bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing experts’ and users’ perspectives on the use of password workarounds and the risk of data breaches
Authors: Rooney Michael J , Levy Yair , Li Wei , Kumar Ajoy 
Published: July 2024

Purpose
The increased use of Information Systems (IS) as a working tool for employees increases the number of accounts and passwords required. Despite being more aware of password entropy, users still often participate in deviant password behaviors, known as “password workarounds” or “shadow security.” These deviant password behaviors can put individuals and organizations at risk, resulting in a data breach. This paper aims to engage IS users and Subject Matter Experts (SMEs), focused on designing, developing and empirically validating the Password Workaround Cybersecurity Risk Taxonomy (PaWoCyRiT) – a 2x2 taxonomy constructed by aggregated scores of perceived cybersecurity risks from Password Workarounds (PWWAs) techniques and their usage frequency.

Design/methodology/approach
This research study was a developmental design conducted in three phases using qualitative and quantitative methods: (1) A set of 10 PWWAs that were identified from the literature were validated by SMEs along with their perspectives on the PWWAs usage and risk for data breach; (2) A pilot study was conducted to ensure reliability and validity and identify if any measurement issues would have hindered the results and (3) The main study data collection was conducted with a large group of IS users, where also they reported on coworkers' engagement frequencies related to the PWWAs.

Findings
The results indicate that statistically significant differences were found between SMEs and IS users in their aggregated perceptions of risks of the PWWAs in causing a data breach, with IS users perceiving higher risks. Engagement patterns varied between the two groups, as well as factors like years of IS experience, gender and job level had statistically significant differences among groups.

Practical implications
The PaWoCyRiT taxonomy that the we have developed and empirically validated is a handy tool for organizational cyber risk officers. The taxonomy provides organizations with a quantifiable means to assess and ultimately mitigate cybersecurity risks.

Social implications
Passwords have been used for a long time to grant controlled access to classified spaces, electronics, networks and more. However, the dramatic increase in user accounts over the past few decades has exposed the realization that technological measures alone cannot ensure a high level of IS security; this leaves the end-users holding a critical role in protecting their organization and personal information. Thus, the taxonomy that the authors have developed and empirically validated provides broader implications for society, as it assists organizations in all industries with the ability to mitigate the risks of data breaches that can result from PWWAs.

Originality/value
The taxonomy the we have developed and validated, the PaWoCyRiT, provides organizations with insights into password-related risks and behaviors that may lead to data breaches.
AI is not careful: approach to the stock market and preference for AI advisor
Authors: Koo Jieun 
Published: July 2024

PurposeFinancial institutions actively seek to leverage the capabilities of artificial intelligence (AI) across diverse operations in the field. Especially, the adoption of AI advisors has a significant impact on trading and investing in the stock market. The purpose of this paper is to test whether AI advisors are less preferred compared to human advisors for investing and whether this algorithm aversion diminishes for trading.Design/methodology/approachThe four hypotheses regarding the direct and indirect relationships between variables are tested in five experiments that collect data from Prolific.FindingsThe results of the five experiments reveal that, for investing, consumers are less likely to use AI advisors in comparison to human advisors. However, this reluctance to AI advisors decreases for trading. The author identifies the perceived importance of careful decision-making for investing and trading as the psychological mechanism. Specifically, the greater emphasis on careful decision-making in investing, as compared to trading, leads to consumers’ tendency to avoid AI advisors.Originality/valueThis research is the first to investigate whether algorithm aversion varies based on whether one’s approach to the stock market is investing or trading. Furthermore, it contributes to the literature on carefulness by exploring the interaction between a stock market approach and the lay belief that algorithms lack the capability to deliberate carefully.
Exploring new realms or losing touch? Assessing public beliefs about tourism in the metaverse–a big-data approach
Authors: Mahmoud Ali B. , Fuxman Leonora , Asaad Yousra , Solakis Konstantinos 
Published: July 2024

Purpose
The Metaverse is rapidly reshaping the understanding of tourism, yet the public perception of this new domain remains largely uncharted empirically. This paper aims to build on the technology acceptance model (TAM) and diffusion of innovations theory (DIT) to fill this gap, offering crucial insights that could inform scholars and practitioners in both the tourism and technology sectors.

Design/methodology/approach
Using a big-data approach, the authors applied machine learning to scrape comments made by social media users on recent popular posts or videos related to tourism in the Metaverse from three prominent social media platforms. The cleaning process narrowed down 15,461 comments to 2,650, which were then analysed using thematic, emotion and sentiment analysis techniques.

Findings
The thematic analysis revealed that virtual tourism evokes a complex range of public beliefs. While many express awe and excitement toward its immersive capabilities, others remain sceptical about authenticity compared to physical travel. Additional themes show people draw comparisons to real-world tourism, discuss technology’s role and note educational value and novelty. However, some comments raise concerns about potential societal harms, exploitation and mental health impacts. Sentiment analysis found over half of the comments positive, though some were negative. Emotion analysis showed contentment, happiness and excitement as most frequent, though sadness, worry and loneliness also featured. Overall, perceptions of Metaverse tourism encompass enthusiasm yet substantial ambivalence.

Originality/value
To the best of the authors’ knowledge, this study is one of the first to comprehensively analyse public discussions on Metaverse tourism. It takes TAM and Rogers’s DIT a step further and provides fresh insights into how these theories can be employed in the emerging field of Metaverse tourism. The themes revealed new conceptual insights into multidimensional factors shaping public beliefs about Metaverse tourism and thus informing scholarly research on virtual interaction and technology acceptance regarding Metaverse tourism. In addition, the results can help tourism providers, platforms and marketers address salient public beliefs and sentiments/attitudes in developing marketing offerings, experiences and communications. Over time, this analysis methodology can be used to track the evolving public perceptions of Metaverse tourism.
Examining the minimal combined effects of gender and minoritized racial/ethnic identity among academic entrepreneurs
Authors: Duval-Couetil Nathalie , Epstein Alanna , Huang-Saad Aileen 
Published: July 2024

PurposeThis study examined differences related to gender and racial/ethnic identity among academic researchers participating in the National Science Foundation’s “Innovation-Corps” (NSF I-Corps) entrepreneurship training program. Drawing from prior research in the fields of technology entrepreneurship and science, technology, engineering and mathematics (STEM) education, this study addresses the goal of broadening participation in academic entrepreneurship.Design/methodology/approachUsing ANOVA and MANOVA analyses, we tested for differences by gender and minoritized racial/ethnic identity for four variables considered pertinent to successful program outcomes: (1) prior entrepreneurial experience, (2) perceptions of instructional climate, (3) quality of project team interactions and (4) future entrepreneurial intention. The sample includes faculty (n = 434) and graduate students (n = 406) who completed pre- and post-course surveys related to a seven-week nationwide training program.FindingsThe findings show that group differences based on minoritized racial/ethnic identity compared with majority group identity were largely not evident. Previous research findings were replicated for only one variable, indicating that women report lower amounts of total prior entrepreneurial experience than men, but no gender differences were found for other study variables.Originality/valueOur analyses respond to repeated calls for research in the fields of entrepreneurship and STEM education to simultaneously examine intersecting minoritized and/or under-represented social identities to inform recruitment and retention efforts. The unique and large I-Corps national dataset offered the statistical power to quantitatively test for differences between identity groups. We discuss the implications of the inconsistencies in our analyses with prior findings, such as the need to consider selection bias.
Flexicurity and employment inflows in the EU28 countries: a panel data analysis
Authors: Ferent-Pipas Marina 
Published: July 2024

PurposeThis paper examines the relationship between flexicurity and employment inflows in the EU28 countries over the 2007–2019 period. Flexicurity is defined as the mix of flexible contractual arrangements, social security systems, active labor market policies and lifelong learning strategies.Design/methodology/approachUsing two-way fixed effects two-stage least squares, we estimate the employment inflows as a function of an equal-weighted flexicurity composite indicator and other labor market, economic and business environment characteristics. To ensure the robustness of results, in additional specifications, we test the sensitivity of the flexicurity’s coefficient to: (1) the change of instruments; (2) the removal of different non-core variables and (3) the consideration of recessionary periods European regions. In addition, we estimate regressions with separate flexicurity components and with differently constructed flexicurity indices.FindingsIn all the estimations, increased flexicurity efforts are positively related to employment inflows. Increased flexicurity efforts benefit Eastern European countries more than the Northern and Anglo-Saxon groups. Not only a synergistic policy action that uses an equal combination of the four pillars of flexicurity has a positive impact on the employment inflow rate. Strategies that give more weight to the formation of skills seem to favor the labor market reinsertion most.Originality/valueTo our knowledge, this is the first comprehensive study in the flexicurity–employment inflows literature since it: (1) follows all the European Union countries over more than a decade; (2) brings some tentative findings on the socio-cultural moderation of flexicurity’s impact on employment inflows and (3) explores different country-level flexicurity indices.
Digitisation of franchising supply chain impact on franchisor performance: a longitudinal case study of a coffee retail chain
Authors: Vlachos Ilias , Zisimopoulos Apostolos , Tsoulfas Giannis T. 
Published: July 2024

PurposeFranchising contributes significantly to national economies but is overlooked in supply chain literature. This study aims to contribute to the franchising and supply chain literature by examining how the digitisation of the franchising supply chain improves firm performance.Design/methodology/approachA single longitudinal case study approach was selected to investigate how a leading coffee brand digitised its franchising supply chain. Resource constraints theory and agency theory provide the theoretical framework. Data collection included both qualitative and quantitative data. Over two years, chronological, supply chain and thematic analyses and interpretation uncovered important findings and developed four research propositions.FindingsFindings show that digitisation can impact performance in eight areas: Resource management, Resource constraints, Efficiency, Business-to-Business (B2B)/Business-To-Customer (B2C) links, Rapid expansion, Risk mitigation, Information asymmetries and Faster supply chain responses. Four digital technologies (advanced analytics, Internet of Things, Autonomous Mobile Robots and B2B e-shop) impacted three franchisor functions (Machine maintenance, Inventory management, Franchisee and end-customer relations). The study develops four research propositions on how digitisation impacts performance in terms of (1) resource monitoring and control, (2) learning and knowledge creation, (3) coordination and collaboration and (4) competition.Originality/valueFranchising supply chains have been overlooked in the literature; this study provides insights into using resource constraints theory and agency theory complementarily to explain supply chain digitisation and provides actionable practical implications for selecting, implementing and continuously improving Industry 4.0 technologies in franchising supply chains.
Transformative learning with ChatGPT: analyzing adoption trends and implications for business management students in India
Authors: Sudan Tapas , Hans Arjun , Taggar Rashi 
Published: July 2024

Purpose
The intricate dynamics of ChatGPT adoption among Indian students are discussed while exploring the factors outlined by Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). By assessing these factors, this study aims to unravel their impact on the behavioral intention to use ChatGPT.

Design/methodology/approach
While evaluating ChatGPT's adoption dynamics, this study analyses the UTAUT2 core factors and perceived benefits. Real-time data from 638 business and management students in India were collected through purposive sampling and a cross-sectional survey. An in-depth examination using IBM SPSS and AMOS revealed the patterns that regulate ChatGPT reception in educational settings.

Findings
Habit emerges as a powerful predictor, which aligns with the Habit Loop Theory's cues, routine and rewards. Perceived benefits significantly influence adoption, and traditional factors like performance expectancy and social influence exert no influence. The insignificance of effort expectancy challenges conventional understanding, unveiling novel aspects of student tech adoption.

Social implications
There is a need for guidelines to ensure fair and responsible use of ChatGPT among students. While ChatGPT presents advantages like task automation and personalized learning, integrating it into the existing education system requires careful planning to harness its benefits effectively.

Originality/value
With the recent introduction of Generative-AI tools, understanding student acceptance and application is essential. This research sheds light on this emerging technology, emphasizing the importance of analyzing technology acceptance for its successful adoption.
Leadership, knowledge dynamics and dual-path innovation: unravelling the synergy in Pakistan’s manufacturing sector
Authors: Waseel Abdul Hakeem , Zhang Jianhua , Zia Umair , Mohsin Malik Muhammad , Hussain Sajjad 
Published: July 2024

Purpose
With ambidextrous innovation (AI) gaining paramount importance in the manufacturing sectors of emerging markets, this research aim to explore how leadership and management support (LMS) amplify this type of innovation by leveraging knowledge sources (KS). The study further probes the knowledge management capability (KMC) as moderating effect between KS and AI.

Design/methodology/approach
Using the convenient random sampling technique of a sample of 340 professionals within Pakistan’s manufacturing realm, data was collated via a structured questionnaire. The subsequent analysis harnessed the power of the variance-based partial least squares structural equation modelling approach.

Findings
This research underscores the pivotal role of LMS in elevating both facets of AI i.e. exploitative innovation (ERI) and exploratory innovation (ERT). KS emerge as a vital intermediary factor that bridges LMS with both types of innovation. Notably, the potency of KS in driving AI is significantly boosted by an organization’s KMC.

Originality/value
This study fills existing gaps in contemporary research by offering a nuanced perspective on how LMS enrich an organization’s dual innovation spectrum via KS. It sheds light on the symbiotic interplay of leadership, knowledge flows and innovation in Pakistan’s burgeoning manufacturing sector.
One psychopathic route to an unsuccessful life. Psychopathy and life outcomes in Generation 3 of the Cambridge study in delinquent development
Authors: Zara Georgia , Bergstrøm Henriette , Farrington David P. 
Published: July 2024

Purpose
This study aims to examine whether psychopathic traits are associated with “unsuccessful” life outcomes in a community sample. While it is not easy to define what a successful life is, as it varies by context and developmental stage, there is a consensus in psychological research on what constitutes an unsuccessful life, as measured by the revised Unsuccessful Life Scale. This concept of unsuccessful life encompasses areas such as family and health, alcohol and drug use and work and job satisfaction, which, when compromised, are essential components of an unsuccessful 21st-century life.

Design/methodology/approach
The study continues the work carried out in the prospective longitudinal Cambridge Study in Delinquent Development by including the offspring (n = 551 G3 females and males) of the original 411 G2 males.

Findings
A small proportion of G3 individuals (6.5%, n = 36) were having an unsuccessful life, and 23.3% (n = 124) of them were exhibiting a high level of psychopathic traits as measured by the PCL:SV. The results suggest that some psychopathic traits are an integral part of an unsuccessful mix. For instance, for both males and females, drug use and physical fights were significantly associated with psychopathic traits. However, there were some differences, where a wider range of unsuccessful outcomes was associated with psychopathic traits in males (e.g. unsatisfactory accommodation) compared to females (e.g. unsatisfactory intimate relationships).

Originality/value
It seems that the costs of psychopathic traits outweigh the benefits when it comes to success in life. The implications of these findings are discussed.
Navigating ChatGPT: catalyst or challenge for Indonesian youth in digital entrepreneurship?
Authors: Herani Rina , Angela Jovita 
Published: July 2024

PurposeThis study aims to explore both the drivers (performance expectancy and perceived usefulness of ChatGPT) and the barrier (effort expectancy) that Indonesian youth encounter when adopting generative AI technology, such as ChatGPT, as they pursue digital entrepreneurship.Design/methodology/approachThis study utilizes Hayes' Process Model to evaluate the proposed hypotheses through survey data collected from 518 Indonesian youth.FindingsThis study's findings highlight a paradoxical relationship that emerges when effort expectancy intersects with performance expectancy and perceived usefulness of ChatGPT. Specifically, we discovered that when young individuals perceive the adoption of generative AI technology as requiring significant effort, their motivation to engage in digital entrepreneurship is significantly enhanced if they also view the tool as highly useful and beneficial to their future business endeavors.Practical implicationsThe findings provide valuable insights for educators and policymakers focused on advancing digital entrepreneurship in developing nations through the integration of generative AI technology.Originality/valueOur study enriches an underexplored niche within the field of entrepreneurship by examining the intersection of Indonesian youth, generative AI technology and digital entrepreneurship. By incorporating the Expectancy-Value Theory, it brings a fresh perspective to the study of paradoxical relationships in contemporary research in this domain.
Predicting stock market crashes in MENA regions: study based on the irrationality of investor behavior and the NARX model
Authors: Ben Yaala Sirine , Henchiri Jamel Eddine 
Published: July 2024

Purpose
This study aims to predict stock market crises in the Middle East North Africa (MENA) regions by leveraging the nonlinear autoregressive neural network with exogenous inputs (NARX) model with two measures of investor sentiment: the ARMS indicator and Google Trends' search volume of positive and negative words.

Design/methodology/approach
Employing a novel approach, this study utilizes the NARX model with ten neurons in the hidden layer and the Levenberg–Marquardt training algorithm. It evaluates model performance through learning, validation and test errors, as well as correlation analysis between predicted and actual crises.

Findings
The NARX model, incorporating investor sentiment, has proven to be a reliable tool for forecasting crises, helping market participants understand data complexity and avoid crisis consequences. The divergence in how investors interpret market news, with some focusing solely on negative developments and others valuing positive outcomes, highlights the predictive nature of the optimistic and pessimistic sentiments captured by the model.

Research limitations/implications
This study advocates for integrating behavioral approaches into stock market crisis prediction, highlighting the significance of investor sentiment and deep learning. It advances crisis mechanism understanding and opens avenues in behavioral finance. Integration of these findings into finance and economics education could enhance students' risk understanding and mitigation strategies.

Practical implications
The adoption of NARX models, incorporating investor sentiment, empowers market participants to proactively manage crises, adjust strategies, enhance asset protection and make informed decisions. These models enable them to minimize losses, maximize returns and diversify portfolios effectively in response to market fluctuations. These insights also guide policymakers such as governments, regulatory institutions and financial organizations in formulating crisis prevention and mitigation policies, bolstering economic and financial stability.

Social implications
This research reduces economic uncertainty, safeguards individuals' savings and investments and promotes a stable financial climate.

Originality/value
This study is one of the first attempts to demonstrate the detection and prediction of stock market crises, specifically in the MENA stock market, using the NARX model. It offers a robust forecasting model using machine learning and investor sentiment, providing decision-making support for investment strategies and policy development aimed at enhancing financial and economic stability.