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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.

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.

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.

The paper aims to investigate the dynamic measurement of the water vapour resistance. The water vapour diffusion kinetics depends on the fibre’s material. So, water vapour resistance measurement times till the equilibrium steady state can vary in the case of natural fibres compared to synthetic fibres. Devices for determining water vapour resistance according to the ISO 11092 standard allow static values to be measured.

In this study to investigate the dynamic of the water vapour resistance, a new parameter named “holding period” was introduced and defined as the time from sample placement on the measuring head until the measuring process begins. The holding period was varied as 0, 30, 60, 90, 120, 180, 240 and 300 s. Wool and cotton knitted fabrics were tested as natural fibres and compared to 100% polyester and 90% polyester/10% elastane as synthetic fibres. Measurements were conducted under both air velocities of 1 and 2 m/s. The experimental test data were statistically analysed based on ANOVA and four-in-one residual plots.

Statistical analysis of experimental tests shows that the holding period affects water vapour resistance in both air velocities of 1 and 2 m/s and on the measured values in the case of hydrophilic fibres.

The study of the dynamic relative water vapour permeability of natural and synthetic is an important area of interest for future research.

It is recommended to hold the samples on the top of the head measurement before starting the test.

Following the ISO 11092 standard, the static values of the water vapour resistance were measured without considering the dynamic behaviour of the water vapour diffusion through the textile fabrics. This paper fulfils an experimental dynamic measurement of the water vapour resistance.

Trust plays a crucial role in overcoming uncertainty and reducing risks. Uncovering the trust mechanism in the sharing economy may enable sharing platforms to design more effective marketing strategies. However, existing studies have inconsistent conclusions on the trust mechanism in the sharing economy. Therefore, this study aims to investigate the antecedents and consequences of different dimensions of trust (trust in platform and trust in peers) in the sharing economy.

First, we conducted a meta-analysis of 57 related articles. We tested 13 antecedents of trust in platform (e.g. economic benefits, enjoyment, and information quality) and eight antecedents of trust in peers (e.g. offline service quality and providers’ reputation), as well as their consequences. Then, we conducted subgroup analyses to test the moderating effects of economic development level (Developed vs Developing), gender (Female-dominant vs Male-dominant), platform type (Accommodation vs Transportation), role type (Obtainers vs Providers), and uncertainty avoidance (Strong vs Weak).

The results confirm that all antecedents and consequences significantly affect trust in platform or peers to varying degrees. Moreover, trust in platform greatly enhances trust in peers. Besides, the results of the moderating effect analyses demonstrate the variability of antecedents and consequences of trust under different subgroups.

This paper provides a clear and holistic view of the trust mechanism in the sharing economy from an object-based trust perspective. The findings may offer insights into trust-building in the sharing economy.

The research fields of consumer behaviour and neurology are connected to the emerging subject of neuromarketing. The learning of how the human mind reacts to marketing stimulus is called neuromarketing, which integrates concepts from neuroscience and economics. It looks for the underlying brain mechanisms and affective states that shape the behaviour of consumers. Neuromarketers use methods like eye tracking, biometrics, brain imaging (fMRI and EEG) and eye tracking to try and understand how consumers make decisions, what grabs their attention and how they emotionally interact with companies, products and ads. Market grooming is the process of creating and manipulating the existing market towards a specific product, service or idea. It is the practice that helps the marketer to groom the product through various stages of marketing, be it market research, product development, advertising campaigns or creating favourable conditions for the product. All practices are performed to groom the market for a specific product, when they are combined with neuromarketing, it becomes a perfect blend for the success of product in the actual market. The study concludes that market grooming along with neuromarketing can present a significant potential for enhancing the understanding of consumer decision behaviour by increasing the validity and precision of assessing customer responses to marketing activities.

The unethical use of natural resources is contributing to the increasing environmental degradation. The depleting environment poses a threat to the sustainability of present and future generations. This paper aims to investigate the impact of social media on the green purchase intention of consumers. The research adopts the theory of reciprocal determinism to integrate the variables of social media, green product knowledge, green consumption values and drive for environmental responsibility, assessing their collective impact on green purchase intention.

Data were gathered from a sample of 310 young consumers using a structured close-ended questionnaire. The proposed hypothesis was tested by employing PLS-SEM.

The study validates that social media (SM) has the ability to shape consumers' intention to choose more eco-friendly products. In addition to social media, green consumption values and the drive for environmental responsibility exert a significant influence on green purchase intention. However, green product knowledge did not have a significant impact on green purchase intention nor did mediate the relationship between social media and green purchase intention.

The existing scholarly literature indicates that researchers have employed a variety of theories as the basis for their studies aimed at predicting intentions and behaviors related to environmentally conscious purchases. To our knowledge, this is the first study to incorporate social media in the theory of reciprocal determinism. Notably, the paper represents the inaugural investigation in the context of an emerging economy to incorporate green product knowledge as a mediating variable.