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Employee performance and job satisfaction are crucial factors that influence organizational success, particularly in the insurance industry. The advent of data-driven approaches has led to the emergence of Employee-Performance Data Management (EPDM) practices, which play a pivotal role in shaping employee outcomes. This study, with its clear focus on the impact of EPDM on job satisfaction within the insurance sector, aims to provide an understanding of this relationship, employing a positivist perspective grounded in existing theories.

The primary objective of this research is to investigate the influence of EPDM variables, such as data integration, technology integration, and ethical considerations, on job satisfaction among employees in the insurance industry.

We adopted a causal-comparative research design. This design allowed us to discern the cause-and-effect relationships among the variables under study. We collected data through structured questionnaires, ensuring a diverse sample of 415 employees across various job roles within the insurance sector. Our analytical framework encompassed multiple regression analysis, f-tests, t-tests, and calculations of means and standard deviations, all of which were used to rigorously assess the data.

Our study's findings have significant implications for the insurance industry. We found that aspects of EPDM variables, including data integration, technology integration, and ethical consideration, have a profound impact on job satisfaction. These results underscore the critical role of effective data management in enhancing employee outcomes. They also highlight the need for insurance companies to invest in robust data management strategies, potentially leading to improved job satisfaction and enhanced organizational performance.

The study examines the impact of behavioral biases, such as herd behavior, overconfidence and reactions to ESG News, on Socially Responsible Investing (SRI) decisions in the Indian context. Additionally, it explores gender differences in SRI decisions, thereby deepening the understanding of the factors shaping SRI choices and their implications for sustainable finance and gender-inclusive investment strategies.

The study employs Bayesian linear regression to analyze the impact of behavioral biases on SRI decisions among Indian investors since it accommodates uncertainties and integrates prior knowledge into the analysis. Posterior distributions are determined using the Markov chain Monte Carlo technique, ensuring robust and reliable results.

The presence of behavioral biases presents challenges and opportunities in the financial sector, hindering investors’ SRI engagement but offering valuable opportunities for targeted interventions. Peer advice and hot stocks strongly predict SRI engagement, indicating external influences. Investors reacting to extreme ESG events increasingly integrate sustainability into investment decisions. Gender differences reveal a greater inclination of women towards SRI in India.

The sample size was relatively small and restricted to a specific geographic region, which may limit the generalizability of the findings to other areas. While efforts were made to select a diverse sample, the results may represent something different than the broader population. The research focused solely on individual investors and did not consider the perspectives of institutional investors or other stakeholders in the SRI industry.

The study's practical implications are twofold. First, knowing how behavioral biases, such as herd behavior, overconfidence, and reactions to ESG news, affect SRI decisions can help investors and managers make better and more sustainable investment decisions. To reduce biases and encourage responsible investing, strategies might be created. In addition, the discovery of gender differences in SRI decisions, with women showing a stronger propensity, emphasizes the need for targeted marketing and communication strategies to promote more engagement in sustainable finance. These implications provide valuable insights for investors, managers, and policymakers seeking to advance sustainable investment practices.

The study has important social implications. It offers insights into the factors influencing individuals' SRI decisions, contributing to greater awareness and responsible investment practices. The gender disparities found in the study serve as a reminder of the importance of inclusivity in sustainable finance to promote balanced and equitable participation. Addressing these disparities can empower individuals of both genders to contribute to positive social and environmental change. Overall, the study encourages responsible investing and has a beneficial social impact by working towards a more sustainable and socially conscious financial system.

This study addresses a significant research gap by employing Bayesian linear regression method to examine the impact of behavioral biases on SRI decisions thereby offering more meaningful results compared to conventional frequentist estimation. Furthermore, the integration of behavioral finance with sustainable finance offers novel perspectives, contributing to the understanding of investors, investment managers, and policymakers, therefore, catalyzing responsible capital allocation. The study's exploration of gender dynamics adds a new dimension to the existing research on SRI and behavioral finance.

Tech start-ups (TSs) functioning in different domains have a responsibility of ensuring that domestic knowledge and capabilities are leveraged to minimize dependence on foreign organizations. Despite the growth of the ecosystem, while numerous TSs emerge, very few of them are able to survive, and of those that survive, very few scale up. The aim of this study is to identify the factors influencing the competitiveness of technological start-ups and to study the interrelationship and interdependence of these factors.

Modified total interpretative structural modeling (m-TISM) was employed for the current research. The analysis of what factors have an effect on competitiveness, how they affect it and why they affect it should be explored. The study begins by developing the list of factors through literature search, and further it is validated by expert opinion. A hierarchical model has been developed using m-TISM and MICMAC analysis to analyze the driving and dependency power of factors at each level.

Results show that the competitiveness of TSs is affected by organizational agility and internationalization. Factors present at the bottom level, namely entrepreneurial intensity, act as a strong driver for TSs. Team member commitment, transformational leadership, strategic alliances, knowledge sharing and organizational ambidexterity are middle-level factors.

This study is among the few articles that have explored competitiveness of TSs in the Indian context.

Ethereum-based blockchain technology (EBT) affords members of the Enterprise Ethereum Alliance (EEA) a market advantage in deploying blockchain within their organizations, including cybersecurity and operational benefits, that leads firms to strategically invest in this nascent technology. However, the impact of such strategic investments in EBT has yet to be explored in the context of its relationship to firm value. Therefore, this study explores EBT-specific firm-level characteristics that result in a stock market reaction to announcements of strategic investments.

The authors use the event study methodology, strategic investment literature and signaling theory as contextualizing frameworks for their study. Additionally, the authors explore a new method for examining technology investments as a strategic counter to cybersecurity threats.

Firms that signal to the market their strong commitment to their strategic investment by developing an EBT proof of concept see significantly higher market returns. Firms that have had prior cybersecurity incidents are rewarded by the market for strategically investing in EBT, and when firms with large undistributed free cash flows utilize this cash for strategic EBT investment, the market is more likely to reward these firms, indicating the market views EBT investment positively in these circumstances.

The results of this study provide new evidence of the value impact of EBT for firms that suffered cybersecurity events in the past. The authors provide empirical evidence of firm-level characteristics that investors use to discern whether a strategic investment in EBT will drive organizational value. Likewise, the authors demonstrate how signaling affects investor perceptions of strategic information technology (IT) investments in EBT.

This paper aims to provide empirical evidence on adopting artificial intelligence (AI), including generative AI, in knowledge management (KM) processes and its impact on organisational decision-making. Specifically, the study addresses three key research questions: RQ1: How is (generative) AI adopted within KM processes in organisations? RQ2: What factors influence the adoption of AI in these processes, either facilitating or inhibiting it? RQ3: How does AI adoption in KM processes affect organisational decision-making?

An explorative investigation has been conducted through semi-structured interviews with KM and AI experts from a worldwide sample of 52 mostly private, large and for-profit organisations. Interviews have been analysed through a mixed thematic analysis.

The study provides an original framework in which the three investigated concepts are interconnected according to a dual relationship: linear and retroactive and 20 factors affecting AI adoption within KM processes.

The provided model guides managers in improving their organisational decision-making through AI adoption in KM processes. Moreover, according to the rational decision-making model, the authors propose a six-step systematic procedure for managers.

To the best of the authors’ knowledge, this is the first study that simultaneously addresses AI, KM and decision-making and provides an integrated framework showing the relationships between them, allowing organisations to better and practically understand how to ameliorate their decision-making through AI adoption in KM processes.

Based on the job-demands resources (JD-R) model and the self-determination theory (SDT), this paper aims to explore team empowerment (TEMP) as a mediating mechanism through which team climate (TC) marked by innovativeness, cohesion and trust and knowledge management (KM) in teams.

Using a convenience sampling method, data were gathered from 246 employees of Tunisian knowledge-intensive firms (KIFs) and involved within 69 R&D teams. The partial least square-structural equation modeling approach through SMART PLS 3.2 software was used to evaluate the constructs’ psychometric properties and hypotheses. The mediating effect in the model was evaluated through the non-parametric bootstrapping method.

Results highlight that TC marked by innovativeness, cohesion and trust represents a key team contextual antecedent promoting TEMP and KM in teams. In turn, TEMP, as a critical intrinsic task motivation factor, is revealed as a driver of KM practices. This research demonstrates that TEMP partially mediates the relationship between TC and KM in teams.

This study pioneers the examination of TEMP’s mediating role between a TC marked by innovativeness, trust and cohesion and KM. By applying insights from the JD-R model and SDT to team-level dynamics, it uniquely positions TEMP as an intrinsic motivational factor explaining the mechanism through which the contextual resources provided by a supportive TC promote KM practices. It provides practical insights for KIFs’ managers through highlighting how intrinsically motivated teams of knowledge workers, empowered by a cohesive, innovative and trust-based TC, can effectively navigate the challenges inherent in knowledge-intensive teamwork, leading to enhanced KM practices.

Remote working has brought forward many challenges for employees as the phenomenon is still new for most employees across the globe. Some of these challenges may be addressed by the recent adoption of digital technologies by organizations. In this vein, our study explores the impact of digital platform capability on the creativity of employees through the mediating mechanism of explicit and tacit knowledge sharing.

The data were gathered from higher education institutes (HEIs) in a developing country, Pakistan which recently saw a major disruption during the Covid-19 pandemic. The proposed hypotheses were tested through Structural Equational Modeling (SEM) and the results confirmed our hypotheses.

The findings confirmed that the digital platform capabilities impact both tacit and explicit knowledge sharing among these remote employees. Likewise, the results also supported the mediating role of both explicit and tacit knowledge sharing on the creativity of these remote workers.

Our results are significant as they confirm the impact of digitalization on remote workers’ creativity predisposition. We thus advance the academic debate on the problems of knowledge sharing in remote working. We prove that digital capabilities outweigh the challenges created due to new forms of work driven by the pandemic. It further highlights the important areas to focus on while planning human resource policies in the new normal.

Purpose: This study aims to explore the efforts of several Asian countries adopting blockchain-enabled letter of credit (LC) processes and highlight the key challenges hindering blockchain adoption into the entire LC system.

Need for the study: As trade volume among countries grows, nations should agree on the technology’s application mechanism to prevent disputes over discrete practices. As blockchain is a borderless approach, the global context of the applications should be considered, incorporating the cases of Asia, the hub of intraregional collaboration in trading.

Methodology: This chapter has surveyed the existing literature to identify the dichotomy between blockchain-enabled LC and traditional LC. Ten Asian countries were selected considering their adaptation motivations, number of use cases, and economic outlook. The case-study method was applied to compare the counties.

Findings: Countries reported blockchain-enabled LC as time-efficient, less costly, and secure. Interoperability, scalability, the absence of legal and administrative infrastructure, stress for new skills, and cyber security concerns are the most cited challenges among users. Instances of regulatory sandbox and collaborative effort were found among some countries, although some countries have yet to publish application guidelines.

Practical implication: The study provides comparative pictures of blockchain-enabled LC systems adopted by several Asian countries. This will contribute to future collaboration between Asian countries to create a unified and standardised trade financing platform. The study will also contribute to the future formulation of guidelines for administrative methodologies of the permissioned blockchain application in the trade finance section.

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.

This paper examines to what extent blockchain creates legitimacy and trust in different modes of public governance. It posits that while blockchain aims for political legitimacy through decentralising, immutable and consensus-based mechanisms, the execution of these mechanisms is limited in legitimating governance, which has knock-on effects on trust. It provides an original contribution by recontextualising and reframing blockchain as a governance mechanism that should, and must, perform a legitimating function in order to engender trust.

The research adopts a comprehensive framework for understanding the legitimacy of blockchain governance, positioning it in terms of co-governance, self-governance and hierarchical governance modes. It systematically analyses blockchain whitepapers, legislation, government documents and other sources in three paradigmatic case studies where blockchain governance failed. These cases are then used to assess blockchain according to three key characteristics of decentralisation, immutability and consensus.

The research finds that blockchain’s use in governance settings still relies on legitimacy conferred from other sources – namely state – in order to generate trust. Significant limitations in its de facto political decentralisation, immutability and consensus protocols can create failures in co-governance, self-governance and hierarchical-governance applications, thus limiting the legitimation function of blockchain in facilitating political trust.

These findings are significant in highlighting blockchain’s limitations as a decentralised, immutable and consensus-driven legitimating tool, which has knock-on effects on trust in technology and governance more broadly. It also has broader implications in more clearly highlighting the interconnectedness of political trust and legitimacy in governance processes.