Search results

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.

The shape of a product plays a crucial role in shaping consumer behavior. Despite the voluminous research on factors influencing consumers’ shape preferences, there remains a limited understanding of how the busy mindset, a mentality increasingly emphasized by marketing campaigns, works. This study aims to fill this gap by exploring the relationship between a busy mindset and the preference for angular-shaped versus circular-shaped products and brand logos.

This research consists of seven experimental studies using various shape stimuli, distinct manipulations of busy mindset, different assessments of shape preference and samples drawn from multiple countries.

The findings reveal that a busy mindset leads to a preference for angular shapes over circular ones by amplifying the need for uniqueness. In addition, these effects are attenuated when products are scarce.

This research represents one of the pioneering efforts to study the role of a busy mindset on consumers’ aesthetic preferences. Beyond yielding insights for practitioners into visual marketing, this research contributes to the theories on the busy mindset and shape preference.

Based on social cognitive theory, this study aims to explore the psychological mechanism behind consumer verification behavior following tourism e-commerce live-streaming.

Based on grounded theory, data were collected through 20 semi-structured in-depth interviews and analyzed.

This study identified that companies commonly use reminder messages and secondary promotions to facilitate the verification of tourism live-streaming products. Throughout this process, consumers undergo various psychologies related to verification. Specifically, they experience four positive verification psychologies: fear of missing out, anticipated emotions, status self-esteem and promotional perception. They also encounter two negative verification psychologies: psychological reactance and invasiveness. In addition, environmental factors such as the type of tourism live-streaming products and tourism destinations, along with individual trait factors like cognitive miserliness, tourism experience, autonomy, regulatory mode and impulsiveness, play significant roles in shaping verification behavior. These factors collectively influence the formation of verification behavior.

This study can provide recommendations for tourism companies to conduct marketing events following live-streaming. It is one of the earlier comprehensive studies discussing how to promote verification behavior following tourism e-commerce live-streaming. It helps to understand the psychological mechanism underlying the formation of verification behavior.

This study is exploratory in nature and designed to address poorly documented issues in the literature. The dimensions of regional distribution or spatial organisation of Industry 4.0 (I4.0), including the potential role of clusters, have only recently been addressed, with most available studies focusing on advanced, mainly Western European countries. Although developing fast, the literature on I4.0 in other countries, such as the Central and Eastern European or post-transition economies like Poland, needs to pay more attention to the spatial distribution or geographical and organisational aspects. In response to the identified knowledge gap, this paper aims to identify the role of clusters in the transformation towards I4.0. This explains why clusters may matter for advancing the fourth digital transformation, how advanced in implementing I4.0 solutions are the residents of Polish clusters and how they perceive the advantages of cluster membership for such implementation. Finally, it seeks to formulate policy recommendations based on the evidence gathered.

The methodology used in this study combines quantitative analysis of secondary data from a cluster benchmarking survey with a case study approach. The benchmarking survey, conducted by the polish agency for enterprise development in 2021, gathered responses from 435 cluster members and 41 cluster managers, representing an estimated 57% of the current clusters in Poland. In addition to quantitative analysis, a case study approach was used, incorporating primary sources such as interview with cluster managers and surveys of cluster members, as well as secondary sources like company documents and information from cluster organisation websites. Statistical analysis involved assessing the relationship between technology implementation and the adoption of management systems, as well as exploring potential correlations between technology use and company characteristics such as revenue, export revenue share and number of employees using Pearson correlation coefficient.

In Poland, implementing I4.0 technologies by cluster companies is still modest. The cluster has influenced the use of I4.0 technologies in 23% of surveyed companies. Every second surveyed company declared a positive impact of a cluster on technological advancement. The use of I4.0 technologies is not correlated with the revenue of clustered companies. A rather bleak picture emerges from the results, revealing a need for more interest among cluster members in advancing I4.0 technologies. This may be due to a comfortable situation in which firms still enjoy alternative competitive advantages that do not force them to seek new advanced advantages brought about by I4.0. It also reflects the sober approach and awareness of associated high costs and necessary investments, which are paramount and prevent successful I4.0 implementation.

The limitations inherent in this study reflect the scarcity of the available data. This paper draws on the elementary survey administered centrally and is confined by the type of questions asked. The empirical section focuses on an important, though only one selected sector of the economy – the automotive industry. Nevertheless, the diagnosis of the Polish cluster’s role in advancing I4.0 should complement the existing literature.

The exploratory study concludes with policy recommendations and sets the stage for more detailed studies. Amidst the research’s limitations, this study pioneers a path for future comprehensive investigations, enabling a deeper understanding of Polish clusters’ maturity in I4.0 adoption. By comparing the authors’ analysis of the Polish Automotive Group (PGM) cluster with existing literature, the authors uncover a distinct disparity between the theoretical prominence of cluster catalysis and the current Polish reality. Future detailed dedicated enquiries will address these constraints and provide a more comprehensive map of Polish clusters’ I4.0 maturity.

This study identifies patterns of I4.0 implementation and diagnoses the role of clusters in the transformation towards I4.0. It investigates how advanced is the adoption of I4.0 solutions among the residents of Polish clusters and how they perceive the advantages of cluster membership for such transformation. Special attention was paid to the analysis of the automotive sector. Comparing the conclusions drawn from the analysis of the Polish PGM cluster in this case study to those from the literature on the subject, it becomes clear that the catalytic role of clusters in the implementation of I4.0 technologies by enterprises, as emphasised in the literature, is not yet fully reflected in the Polish reality.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

The agri-food industry is experiencing a revolutionary shift due to the introduction of Industry 4.0 technologies to improve efficiency, transparency and sustainability. The importance of agri-food supply chains (AFSC) in promoting sustainability is expanding as the globe struggles with issues including resource scarcity, climate change and population growth. In order to better understand how Industry 4.0 might improve sustainability in a world that is changing quickly, this work aims to focus on identifying various sustainability assessment factors influencing AFSC to increase overall sustainability, minimize resource consumption, cut waste and streamline operations.

Important sustainability assessment factors are identified from the past academic literature and are then validated using the fuzzy-Delphi method. A method called decision-making trial and evaluation laboratory (DEMATEL) is used to examine and analyze structural models with complex causal linkages. The results are then validated using sensitivity analysis.

The factors that emerged as the highest ranked for evaluating the sustainability of Industry 4.0 in AFSC are market competitiveness, and knowledge and skill development, followed by resource efficiency. Industry 4.0 technologies are essential for increasing the marketability of agricultural products because of the major implications of market competitiveness. The significance of knowledge and skill development draws attention to Industry 4.0’s contribution to the promotion of chances for farmers and agricultural employees to increase their capability.

By outlining the nexus between Industry 4.0 technologies and sustainability, the study presents a comprehensive framework that would be relevant for researchers, policymakers and industry stakeholders who want to leverage Industry 4.0 technology to build more sustainable AFSC in the future. The study findings can help the farmers or producers make sensible choices that adhere to sustainability standards and guarantee long-term financial viability.

The originality of this work lies in the identification of sustainability assessment factors especially for AFSC in the era of digitalization which has not been discussed previously.

The purpose of the research is to recognize and rank the barriers preventing Industry 4.0 (I4.0) adoption in Bangladesh’s food and beverage industries. It aims to highlight the major difficulties the sector is currently facing and offer a hierarchical framework for evaluating these barriers.

An exhaustive literature review was conducted along with expert interviews with academics and industry professionals to identify and assess the barriers. The interpretive structural modeling and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (ISM-MICMAC) approach was used to classify the identified barriers based on driving and dependent power and understand the interrelationships among them.

A total of 20 barriers to I4.0 adoption in the food and beverage sector of Bangladesh were identified. The top tier of significant barriers includes “Financial constraints,” “Lack of management support,” “Lack of research and development team,” “Lack of adequate skills in the workforce,” “Lack of digital strategy alongside resource scarcity” and “Employee resistance to change.”.

The created hierarchical framework offers a useful tool for dealing with the noted barriers and assisting with the successful adoption of I4.0 in the food and beverage sector. Businesses can overcome financial constraints by allocating enough resources and obtaining management support. By creating a focused research and development team and giving the workforce the necessary training, the lack of knowledge and skills can be overcome. By developing a thorough digital strategy and making sure that the necessary resources are available, resource scarcity can be overcome. Furthermore, effective change management methods can support the adoption of I4.0 technologies by overcoming employee resistance to change.

By concentrating specifically on the difficulties encountered by the food and beverage industries in Bangladesh as it attempts to adopt I4.0, this study contributes to the body of existing literature. The study’s originality lies in its thorough analysis of barriers and the use of the ISM-MICMAC approach to comprehend how these barriers interact with one another.

This study aims to investigate how phishers apply persuasion principles and construct deceptive URLs in mobile instant messaging (MIM) phishing.

In total, 67 examples of real-world MIM phishing attacks were collected from various online sources. Each example was coded using established guidelines from the literature to identify the persuasion principles, and the URL construction techniques employed.

The principles of social proof, liking and authority were the most widely used in MIM phishing, followed by scarcity and reciprocity. Most phishing examples use three persuasion principles, often a combination of authority, liking and social proof. In contrast to email phishing but similar to vishing, the social proof principle was the most commonly used in MIM phishing. Phishers implement the social proof principle in different ways, most commonly by claiming that other users have already acted (e.g. crafting messages that indicate the sender has already benefited from the scam). In contrast to email, retail and fintech companies are the most commonly targeted in MIM phishing. Furthermore, phishers created deceptive URLs using multiple URL obfuscation techniques, often using spoofed domains, to make the URL complex by adding random characters and using homoglyphs.

The insights from this study provide a theoretical foundation for future research on the psychological aspects of phishing in MIM apps. The study provides recommendations that software developers should consider when developing automated anti-phishing solutions for MIM apps and proposes a set of MIM phishing awareness training tips.

This paper aims to disentangle Chinese-English-rich resources linguistic and speaker timbre features, achieving cross-lingual speaker transfer for Cambodian.

This study introduces a novel approach: the construction of a cross-lingual feature disentangler coupled with the integration of time-frequency attention adaptive normalization to proficiently convert Cambodian speaker timbre into Chinese-English without altering the underlying Cambodian speech content.

Considering the limited availability of multi-speaker corpora in Cambodia, conventional methods have demonstrated subpar performance in Cambodian speaker voice transfer.

The originality of this study lies in the effectiveness of the disentanglement process and precise control over speaker timbre feature transfer.