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Research on employee non-/compliance to information security policies suffers from inconsistent results and there is an ongoing discussion about the dominating survey research methodology and its potential effect on these results. This study aims to add to this discussion by investigating discrepancies between what the authors claim to measure (theoretical properties of variables) and what they actually measure (respondents’ interpretations of the operationalized variables). This study asks: How well do respondents’ interpretations of variables correspond to their theoretical definitions? What are the characteristics of any discrepancies between variable definitions and respondent interpretations?

This study is based on in-depth interviews with 17 respondents from the Swedish public sector to understand how they interpret questionnaire measurement items operationalizing the variables Perceived Severity from Protection Motivation Theory and Attitude from Theory of Planned Behavior.

The authors found that respondents’ interpretations in many cases differ substantially from the theoretical definitions. Overall, the authors found four principal ways in which respondents interpreted measurement items – referred to as property contextualization, extension, alteration and oscillation – each implying more or less (dis)alignment with the intended theoretical properties of the two variables examined.

The qualitative method used proved vital to better understand respondents’ interpretations which, in turn, is key for improving self-reporting measurement instruments. To the best of the authors’ knowledge, this study is a first step toward understanding how precise and uniform definitions of variables’ theoretical properties can be operationalized into effective measurement items.

Blockchain technology enhances information management in healthcare supply chains by securing healthcare information and providing medical resource traceability. However, there is no decision framework to support blockchain implementation for managing information, especially in emerging economies’ healthcare supply chains. This paper develops a hierarchical decision model for implementing blockchain technology for information management in emerging economies’ healthcare supply chains.

This study uses 20 health supply chain experts in Ghana to rank 17 decision criteria for implementing blockchain for healthcare information management using the best-worst method (BWM) multi-criteria decision technique.

The results show that “security” and “privacy,” “infrastructural facility” and “presence of training facilities” are the top three critical factors impacting blockchain adoption in the health supply chain for healthcare information management. Other sub-factors are prioritized.

To implement blockchain effectively to enhance information management in the healthcare supply chain, health institutions, blockchain technology providers and state authorities should concentrate on the highly critical factors extracted from the study.

This is the first study that develops a hierarchical decision model for implementing blockchain technology in emerging economies' health supply chains.

The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment awareness, examining media anxiety and financial security, and including a gender analysis.

Consumers’ attitudes toward cashless payments were investigated using an online survey conducted from November 2021 to February 2022 on a sample of 836 Italian citizens by considering the behavioral characteristics and aspects of financial literacy. Structural equation modeling (SEM) was used to test the hypotheses and to determine whether the model was invariant by gender.

The analysis showed that the fear of contracting COVID-19 and the level of financial literacy had a direct influence on the payment behavior of Italians, which was completely different in its weighting. Fear due to the spread of news regarding the pandemic in the media indirectly influenced consumers’ noncash attitude. The preliminary results of the gender multigroup analysis showed that cashless payment was the same in the male and female subpopulations.

This research is noteworthy because of its interconnected examination. It examined the effects of the COVID-19 pandemic on people’s payment choices, assessed their knowledge, and considered the influence of media-induced anxiety. By combining these factors, the study offered an analysis from a gender perspective, providing understanding of how financial behaviors were shaped during the pandemic.

M-wallets have emerged as one of the most important financial innovations of the 21st century, enabling users to carry digital cash by securely storing payment methods on their mobile devices. However, the continued use of m-wallets varies among people for several reasons. This study used the technology continuation theory (TCT), gamification and trust factors to examine the variables affecting consumers' intentions to continue using mobile wallets.

The SmartPLS partial least squares software was used to analyze data from 431 m-wallet users in Vietnam using the structural equation modeling technique.

The data revealed that the research model can predict users' intentions to continue using mobile wallets. TCT constructs demonstrated strong exploratory power in explaining consumer satisfaction and attitudes towards m-wallets. Furthermore, the study confirmed the direct effect of the perceived effectiveness of gamification on perceived ease of use and attitude, as well as its indirect effect on consumers' continued use intentions of mobile wallets via attitude. In addition, the trust negatively influenced consumers' intentions to continue using m-wallets.

The findings of this study can help researchers, practitioners and policymakers improve m-wallet design, development and adoption, as well as advance financial technology and define the future of digital payments in terms of consumer attraction, engagement and financial inclusion.

Based on TCT theory, this study enriches m-wallet research by examining two important factors, gamification and trust, and thus provides insights into how to improve consumers’ intentions to continue using m-wallets in developing countries. This study offers timely insights into theory and practice regarding these factors. It therefore paves the way for researchers and practitioners to learn how easy, enjoyable and secure the end-user experience should be to keep users engaged with m-wallets.

This study aims to investigate the different attributes of electronic commerce (e-commerce) that determine perceived value and electronic loyalty (e-loyalty) among consumers of online food delivery applications (OFDAs). In this globalized world and competitive environment, e-commerce demands have increased and organizations are giving special attention to web development, website design and functions to hold the current consumers with sustainable performance in the globalized and competitive environment. Almost every industry has been affected by the coronavirus disease 2019 (COVID-19) and changed the way of operational work in many industries. Similarly, the food industry is facing serious challenges and now restaurants started heavily depending on OFDAs.

The study was quantitative and data were collected from 509 consumers of the district of Rawalpindi, Punjab Pakistan by using a convenience sampling technique who was the users of OFDAs to evaluate the proposed research model. Confirmatory factor analysis was applied to evaluate the validity of the constructs, and structural equation modeling was employed to test the model through Smart-PLS.

Our findings revealed that perceived value has a substantial positive impact on electronic loyalty (e-loyalty). Moreover, results confirmed that perceived value mediates the relationship of electronic privacy (e-privacy), electronic security (e-security), electronic payment (e-payment), usability and electronic innovativeness (e-innovativeness) with e-loyalty.

This study added to the unified theory of acceptance and use of technology (UTAUT) and technology acceptance model (TAM) by exploring consumers’ intentions for using OFDAs in the framework of e-commerce attributes, perceived value and e-loyalty. Similarly, the study enabled the author to learn more about how people would use the information system after successfully applying the UTAUT.

This study has significant implications for web developers, application designers, food delivery companies, restaurants and other businesses. Subsequently, it indicates the importance of the incredible attractiveness of OFDAs in boosting users’ intentions to keep using the application.

This research contributes substantially to OFDAs efforts to continuously increase its meal service platform and improve client satisfaction which resulted in repurchase intent. In addition, the research facilitates OFDA firms to enhance the features of their applications according to clients.

This conceptual study investigates the adoption of education technology (EdTech) products among college students, focusing on identifying the key factors influencing the adoption process within educational institutions. Technology integration in education has rapidly gained prominence, with EdTech offering innovative solutions to enhance teaching and learning experiences. However, understanding the determinants that affect EdTech adoption remains critical for its successful implementation and impact. This paper aims (1) to identify the factors influencing the adoption of EdTech by college students (2) to create a conceptual model that shows the connections between the elements that lead to college students adopting EdTech.

The research employed a mixed-methods approach, combining qualitative data analysis and conceptual modeling to achieve the objectives. The underlying knowledge required to create a qualitative data gathering tool was obtained through a thorough literature analysis on innovation dissemination, educational psychology and technology adoption. College students, teachers and administrators participated in semi-structured interviews, focus groups and surveys to provide detailed perspectives on their attitudes about and experiences with EdTech. The Scopus and Web of Science databases are searched for relevant information in an organized manner in order to determine the factors influencing the adoption of EdTech. Second, an extended version of the technology adoption model is adopted to develop a qualitative data-based conceptual framework to analyze EdTech adoption in the Indian context.

Overall, by highlighting the critical components that emotionally influence college students' adoption of EdTech products in educational institutions, this course adds to the body of information already in existence. The conceptual framework model serves as a roadmap for educational stakeholders seeking to leverage EdTech effectively to enrich the learning environment and improve educational outcomes. By recognizing the significance of the identified factors, academic institutions can make informed decisions to foster a climate conducive to successful EdTech integration.

A comprehensive conceptual framework model was developed based on qualitative data analysis to illustrate the interrelationships between the identified factors influencing EdTech adoption. This model presents a valuable tool for educational institutions, policymakers and EdTech developers to comprehend the complex dynamics of implementing these technological solutions.

The findings of this study demonstrated a number of important variables that affect the uptake of EdTech products in educational settings. These factors encompassed technological infrastructure, ease of use, perceived usefulness, compatibility with existing academic practices, institutional support, financial constraints and individual attitudes towards technology. Additionally, the research explored the significance of institutional preparation for embracing technological advancements as well as the influence of socio-cultural elements.

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.

This study investigates the factors influencing citizen attitudes toward e-government services and their effects on the adoption of e-government services in Saudi Arabia. It sheds light on the moderating role of citizen motivation in the relationship between factors influencing citizen attitudes in favor of e-government services and their adoption and usage behavior in the Saudi Arabian context. The study analyzes both the drivers propelling the uptake and the barriers impeding it.

A descriptive research design was employed in this study, which surveyed 487 respondents from Jeddah and Madina cities and the surrounding region. The research identifies key drivers, including cultural factors, digital literacy, government policy and interventions, privacy and security, technical infrastructure, support services and citizen trust, alongside barriers such as concerns about data security and digital literacy.

The findings reveal the complex interplay of these factors in shaping citizen attitudes toward e-government services and their effects on adoption in Saudi Arabia. The study indicates that citizen motivation toward e-government services moderates the relationship between, adoption and usage behavior.

This study contributes valuable insights for policymakers and practitioners by offering a nuanced perspective on e-government service adoption in the Saudi Arabian context. It enhances our understanding of the factors influencing citizen attitudes and their impact on e-government adoption, highlighting the importance of citizen motivation as a moderating factor in this relationship.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.

Online food delivery applications (OFDAs) provide an expedient platform, and consumers’ access to food has been drastically altered, especially during and after the COVID-19 pandemic. This study aimed to completely explore the attributes that influence consumers' purchase intention and how an app's aesthetics can evoke feelings that predict continuous usage intentions for OFDAs. The food industry, especially restaurants, heavily relies on mobile technology to facilitate critical online food delivery during the pandemic crisis.

The data for this study are gathered from 477 food consumers located in the federal capital territory (FCT) of Islamabad, Pakistan, through convenient sampling by developing a self-administrated online survey. SmartPLS is used for structural equation modeling to test the proposed research model and perform bootstrapping and algorithmic analysis.

Our findings revealed that perceived value positively predicted consumers’ purchase intentions. Moreover, perceived value mediates the association of information quality, familiarity, time-saving, usability and reputation with purchase intentions and fear of COVID-19 moderates the relationship between perceived value and purchase intention.

This research work has significant implications for researchers, web developers, app designers, delivery services, restaurants and other enterprises as it demonstrates the importance of aesthetically pleasing OFDAs in eliciting positive emotions and bolstering consumers’ intentions to continue using the app for efficient food delivery services.

This study expanded the application of the technology acceptance model (TAM) and attention, interest, desire and action (AIDA) by examining consumers’ purchase intentions in the context of OFDAs. Further, the successful utilization of TAM enhanced the understanding of consumer perceptions and behavioral intentions about the usage of OFDAs.