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Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

This study aimed to identify and analyse the key factors influencing the adoption of e-government services and to discern their implications for various stakeholders, from policymakers to platform developers.

Through a comprehensive review of existing literature and detailed analysis of multiple studies, this research organised the influential factors based on their effect: highest, direct and indirect. The study also integrated findings to present a consolidated view of e-government adoption drivers.

The research found that users' behaviour, attitude, optimism bias and subjective norms significantly shape their approach to e-government platforms. Trust in e-Government (TEG) emerged as a critical determinant, with security perceptions being of paramount importance. Additionally, non-technical factors, such as cultural, religious and social influences, play a substantial role in e-government adoption decisions. The study also highlighted the importance of performance expectancy, effect expectancy and other determinants influencing e-government adoption.

While numerous studies have explored e-government adoption, this research offers a novel classification based on the relative effects of each determinant. Integrating findings from diverse studies and emphasising non-technical factors introduce an interdisciplinary approach, bridging the gap between information technology and fields like sociology, anthropology and behavioural sciences. This integrative lens provides a fresh perspective on the topic, encouraging more holistic strategies for enhancing e-government adoption globally.

This paper has two objectives: first, to investigate the state-of-the-art of Industry 4.0 (I4.0) adoption in Italian manufacturing firms and, second, to understand variations in technologies implemented and business functions involved, benefits perceived, and obstacles encountered in I4.0 implementation over a three-year period.

The approach adopted in this research is descriptive, nesting longitudinal features. The paper presents a descriptive survey of 102 Italian manufacturing companies. The authors also evaluated non-response biases. The longitudinal approach was achieved by comparing the responses of the 40 sub-samples in common with a second similar survey launched three years prior, which aimed to identify patterns of evolution in the adoption of the I4.0 paradigm.

Survey findings demonstrate that Italian manufacturing companies still have limited awareness of I4.0 technologies, and the adoption of I4.0 technologies differs per technology. Company size and information system coverage level are the two factors that impact the company's technology adoption level. The comparative study shows that knowledge and adoption increase in a three-year interval with an unbalanced involvement of business functions regarding the I4.0 transformation. Indeed, companies are still seeking I4.0 solutions to reduce costs and lead times primarily, and the benefits perceived by companies are shown to be related to the number of I4.0 technologies in use. Finally, when companies put the I4.0 technologies into practice, competence is constantly considered the most significant barrier.

This paper aims at conducting a thorough investigation into the development of I4.0 adoption in manufacturing companies. The main limitation of this study concerns the limited number of subjects involved in the longitudinal study (40) and the focus on a limited geographical area (Italy). In addition, more I4.0 technologies could also be incorporated into the survey protocol to gain further insight into I4.0 development.

The authors provide one of the first attempts to assess the variations of I4.0 implementation concerning technology adoption, business function involvement, and the alteration of benefits and obstacles. Several studies presented in the literature highlight the lack of longitudinal studies investigating the development of the I4.0 paradigm in a specific manufacturing context: this paper is the attempt at filling this gap.

This paper investigates constraints to yield enhancing technology adoptions, highlighting credit using data pooled from the first three waves of the Ethiopian socio-economic surveys.

Direct elicitation methodology is used to identify household's non-price credit rationing status. The panel selection model specified to examine causal effects of credit constraint on adoption variables allows us to tackle self-selection into adoptions and potential endogeneity of credit constraint while controlling for unobserved heterogeneity in both the selection and main equations.

Results show that about 54% of sample households face credit rationing, predominantly demand-side risk rationing. There is a negative association between measures of credit constraint status and adoption variables. The effect is stronger when the demand-side credit rationing is accounted for and when within household variation in credit constraint status overtime is considered as opposed to across constrained and unconstrained households.

Expanding physical access to institutional credit alone may not necessarily spur increased uptake of credit and instant investment by farm households. For a majority of them to take advantage of available credit and improved technology, interventions should also aim at minimizing downside risks.

This paper incorporates the role of downside risk in influencing farmer's decisions to uptake credits and subsequently his/her adoption behaviors. The researcher approached the topic by state-of-the-art method which allows obtaining more reliable results and hence more specific contributions to research and practice.

The coronavirus disease 2019 (COVID-19) pandemic altered business and personal activities globally especially stimulating contactless financial transactions. However, despite the similar national lockdowns in cash-based economies, the adoption of contactless transactions through the widely available mechanism, mobile wallets, remained low. This research aimed to identify the factors surrounding this peculiarity.

The study was investigated using a composite model based on the diffusion of innovation theory (DIT), technology acceptance model (TAM) and information systems success model (ISSM). Data were collected from 621 Cameroonian mobile wallet users and analyzed using partial least squares structural equation (PLS-SEM) modeling.

The key findings revealed that the usage of mobile wallets, in the current form, were not affected by the perceived ease of use and did not match the existing lifestyle of users in Cameroon (no compatibility). The branding of mobile wallets (image) which was based on global messaging did not appeal to Cameroonians; in fact, the branding gave mobile wallets a negative image.

These key findings reveal the dangers of assuming that global strategies which have been effective in dealing with the pandemic will be effective in low-income or cash-based economies. The findings suggest that considering essential contextual dispositions is critical.

Research consistently shows that non-scientific bias, equity, and diversity trainings do not work, and often make bias and diversity problems worse. Despite these widespread failures, there is considerable reason for hope that effective, meaningful DEI efforts can be developed. One approach in particular, the bias habit-breaking training, has 15 years of experimental evidence demonstrating its widespread effectiveness and efficacy.

This article discusses bias, diversity, equity, and inclusion (DEI) efforts from the author’s perspective as a scientist–practitioner – the author draws primarily on the scientific literature, but also integrates insights from practical experiences working in DEI. The author provides a roadmap for adapting effective, evidence-based approaches from other disciplines (e.g. cognitive-behavioral therapy) into the DEI context and review evidence related to the bias habit-breaking training, as one prominent demonstration of a scientifically-validated approach that effects lasting, meaningful improvements on DEI issues within both individuals and institutions.

DEI trainings fail due to widespread adoption of the information deficit model, which is well-known as a highly ineffective approach. Empowerment-based approaches, in contrast, are highly promising for making meaningful, lasting changes in the DEI realm. Evidence indicates that the bias habit-breaking training is effective at empowering individuals as agents of change to reduce bias, create inclusion, and promote equity, both within themselves and the social contexts they inhabit.

In contrast to the considerable despair and pessimism around DEI efforts, the present analysis provides hope and optimism, and an empirically-validated path forward, to develop and test DEI approaches that empower individuals as agents of change.

Despite ample research on the adoption of online banking, the post-adoption phase remains largely neglected. The purpose of this paper is to develop a new conceptual model to investigate drivers, attitudes and behaviours in the post-adoption phase of the e-postbox, a co-creative online banking feature.

Research from bank marketing, services marketing, information systems and relationship management informs the proposed post-adoption model. Empirical tests rely on structural equation modelling and a sample of 750 current customers of the e-postbox of a large German bank.

The proposed model provides a multifaceted view of the post-adoption phase, including task-related, organisation-related and interpersonal communication-related drivers. This study reveals the importance of integrating dual interpersonal communication as a post-adoption driver and a post-adoption behaviour. It also extends the technology acceptance model by applying it to the post-adoption phase. Significant effects of age further suggest that younger customers express the most favourable attitudes towards and highest intentions to continue using the e-postbox; interestingly, older customers use it more and share more word-of-mouth.

This paper develops a post-adoption model that highlights the importance of continued usage for successful co-creation between the bank and its customers.

Managers can encourage continued usage during the post-adoption phase of a co-creative, digitalised service, which determines the retention of current customers and opportunities to attain new customers.

This study defines and establishes constructs for the post-adoption phase and categorises them according to post-adoption drivers, attitudes and behaviours.

The purpose of this paper to analyze the risk reporting practices and its determinants of commercial banks during the period of the adoption of the Basel II Accord in Portugal.

The paper conducts a content analysis of the risk and risk management sections included in the management reports and the notes of the annual reports of Portuguese commercial banks, for the years 2007, 2010 and 2013.

Findings show that theoretical frameworks underpinned in agency and legitimacy theories continue to provide valid explanations for risk reporting by Portuguese banks. More specifically, findings indicate that agency costs, public visibility and reputation are crucial drivers of risk reporting. Findings also indicate that younger banks with lower risk management skills use risk reporting either as an informational process or as a channel to manage organizational legitimacy.

The content analysis does not allow readily for in-depth qualitative inquiry. The coding instrument is subject to coder bias. Information about risk can be provided in sources other than annual reports. Additionally, not all banks disclose information on corporate governance-related variables that could also influence risk reporting.

The current research setting has never been studied hitherto. In this sense, this study seems to be of great relevance given the scarcity of literature on the subject in Portugal.

The need for context-specific adoption models led to the development of the firm technology adoption model (F-TAM) model. Among small to medium-scale enterprises (SMEs); however, firm-level factors were rather insignificant in engendering SME level adoption of technological innovation. This study aims to examine the effect of firm size and other moderating and mediating factors on the relationships between personal, firm, societal and technological factors proposed in the stakeholder-oriented F-TAM among SMEs.

A research instrument was developed, reviewed by experts, and pilot tested with a sample of 25 respondents. Data were purposively collected from four hundred (400) SMEs and analyzed with partial least squares structural equation modeling (PLS-SEM).

The study discovered that employees, societal and technological factors moderate the relationship between firm factors of adoption and firm adoption. Without these moderating effects, firm factors of adoption would have been insignificant at the SMEs’ level of organizational technology adoption. The study further discovered that firm size, as well as risk propensity, also affect the relationships proposed in the model.

Data was collected on voluntary adoption from the most cosmopolitan area of a developing country. It, therefore, needs further contextual validation across the country and different countries.

The engagement of innovations in firms must be planned with employees and society as major stakeholders.

The significance of this finding is the study’s emphasis on an eco-system approach for examining the phenomenon of innovation adoption. To the best of the authors’ knowledge, this study is the first to examine the effect of firm characteristics on is proposed eco-system of stakeholders.

This study aims to explore the implementation of artificial intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It contributes to the extant literature with a fresh perspective, expanding the discussion on AI adoption by investigating how it influences the perceptions of digital archival expertise.

In this study a two-phase data collection consisting of four online focus groups was held to gather the opinions of international archives and digital preservation professionals (n = 16), that participated on a volunteer basis. The qualitative analysis of the transcripts was performed using template analysis, a style of thematic analysis.

Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.

The volunteer basis of this study meant that the sample was not representative or generalisable.

Although the results of this research are not generalisable, they shed light on the challenges prospected by the implementation of AI in the archives and for the digital curation professionals dealing with this change. The evolution of the characterisation of digital archival expertise is a topic reserved for future research.