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Drawing on signalling and impression management theories, this study aims to examine a bidirectional association between managerial tone in earnings conference calls and financial performance.

The sample includes non-financial firms listed in the FTSE 350 index during the period 2010–2015. Managerial tone was measured using positive and negative keywords based on the Loughran-McDonald Sentiment Word Lists, while return on assets was used as a proxy for firms’ financial performance.

The findings indicate that current financial performance positively affects the managerial tone in earnings conference calls. Likewise, the results also show that there is a positive relationship between managerial tone in earnings conference calls and firms’ future financial performance.

The results have important implications for top management to use more virtual communication media (i.e. earnings conference calls) to continue managing their relationships with financial stakeholders and helping them better understand financial performance, especially in countries where holding such calls is not yet part of firms’ policy.

To the best of the authors’ knowledge, this is one of the first studies that explore the relationship between managerial tone in earnings conference calls and financial performance. Overall, this study contributes to managerial tone literature and holds significant theoretical and practical implications.

As it is known, the accounting information system (AIS) plays a significant role in the business ecosystem by recording and processing financial and accounting data and reporting the produced information to all relevant parties for decision-making. However, its used methods and systems, including double-entry bookkeeping and enterprise resource planning (ERP) systems, have limitations, especially in terms of trust and reliability concerns for stakeholders and the possible scope for records manipulation and fraud. The application of blockchain technology is believed to enhance the reliability of the AIS and addresses many of its current limitations. Blockchain can offer numerous benefits if used to manage AIS functions through enhanced trust, reliability, and transparency, increased efficiency, reduced costs and fraud, improved accounting information quality and real-time accounting. Nevertheless, the adoption and implementation of blockchain in the AIS are associated with several technical and nontechnical challenges which are not easy to address and could limit the wide technology adoption in the immediate future. Considering that a full understanding of the benefits and challenges of adopting blockchain in the AIS still needs more clarification, this chapter examines blockchain technology and its implications for the AIS. It reviews blockchain characteristics and its benefits to the AIS, discusses its possible integration into the AIS, outlines adoption and implementation challenges, and suggests critical avenues for future research.

The purpose of this paper is to review how knowledge transfer, including knowledge integration, absorptive capacity and reverse knowledge transfer (RKT) in cross-border acquisitions, is examined in existing research work. The authors also propose directions to advance research in cross-border acquisitions.

A systematic literature review is conducted, and related propositions are advanced based on scientometric and bibliometric analysis of 146 papers published over 10 years about tacit knowledge transfer, innovation activities, industrial policy effect on merger decisions, top management experience and value creation in cross-border acquisition. First, the authors searched major themes with the help of Scopus, and later, the authors analysed all received literature with the help of VOS Viewer.

This review facilitates us to identify six clusters and main author keywords. These six clusters are the underlying six research streams, including RKT, cultural distances, value creation, absorptive capacity, innovation and reference to India and China.

Despite knowledge transfer constituting important antecedents and critical factors for the success of cross-border acquisitions, knowledge management in the acquired company through proper knowledge transfer and knowledge integration is not given enough attention. Current literature still fails to provide a holistic picture of how firms strategically manage knowledge post-acquisition. To the best of the authors’ knowledge, this study is the first to analyse the dynamics of knowledge transfer in cross-border acquisitions. The study is a novel attempt to relate current research themes to emerging areas of cross-border acquisitions.

This study aims to examine the combinations of internal and external knowledge flows between research and development (R&D) incumbents and start-ups in the context of open innovation. While there is a growing body of knowledge that has examined how, in a knowledge economy, a firm’s knowledge and innovation activities are closely linked, there is no systematic review available of the key antecedents, perspectives, phenomenon and outcomes of knowledge spillovers.

The authors have conducted dual-stage research. First, the authors conducted a systematic review of literature (97 research articles) by following the theories–contexts–methods framework and the antecedent-phenomenon-outcomes logic. The authors identified the key theories, contexts, methods, antecedents, phenomenon and outcomes of knowledge spillovers between R&D-driven incumbents and start-ups in the open innovation context. In the second stage, the findings of stage one were leveraged to advance a nomological network that depicts the strength of the relationship between the observable constructs that emerged from the review.

The findings demonstrate how knowledge spillovers can help incumbent organisations and start-ups to achieve improved innovation capabilities, R&D capacity, competitive advantage and the creation of knowledge ecosystems leading to improved firm performance. This study has important implications for practitioners and managers – it provides managers with important antecedents of knowledge spillover (knowledge capacities and knowledge types), which directly impact the R&D intensity and digitalisation driving open innovation. The emerging network showed that the antecedents of knowledge spillovers have a direct relationship with the creation of a knowledge ecosystem orchestrated by incumbents and that there is a very strong influence of knowledge capacities and knowledge types on the selection of external knowledge partners/sources.

This study has important implications for practitioners and managers. In particular, it provides managers with important antecedents of knowledge spillover (knowledge capacities and knowledge types), which directly impact the R&D intensity and digitalisation driving open innovation. This will enable managers to take important decisions about what knowledge capacities are required to achieve innovation outcomes. The findings suggest that managers of incumbent firms should be cautious when deciding to invest in knowledge sourcing from external partners. This choice may be driven by the absorptive capacity of the incumbent firm, market competition, protection of intellectual property and public policy supporting innovation and entrepreneurship.

Identification of the key antecedents, phenomenon and outcomes of knowledge spillovers between R&D-driven incumbents and start-ups in the open innovation context. The findings from Stage 1 helped us to advance a nomological network in Stage 2, which identifies the strength and influence of the various observable constructs (identified from the review) on each other. No prior study, to the best of the authors’ knowledge, has advanced a nomological network in the context of knowledge spillovers between R&D-driven incumbents and start-ups in the open innovation context.

This study aims to evaluate the safe haven property of several assets against the US and European stock markets during the Russo-Ukrainian War in a time–frequency framework.

This study uses the wavelet-based dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) methodology and wavelet coherence on daily returns for the S&P500, STOXX600 and 13 possible save haven assets.

The results show that wheat and corn are the best assets to use as hedges and safe havens for all types of investors. The second-ranked are energy commodities, which are hedges and safe havens for long-term investors. Gold, silver and palladium display hedging and safe haven qualities for medium- and long-term investment. However, cryptocurrencies, the Dow Jones sustainability index and Islamic indices do not act as safe havens for most holding periods.

These findings have significant implications for portfolio investment strategies in times of geopolitical risks.

The contributions of this study are twofold. First, several assets from different classes were analyzed as possible candidates for safe havens. Second, to the best of the authors’ knowledge, this is the first study to analyze safe haven property through different investment horizons for the US and the European stock market indices during the Russo-Ukrainian War.

The effects of gendered views on employee voice are of great importance for knowledge sharing within public universities. Yet, they are still neglected by current human resource management and entrepreneurship literature. While strengthening themselves by reinforcing the strengths and opportunities, public universities can generate entrepreneurial opportunities through various knowledge-sharing mechanisms, including social networks and employee voice. This became a crucial lever for public universities to leverage competitive advantages and to support entrepreneurial activities through network knowledge-based sharing. For this purpose, this study aims to examine the various aspects of entrepreneurship via the voice of employees, emphasizing the moderating effect of gender and the mediating role of social networks on the link between employee voice and the entrepreneurial atmosphere of universities.

The authors collected survey data from a cross-sectional sample of 335 employees engaged in entrepreneurship activities within public universities in an emerging economy context and analyzed the data using partial least squares structural equation modeling (PLS-SEM) with the Smart-PLS software.

The PLS-SEM analysis found that different dimensions of the university entrepreneurial climate (communication, knowledge sharing and innovative climate) positively impact members’ voices within public universities. This effect is amplified by social networks, which are crucial for spreading knowledge among faculty, thereby fostering a more open and collaborative academic environment.

When acting, the university top management team should encourage the generation and dissemination of entrepreneurial ideas to nurture a dynamic entrepreneurial atmosphere and social involvement, ultimately supporting sustainable competitive advantages through a culture of strategic knowledge sharing. The results have practical implications for university managers, entrepreneurship education actors, administrators, policymakers and entrepreneurial ecosystem actors, by demonstrating how social networks can amplify the dissemination of ideas and entrepreneurial spirit.

This research explores how entrepreneurship and social networks can help faculty members have a stronger influence in academic settings. It also fills in the gaps in knowledge about how human resource management and entrepreneurship can work together to create a more communicative and innovative academic environment. Additionally, this study brings new ideas to existing literature by looking at how gender differences can affect employee voice, particularly emphasizing the importance of women in leadership roles at universities. This study is also the first to delve into how entrepreneurship and social networks, along with gender perceptions, play a role in shaping the voice of employees in a public university.

This study aims to focus on sustainable supplier selection in a construction company considering a new multi-criteria decision-making (MCDM) method based on dominance-based rough set analysis. The inclusion of sustainability concept in industrial supply chains has started gaining momentum due to increased environmental protection awareness and social obligations. The selection of sustainable suppliers marks the first step toward accomplishing this objective. The problem of selecting the right suppliers fulfilling the sustainable requirements is a major MCDM problem since various conflicting factors are underplay in the selection process. The decision-makers are often confronted with inconsistent situations forcing them to make imprecise and vague decisions.

This paper presents a new method based on dominance-based rough sets for the selection of right suppliers based on sustainable performance criteria relying on the triple bottom line approach. The method applied has its distinct advantages by providing more transparency in dealing with the preference information provided by the decision-makers and is thus found to be more intuitive and appealing as a performance measurement tool.

The technique is easy to apply using “jrank” software package and devises results in the form of decision rules and ranking that further assist the decision-makers in making an informed decision that increases credibility in the decision-making process.

The novelty of this study of its kind is that uses the dominance-based rough set approach for a sustainable supplier selection process.

This study aims to reveal and prioritize the main barriers and challenges in front of the Logistics 4.0 transformation, which is the extension of Industry 4.0. Also, this study presents a roadmap for a company operating in developing countries to reduce and eliminate challenges and hurdles for each link in their supply chain.

A two-stage methodology was used in this study. First, a detailed literature review was conducted to identify the barriers to innovations compatible with Industry 4.0. Hence, barriers have been identified, including nine from the literature review. The best–worst method (BWM) is then used to determine these barriers’ weights and order of importance. To implement BWM, two-stage e-surveys are applied to experts.

The “Managerial and Economic Challenges” dimension is the most important, and “Regulatory and social challenges” is the least essential dimension among the main dimension. Moreover, financial constraints or capitals are the most critical barriers among the sub-barriers. This study gives the reader a comprehensive insight into how detected barriers affect digitalization performance. Therefore, this framework is a roadmap designed with a holistic view to guide manufacturers, logistics parties and even policy and decision-makers.

Theoretically and empirically identifies the potential barriers and challenges in the digital transformation of logistics is already missing at the desired level. From this point of view, to the best of the authors’ knowledge, this study is the first research that determines barriers based on the Logistics 4.0 model with an industrial perspective. One of the most important limitations of this study is that a total of nine dimensions were examined under only three basic barriers. Different alternatives can be identified for future studies.