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The purpose of this study is to understand user perceptions and misconceptions regarding security tools. Security and privacy-preserving tools (for brevity, the authors term them as “security tools” in this paper, unless otherwise specified) are designed to protect the security and privacy of people in the digital environment. However, inappropriate use of these tools can lead to unexpected consequences that are preventable. Hence, it is significant to examine why users do not understand the security tools.

The authors conducted a qualitative study with 40 participants in the USA to investigate the prevalent misconceptions of people regarding security tools, their perceptions of data access and the corresponding impact on their usage behavior and data protection strategies.

While security vulnerabilities are often rooted in people’s internet usage behavior, this study examined user’s mental models of the internet and unpacked how the misconceptions about security tools relate to those mental models.

Based on the findings, this study offers recommendations highlighting the design aspects of security tools that need careful attention from researchers and industry practitioners, to alleviate users’ misconceptions and provide them with accurate conceptual models toward the desired use of security tools.

The present study investigates the customers' behavioural intention to use voice-based artificial intelligence (AI) to find the appropriate hotels and resorts in an emerging nation. This study determines the influences of information quality, system quality, privacy, and novelty value on attitude and behavioural intention to use voice-based artificial intelligence to obtain the appropriate information and find the location of the hotels and resorts.

This study used a purposive sampling method for collecting data from the respondents, who are customers of the hotels and resorts in Bangladesh. A self-administered survey questionnaire was used to obtain responses from 378 respondents. After collecting the data, the reliability and validity of the constructs and hypotheses were tested via partial least squares structural equation modelling (PLS-SEM).

The findings of the study indicate that information quality, system quality, privacy and novelty value have a positive and significant impact on attitude and behavioural intention to use voice-based AI assistant services in an emerging nation. However, system quality does not significantly influence behavioural intention to use voice-based AI assistant but it has an indirect significant influence on behavioural intention through the mediation effect of attitude.

The study’s findings provide essential guidelines for practitioners to understand the impacts of information quality, system quality, privacy, and novelty value on attitude and behavioural intention to use voice-based artificial intelligence to find the appropriate hotels and resorts to meet customers' needs and expectations.

This study contributes to the existing literature on technology adoption by highlighting the interconnectedness of various factors influencing users' behavioural intentions. The study’s focus on an emerging nation provides a valuable theoretical contribution. It highlights that user perceptions and attitudes towards technology adoption may differ from those in developed nations due to unique contextual factors.

About 50% of innovations achieve commercial success in advanced countries. The number is much lower in emerging markets. Examining the impact of the digital environment on product success is crucial. The purpose of the study is to investigate the direct effects of disruptive technology (quality, efficiency and congruity) on digital entrepreneurship (new product development, cost-effectiveness and internationalization) and indirect moderating effects of the digital environment (data security, customer privacy and search engine optimization [SEO] algorithm) between disruptive technology and digital entrepreneurship.

This is a qualitative study by design. It uses the literature review method and the theory of disruption and competitive advantage to construct the six hypotheses linking the variables – disruptive technology, digital environment and digital entrepreneurship.

The study’s conceptual model proposes that disruptive technology leads to digital entrepreneurship; however, the digital environment moderates the relationship between disruptive technology and digital entrepreneurship in emerging markets.

The conceptual study has research implications for scholars. It constructs a conceptual framework and develops six hypotheses contextualized in emerging markets. The framework can be empirically tested across countries to validate the hypotheses and develop a competing model to explain more variance in digital entrepreneurship. This study also presents the possibility of analytical generalization.

This study has practical implications for digital entrepreneurs in emerging markets or those wishing to enter emerging markets. The main implication is that disruptive technology leads to digital entrepreneurship; however, the digital environment moderates it. Thus, digital entrepreneurs need to consider digital environmental effects such as data security, customer privacy and SEO. Given that two-thirds of the world is classified as an emerging market, the impact of the study is noticeable for practitioners as well.

Disruptive technology fosters digital entrepreneurship, which creates opportunities for innovative solutions for society worldwide. It breaks down the barriers to entry and promotes inclusivity by providing products and services that were unavailable before. Digital products are also economical and environmentally friendly, making them more suitable for people in emerging markets.

This study makes three new contributions. First, it proposes that disruptive technology leads to digital entrepreneurship and that the digital environment moderates the relationship between disruptive technology and digital entrepreneurship. Second, from a theoretical viewpoint, it develops a theoretical testable framework, links the variables and proposes the six hypotheses. Finally, the most significant contribution of the study is the identification of the digital environment variable and its dimensions – security, privacy and SEO algorithm – and its comparison between advanced countries and emerging markets.

There are multiple threats that cause consumers to be vulnerable in the marketplace, with poverty being a leading cause. Impoverishment often negatively impacts access to multiple categories of goods and services that consumers require to experience a reasonable quality of life. While there is research that explores the underlying factors that lead to resource deficits and marketplace restrictions, as well as their physical and emotional outcomes, an understanding of what is necessary to survive and thrive across societies is more elusive. To this end, our chapter carefully examines the concept of consumption adequacy (CA), which historically captures consumer needs for food and potable water, socially acceptable clothing adapted to weather conditions, safe housing that provides for privacy needs of occupants, preventative and remedial health care, and opportunities to grow and advance through education and training. After briefly summarizing the extant literature, each is described in turn, and ways of empirically investigating them across societies are advanced. This chapter closes with both marketer and public policy implications.

Blockchain, a groundbreaking technology that recently surfaced, is under thorough scrutiny due to its prospective utility across different sectors. This research aims to delve into and assess the cognitive elements that impact the integration of blockchain technology (BT) within library environments.

Utilizing the Stimulus–Organism–Response (SOR) theory, this research aims to facilitate the implementation of BT within academic institution libraries and provide valuable insights for managerial decision-making. A two-staged deep learning structural equation modelling artificial neural network (ANN) analysis was conducted on 583 computer experts affiliated with academic institutions across various countries to gather relevant information.

The research model can correspondingly expound 71% and 60% of the variance in trust and adoption intention of BT in libraries, where ANN results indicate that perceived possession is the primary predictor, with a technical capability factor that has a normalized significance of 84%. The study successfully identified the relationship of each variable of our conceptual model.

Unlike the SOR theory framework that uses a linear model and theoretically assumes that all relationships are significant, to the best of the authors’ knowledge, it is the first study to validate ANN and SEM in a library context successfully. The results of the two-step PLS–SEM and ANN technique demonstrate that the usage of ANN validates the PLS–SEM analysis. ANN can represent complicated linear and nonlinear connections with higher prediction accuracy than SEM approaches. Also, an importance-performance Map analysis of the PLS–SEM data offers a more detailed insight into each factor's significance and performance.

This study aims to understand the extent of privacy concerns regarding voice-activated personal assistants (VAPAs) on Twitter. It investigates three key areas: (1) the effect of privacy-related press coverage on public sentiment and discussion volume; (2) the comparative negativity of privacy-focused conversations versus general conversations; and (3) the specific privacy-related topics that arise most frequently and their impact on sentiment and discussion volume.

A dataset of 441,427 tweets mentioning Amazon Alexa, Google Assistant, and Apple Siri from July 1, 2019 to June 30, 2021 were collected. Privacy-related press coverage has also been monitored. Sentiment analysis was conducted using the dictionary-based software LIWC and VADER, whereas text mining packages in R were used to identify privacy-related issues.

Negative privacy-related news significantly increases both negativity and volume in Twitter conversations, whereas positive news only boosts volume. Privacy-related tweets were notably more negative than general tweets. Specific keywords were found to either increase or decrease the sentiment and discussion volume. Additionally, a temporal evolution in sentiment, with general attitudes toward VAPAs becoming more positive, but privacy-specific discussions becoming more negative was observed.

This research augments the existing online privacy literature by employing text mining methodologies to gauge consumer sentiments regarding privacy concerns linked to VAPAs, a topic currently underexplored. Furthermore, this research uniquely integrates established theories from privacy calculus and social contract theory to deepen our analysis.

This study investigates near field communication (NFC) payment method adoption in the Republic of Kosova, aiming to understand factors influencing consumer behavior toward NFC technology adoption. Using the Unified Theory of Acceptance and Use of Technology (UTAUT-3) model and perceived risk theory, the research seeks to establish relationships between various factors and user intentions regarding NFC payment technology.

Using a quantitative approach, the research used a comprehensive questionnaire of 40 questions rated on a seven-point Likert scale across 16 constructs aligned with the research objectives. A convenience sampling method was used, distributing electronic questionnaires to 200 individuals representing diverse demographics in the Republic of Kosova.

The study identified significant support for numerous hypotheses, demonstrating substantial correlations between factors like performance expectancy, effort expectancy, social influence, habit, facilitating conditions and personal innovativeness with behavioral intention to use and behavioral intention to adopt NFC payments.

Because convenience sampling was used, there are restrictions on the study’s sample size. Moreover, although the study delves into noteworthy elements impacting the adoption of NFC payment systems, it might not cover all possible factors that could influence consumer behavior in this regard.

Policymakers, NFC product developers, companies in the technology and payment sectors and Republic of Kosova customers all gain strategically from the research’s findings. Policymakers may make informed judgments about legislation, improve product development and marketing tactics and empower consumers to accept NFC payments by having a better understanding of consumer preferences and behaviors related NFC technology.

Understanding consumer preferences and behaviors regarding NFC technology can refine product development and marketing strategies, inform policymaking and empower consumers’ decisions about adopting NFC payments.

This study’s innovative approach in combining the UTAUT-3 model and perceived risk theory contributes significantly to the understanding of factors influencing users’ intentions in adopting emerging payment technologies, filling a gap in NFC payment literature.

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.

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.

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.

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.

The objective of this study is to explore Generation Z’s interpretation of educational practices at the secondary education level. By examining the expectations of Generation Z, this study aims to provide insights for teachers and decision-makers to improve educational and instructional practices.

The specific approach employed in this study is Transcendental Phenomenology (TPh), which focuses on uncovering the perceived experiences, thoughts and evaluations of the Gen Z generation toward formal education. For this study, the maximum variation sampling strategy, which is one of the purposive sampling methods, was utilized. In line with the nature of the design, one-on-one interviews were conducted to collect data. Thematic analysis, a commonly used method for identifying recurring patterns of meaning, was applied to analyze the data. Peer debriefing or analytic triangulation, Data saturation, Triangulation and member checking techniques were operated to support the validity and reliability of the study.

In the light of the data analysis, four themes emerged: expectations from teachers, curricula, school administration and School Counseling Service (SCS). Gen Z expects from teachers “to be democratic, to adopt novel teaching approaches and technology, to have affective qualities, to be attentive to arts and sports, to conduct qualified assessment.” Gen Z has also expectations regarding the curricula in practice such as “functionality, extracurricular activities, and instructional practices.” The expectations of the students from school administration include “administrative expectations,” “expectations regarding the learning environment” and “social expectations.” The participants had expectations regarding School Counseling Service (SCS) such as “professional guidance,” “academic guidance” and “career guidance.” “Career guidance” includes “introduction of career paths,” “academic guidance” includes “introduction of university programs,” “exam guidance” and “teacher training” and “personal guidance” includes “accessibility,” “equity in guidance services,” “communication” and “functionality.”

The research is limited to the volunteers included in the study. In addition, the study includes only senior high school students, 12th graders, representing Gen Z. In addition, the study includes only Gen Z living in a metropolitan city. The methodological limitation of the study is that only one-to-one interview technique was used for data collection. The main reason behind such a choice is that the most appropriate technique for data collection in the phenomenology method is one-on-one interviews in order to explore individual interpretation.

The research sheds light on many different points in terms of different applications. One of the results obtained in this context is curriculum. Gen Z criticizes the limitation of the program to only in-school learning and states that extracurricular practices should be included. Findings also presents implications regarding learning environments. There is a growing emphasis by Gen Z on the adoption of green, comfortable and interactive learning spaces. The Generation Z population expects teachers to possess digital competence (DC) and utilize it in their teaching practices. This shows that teachers' teaching competencies need to be upskilled.

It is crucial for policymakers to support the development of teachers' digital skills and encourage their integration into teaching to enhance instructional productivity, promote innovative learning, increase instructional appeal, foster teamwork, improve communication and facilitate innovative learning. The research reveals that Gen Z is a social phenomenon and needs to be recognized and their learning needs explored. In this context, it is imperative that the preferences and learning needs of Gen Z are considered in the learning environment, content, method-technique and assessment stages, especially in formal education practices.

The current research is important both in terms of filling the research gap in the literature and making inferences about the learning preferences of the GEN Z generation. In addition, it raises awareness in terms of the return on educational investments, providing sustainable motivation for learning and school and increasing the quality of learning outcomes. While the study reveals certain implications, further research is required to investigate the competencies of teachers, the effectiveness of teaching materials, instructional practices and designs and learning environments. Future studies should particularly concentrate on the personal preferences, motivation, engagement and learning preferences of Gen Z at the secondary level. Authorities, including teachers, ought to reassess their perspectives and adapt their practices in order to better meet the needs and expectations of Gen Z.

This study aims to provide a series of drivers that prompt the blockchain technology (BT) adoption decisions in circular supply chain finance (SCF) and also assesses their degrees of influence and interrelationships, which leads to the construction of a theoretical model depicting the influence mechanism of BT adoption decisions in circular SCF.

This study mainly uses the technology-organization-environment (TOE) framework, which focuses on the aspects based on the nature of innovation, intra-organizational characteristics and extra environmental consideration, to identify the drivers of blockchain adoption in circular SCF context, while the significance and causality of the drivers are explained using interpreting structural models (ISMs) and the decision-making trial and evaluation laboratory (DEMATEL) method.

The findings of this study indicate that government policy and technological comparative advantage are the underlying reasons for BT adoption decisions, management commitment and financial expectations are the critical drivers of BT adoption decisions while other factors are the receivers of the mechanism.

This study provides theoretical references and empirical insights that influence the technology adoption decisions of both BT and circular SCF by practitioners.

The theoretical research contributes significantly to current research and knowledge in both BT and circular SCF fields, especially by extending the existing TOE model by combining relevant enablers from technological, organizational and external environmental aspects with the financial performance objectives of circular SCF services, which refer to the optimization of the financial resources flows and financing efficiency.