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Drawing on the co-creation literature and self-determination theory, this study takes a broader organisational perspective linking employees’ motivational antecedents (corporate brand socialization, employee brand identification and impression management) and employee-based brand co-creation (EBBC), with three employee-level outcomes: sales performance, employee resilience and adaptive selling. We therefore bridge the complex nexus between employees and organisational performance.

Survey data of 313 employees across industries and different-sized business-to-business (B2B) companies in China were collected. We used AMOS 21 to carry out structural equation modelling (SEM) for testing the main hypotheses.

The results reveal that EBBC is driven by external, internal and self-related motivations and leads to an increase in the three employee performance-related outcomes. The results further indicate that employees’ social media usage exerts contrasting moderating effects for each of the three motivational antecedents: While it strengthens the effect of employee identification on EBBC, it weakens the effect of corporate brand socialization on EBBC and exerts no effect on the relationship between impression management and EBBC.

This study confirms the effectiveness of EBBC in improving performance outcomes for B2B employees, particularly sales performance, resilience and job satisfaction, all of which are crucial for employee success. On the basis of our findings, in terms of employee satisfaction and performance, and in addition to conventional strategies and incentives, B2B organisations should encourage employee co-creation activities as outlined above, since such activities tend to impact these outcomes positively.

This study features and substantiates the self-related goal initiatives in EBBC, such as developing a sense of self-promotion desires and uncovers a moderator of the relationships between motivational antecedents and EBBC. These findings highlight the managerial relevance of specific motivational and psychological pathways in building employee brand co-creation behaviours, employee outcomes and organisational performance via employee sales.

The objective of this study is to examine the moderating effect of microfinance on the digital divide in developing countries.

On the methodology, the econometric method employed to estimate the equation is based on the two-stage least squares (2SLS).

This study confirms that microfinance can play an important role in mitigating the adverse effect of digitalization on poverty.

Thus, governments should prioritize and encourage the integration of digital technologies with robust microfinance systems to effectively combat poverty, given the importance of microfinance.

Given the importance of digital technology to businesses and economic development, we need to search for a better solution that allows digital technology to be further developed but at the same time, is not harmful to the poor. The issue of the poor, either financially or technically can be partially resolved if the poor is given the necessary and sufficient assistance. Therefore, this paper examines whether microfinance can be part of solutions to the digital divide in developing countries.

The purpose of this study is to determine the enablers of the quality of work life (QWL) of employees working in the Garment industries.

The study was carried out in a fivefold step. In the first step, the enablers of QWL were identified through an exhaustive literature survey, in the second step identified vital few components through Pareto analysis. Then the third step was followed by exploratory factor analysis (EFA) to further, to identify the precise components and validate the same using confirmatory factor analysis in fourth step. The final step included interpretive structural modeling and Cross-Impact Matrix Multiplication Applied to Classification analysis to model the validated components and determine the interrelationships and linkages.

Predominant QWL enablers of employees working in the garment industries are training and development, satisfaction in job, compensation and rewards, relation and co-operation, grievance handling, work environment, job nature, job security and facilities.

In this study, the interpretive structural model is designed based on the opinion of the experts who are working in the garment industry considering the responses from employees in garment sectors. The framework can be extended further to the other sectors.

In future, the researchers in QWL may develop a model to quantify the level of employees’ QWL who are working in different sectors. Enablers of QWL are essential, and based on this further statistical analysis can be carried out. This study will provide limelight to the researchers in choosing the valid and reliable set of enablers for the empirical studies. Organizations can get benefit by implementing the outcome of this research for the enhancement of the QWL of employees.

The study was carried out in 133 garment industries where 851 workers constituted the final valid responses that were considered for analysis. The outcomes from the study help administrators, policy and decision-takers in taking decisions to enhance QWL.

This study explores the pivotal role of artificial intelligence (AI) in revolutionizing knowledge organization within Nigerian libraries. The purpose of this study is to assess the challenges faced by these libraries, propose strategic approaches for successful AI integration and highlight the potential benefits and future directions of this transformative journey.

This study uses a comprehensive review of existing literature, case studies and a qualitative analysis of challenges faced by Nigerian libraries. Strategies for AI integration are proposed based on targeted capacity building, collaborative partnerships and phased implementation approaches. The methodology also involves assessing the current landscape of AI in Nigerian academic libraries, examining applications and exploring the perceived impacts of AI on library services.

Nigerian libraries face challenges such as limited resources, outdated systems and diverse information that hinder traditional knowledge organization methods. The integration of AI offers dynamic solutions, streamlining administrative tasks, optimizing search algorithms and enhancing user engagement. The findings of this study emphasize the potential benefits of AI, including improved accessibility, searchability and long-term efficiency gains in library collections.

This research contributes to the existing literature by providing insights into the specific challenges faced by Nigerian libraries and proposing practical strategies for AI integration. This study emphasizes the transformative potential of AI in addressing immediate challenges and unlocking enduring benefits. The originality lies in the context-specific exploration of AI in Nigerian libraries, offering a roadmap for stakeholders to embrace technological advancements and position libraries as leaders in providing innovative knowledge services.

This study examined the role of artificial intelligence (AI) tools in facilitating the accessibility and usability of electronic resources (e-resources) in academic libraries.

This study employed a quantitative descriptive survey to collect data from library users. The population targeted was sampled using a purposive sampling technique. A total of 427 (58%) participated in this study.

Most respondents preferred electronic journals (e-journals) among the e-resources stored in academic libraries. Chatbots were identified as preferred AI tools for accessing and enhancing the usability of these resources. Strategies mentioned included the potential for integrating AI tools across various e-resources. However, among the challenges reported was the inability to integrate AI tools with the existing library management systems. Improving e-resource discovery and access can significantly enhance the effectiveness of AI tools in academic libraries.

Originality in the context of AI applications in academic libraries refers to the unique approaches, innovative tools and creative solutions that enhance the accessibility and usability of electronic resources. By focusing on unique solutions that enhance the accessibility and usability of e-resources, these libraries can better serve their diverse user populations and adapt to the evolving landscape of information needs.

The study explores new aspects of financial investment management with technological involvement, providing detailed knowledge for future research. It identifies gaps in the literature and summarizes key research topics, utilizing a precise data collection framework.

The study is structured using systematic and bibliometric analysis with the antecedents, decisions, outcome-theories, context, and methods (ADO-TCM) framework. Data from Scopus and Web of Science were filtered based on Q1, Q2, social sciences citation index (SSCI) and Australian Business Deans Council (ABDC) criteria, resulting in 128 articles majorly emphasizing the last ten years. The “R” package facilitated bibliometric analysis, starting with data cleaning and import into Biblioshiny for effective results interpretation.

The study found that artificial intelligence detects and mitigates biases in investment decisions through rigorous pattern analysis, including social and ethical biases. The ADO-TCM framework revealed emerging theories, such as robo-advisory theory, offering new directions in behavioral finance for researchers and practitioners. The top authors and articles highlighted existing work in financial management.

The study’s originality is highlighted by its use of unique frameworks for data collection (SPAR-4-SLR) and interpretation (ADO-TCM).