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This study aims to investigate how message sidedness affects the impact of fake news posted on social media on consumers' emotional responses.

The study involves a face-tracking experiment in which 198 participants were exposed to different fake news messages concerning the COVID-19 vaccine. Specifically, participants were exposed to fake news using (1) a one-sided negative fake news message in which the message was entirely unfavorable and (2) a two-sided fake news message in which the negative message was mixed with favorable information. Noldus FaceReader 7, an automatic facial expression recognition system, was used to recognize participants' emotions as they read fake news. The authors sampled 17,450 observations of participants' emotional responses.

The results provide evidence of the significant influence of message sidedness on consumers' emotional valence and arousal. Specifically, two-sided fake news positively influences emotional valence, while one-sided fake news positively influences emotional arousal.

The current study demonstrates that research on fake news posted on social media may particularly benefit from insights regarding the potential but often overlooked importance of strategic design choices in fake news messages and their impact on consumers' emotional responses.

This study aims to investigate the impact of message framing (emotional vs rational) on social media users' ability to accurately detect information and their intention to share messages about the COVID-19 vaccine.

Using an experimental design approach, the authors recruited 600 adult participants via a crowdsourcing platform. Participants were randomly assigned to receive emotional or rational messages and their ability to accurately detect information and intention to share messages were assessed.

The results showed a significant multivariate effect of message framing on both the detection of accurate information and intention to share (p < 0.001). Participants who received emotional messages demonstrated better performance in the detection and sharing task than those who received rational messages. Gender and age also had significant main effects on the outcomes, with women performing better than men and younger participants performing better than older participants in detecting the accuracy of information. The interaction effects of the independent variables were not statistically significant (p = 0.098).

The findings highlight the importance of considering emotional factors in combating the spread of messages about the COVID-19 vaccine on social media. Practitioners responsible for social media content should strengthen the content review mechanism, with an emphasis on screening content with high emotional arousal.

The study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.

The study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.

The F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.

Although the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.

The findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.

The study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.

The study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.

This paper aims to conduct an interdisciplinary systematic literature review (SLR) of fake news research and to advance the socio-technical understanding of digital information practices and platforms in business and management studies.

The paper applies a focused, SLR method to analyze articles on fake news in business and management journals from 2010 to 2020.

The paper analyzes the definition, theoretical frameworks, methods and research gaps of fake news in the business and management domains. It also identifies some promising research opportunities for future scholars.

The paper offers practical implications for various stakeholders who are affected by or involved in fake news dissemination, such as brands, consumers and policymakers. It provides recommendations to cope with the challenges and risks of fake news.

The paper discusses the social consequences and future threats of fake news, especially in relation to social networking and social media. It calls for more awareness and responsibility from online communities to prevent and combat fake news.

The paper contributes to the literature on information management by showing the importance and consequences of fake news sharing for societies. It is among the frontier systematic reviews in the field that covers studies from different disciplines and focuses on business and management studies.

The rapid increase of use of online platforms by the customers in the hospitality and tourism industry has invited the needs for using digital platforms by the concerned industry. In such a scenario, the purpose of this study is to examine how adoption of blockchain technology in hospitality and tourism industry could impact the sustainability performance of the organizations under the moderating influence of technological turbulence and senior leadership support.

With the help of existing literature, stakeholder theory and dynamic capability view (DCV), a theoretical model is proposed. It was validated using the PLS-SEM technique with 311 respondents who have different managerial positions in the hospitality and tourism industry. The proposed theoretical model is unique and effective as it has high explanatory power.

The study demonstrates the importance of adopting BCT in the hospitality and tourism sector and how it could improve the sustainability performance of organizations in that sector. This study also finds that there is a significant moderating impact of technological turbulence and senior leadership support on such organizations that adopt BCT.

This study provides valuable inputs to practitioners in the industry by showing how adopting BCT can improve their sustainability performance. The study also demonstrates that leaders and the managers should support adopting BCT in their organizations and they can help to overcome any technological challenges that might come up while adopting it.

The present study proposes a unique theoretical model which was also validated using a statistical approach. Moreover, both stakeholder theory and dynamic capability view were integrated to propose the theoretical model, which is a novel attempt so far as adoption of BCT in hospitality and tourism industry is concerned.

Business models are increasingly recognized as a concept to support innovation in organizations. The implementation and operation of a new or altered business model involves the (re-)design of an organization's business processes and their successful execution. This study reviews and synthesizes the existing body of literature to guide organizations in systematically moving from a business model design to the implementation and operation of the business model through their underlying business processes.

A systematic literature review of the methods that bridge business models and business processes is performed. The selected 34 studies are classified according to the method's characteristics and the support in the design, implementation and operation of business models.

The results of the systematic review provide an overview of existing methods that organizations can adopt when moving from business model design into the implementation and operation of their business model using processes.

This work provides a comprehensive overview and detailed insight into the existing methods that align business models and business processes. It increases the understanding on how these two concepts can be synthesized to support more effective digital innovation in organizations. Based on the review results, knowledge gaps are identified and an agenda for future research bridging the fields of business models and business processes is proposed.

The purpose of this paper was to determine the factors that enable entrepreneurial opportunity recognition and the significant role of education and training in enhancing opportunity recognition.

This paper follows a systematic literature review method to answer the research questions. A systematic literature review allows us to determine the work carried out to date, how it was done, assess literature and report all relevant research. The authors have used the Preferred Reporting Items for Systematic and Meta-Analysis procedure.

The findings of this study showed that prior knowledge, social networks, external environment, entrepreneurial alertness, creativity, self-efficacy and entrepreneurial passion are the main factors that play a role in the opportunity recognition process. The authors were also able to establish the importance of education and training in enhancing opportunity recognition. Experiential learning is at the forefront of education methods used to improve prior knowledge and experience that directly impact the ability to recognize entrepreneurial opportunities.

The paper provides human resource development practitioners and entrepreneurship educators with factors that determine entrepreneurial opportunity recognition. It pinpoints the factors that can be exploited in enhancing employees and novice entrepreneurs’ ability to recognize viable entrepreneurial opportunities.

Opportunity recognition is recognized as the first step in the entrepreneurship process. Therefore, it is crucial for entrepreneurs to have the ability to recognize opportunities that are viable. Understanding the factors that contribute to a successful opportunity recognition is important. In addition, the role of education and training in opportunity recognition and enhancing entrepreneurial opportunity recognition cannot be overlooked.

The goals of the contemporary environment in this new era of the Internet of Things (IoT), digital technologies (DTs) and smartisation are to enhance economic, social and environmental sustainability while also concentrating on the citizens' quality of life. As these initiatives advance, more determination is required to offer effective approaches to the problem posed by the accomplishment of the Sustainable City Project in Nigeria as a developing nation. To address these problems and facilitate the process for Nigeria's major cities to become ‘smart cities’, universities, research institutions and other stakeholders must collaborate alongside. This chapter aims to establish a model or framework that addresses urban intelligence, social inclusion, resilience and technological innovation, mobility, urbanisation and residents' quality of life. The reviews of the characteristics and management of smart cities in developed countries were documented to serve as a comparison study of the cities in African sub-Saharan regions. This will assist in building models that can produce predictions about possible smart solutions in the areas of mobility, urban infrastructure and ecological problems brought on by climate change in African cities. This chapter brings attention to the body of knowledge by envisioning the benefits to the government and citizens in making appropriate decisions to enhance sustainable development, a better resilience environment, improved infrastructure, smart city environments and residents' quality of life. The study's implications centre on how the government could prioritise urban features and services as indicated in the smart cities framework.

The objective of this paper is to evaluate whether the data from consignors, logistics service providers (LSPs) and consignees contribute to the prediction of air transport shipment delays in a machine learning application.

The research database contained 2,244 air freight intercontinental shipments to 4 automotive production plants in Latin America. Different algorithm classes were tested in the knowledge discovery in databases (KDD) process: support vector machine (SVM), random forest (RF), artificial neural networks (ANN) and k-nearest neighbors (KNN).

Shipper, consignee and LSP data attribute selection achieved 86% accuracy through the RF algorithm in a cross-validation scenario after a combined class balancing procedure.

These findings expand the current literature on machine learning applied to air freight delay management, which has mostly focused on weather, airport structure, flight schedule, ground delay and congestion as explanatory attributes.

This study aims to cover the overall gamut of rapid prototyping processes and biomaterials used for the fabrication of occlusal splints in a comprehensive manner and elucidate the characteristics of the materials, which are essential in determining their clinical efficacy when exposed to oral surroundings.

A collective analysis of published articles covering the use of rapid prototyping technologies in the fabrication of occlusal splints, including manufacturing workflow description and essential properties (mechanical- and thermal-based) evaluation of biocompatible splinting materials, was performed.

Without advances in rapid prototyping processes and materials engineering, occlusal splints would tend to underperform clinically due to biomechanical limitations.

Three-dimensional printing can improve the process capabilities for commercial customization of biomechanically efficient occlusal splints.

Rapid technological advancement in dentistry with the extensive utilization of rapid prototyping processes, intra-oral scanners and novel biomaterial seems to be the potential breakthrough in the fabrication of customized occlusal splints which have endorsed occlusal splint therapy (OST) as a cornerstone of orthodontic treatment.