the findings from bibliometric and content analyses for more reliable results and to offer a holistic perspective of the ARM sector, thereby significantly advancing the field of technology-led marketing.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.