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The research on financial satisfaction has risen substantially in recent years due to its importance in personal financial planning and individuals’ subjective well-being. Hence, this study aims to map the existing literature on financial satisfaction to present the current state of knowledge and identify substantial gaps.

The present review uses 109 articles published between 1985 and March 2024 and retrieved from the Scopus database. The study deploys a systematic literature review (SLR), bibliometric analysis and content analysis to attain the objectives. Through bibliometric analysis, the present study highlights the most influential authors, journals, countries and affiliations, augmenting the literature on financial satisfaction. Moreover, the study presents the detailed antecedents and consequences of financial satisfaction through content analysis.

The study outlines that most studies in the financial satisfaction area revolve around its antecedents and consequences. The review details multiple antecedents affecting financial satisfaction, such as socioeconomic, psychological, social, personality, religious, financial literacy, financial behavior and technological factors. The prominent consequences of financial satisfaction include subjective well-being, life satisfaction, happiness, emotional and financial well-being, relationship quality, work engagement and sustainable growth.

The present research is an inaugural SLR that comprehensively maps the existing intellectual structure on financial satisfaction. In addition, it offers future research directions for further developments on the subject.

The research proposes a customised framework for improving logistics service quality (LSQ) in Tanzania's railway transportation, focusing on customer engagement and integrating customer-desired services.

The survey method obtained data from railway customers regarding the LSQ offered. Both probability and purposive sampling techniques were used to get the sample size. The open- and closed-ended questionnaires gathered the pertinent data. The data were analysed qualitatively and quantitatively using the IBM® SPSS® 21.0 and AMOS 21.0 software packages, respectively. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to analyse data and establish relationships between variables.

This study anticipated that the LSQ framework during the period of reviewing literature included three variables for freight transporting customers (tangible components, ways of fulfilment and information actions) and eight variables for passengers (tangible, reliability, assurance, responsiveness, comfort, empathy, connection and convenience). EFA and CFA dropped some factors. The retained factors were used as inputs to develop a framework. The qualitative analysis also established the improvement of customer’s desired services (CDS) and LSQ, which were the framework's processes for improving the LSQ. Ultimately, the study developed the LSQ framework for railway transportation.

The study was conducted on Tanzania’s railways, which incorporated challenges in the Tanzanian context. However, many challenges in the developing countries are relatively the same. Therefore, modifications can be made to adopt the developed framework and be used in other countries to cover the geographical and other challenges in particular countries.

Tanzania’s railway infrastructures are somehow not fully utilised to meet the actual needs of the transportation sector. For example, one of the railway companies has a built capacity of 4 million tonnes carrying capacity per year, but the actual cargo transported by the railway is 200,000 tonnes. This comes from several challenges within the railway companies, including the quality of their services, thus leading to a need to develop a LSQ framework.

The purpose of the study is to examine how risk factors contribute to the occurrence of defects in a process. By analyzing these risk factors in relation to process quality, the study aims to help organizations prioritize their resources and efforts toward addressing the most significant risks. These challenges, integrated with the emerging concept of Quality 4.0, necessitate a comprehensive risk assessment technique.

Fuzzy logic integrated with an analytic network process is used in the process failure mode and effects analysis for conducting risk identification and assessment under uncertainty. Through a mathematical model, the linkage of risk with Six Sigma is established and, finally, a value–risk matrix is developed for illustrating and analysing risk impact on process quality.

A case study on fused filament fabrication demonstrates the proposed methodology’s applicability. The results show its effectiveness in assessing risk factors’ impact on Six Sigma metrics: defects per million opportunities/sigma level.

By integrating qualitative assessments and leveraging available data, this approach enables a more comprehensive understanding of risks and their utilization for an organization’s quality improvement initiatives.

This approach establishes a risk-centric Six Sigma assessment method in accordance with the requirement of ISO 9001:2015 and in the context of Quality 4.0.

This study aims to examine whether agricultural commodities exhibited deviations in the lead-lag relationship between future and spot prices of farmer producer organizations (FPOs) traded commodities in the Indian derivative market after trade suspensions during Covid-19. The study may help buyers and sellers to get a fair price for their commodities after lockdown-trade disruptions.

The study applied the Granger causality (GC) test and the vector error correction model (VECM) to analyse short-run and long-run lead-lag relationships. Moreover, the study examined the pre-post-trade suspension effect on the lead-lag relationship of commodity prices.

The GC test results show that five out of the 13 agri-commodities have changed their lead-lag relationship from future to spot in the short run. Simultaneously, VECM captured changes in the lead-lag relationship for the same five commodities in the long run due to trade suspensions.

The findings indicate a reverse lead-lag relationship between future and spot prices for aforesaid commodities after trade suspension. The stakeholders may use the lead prices for these commodities to perform a fair trade. The study may be helpful in structuring price discovery strategy to achieve optimal price and efficient derivative trading.

To the best of the authors’ knowledge, this is the first study examining the effects of trade suspension on price discovery in FPO-traded agri-derivatives caused by the COVID-19 pandemic.

The primary purpose of the research is to examine the impact of financial socialisation (FS) on the financial well-being (FWB) of unskilled internal migrant labourers, particularly focusing on the intervening roles of financial knowledge (FK) and financial behaviour (FB).

Using a cross-sectional research design, primary data from 269 unskilled internal migrant labourers were collected, applying the purposive sampling method. Using the data, the direct and mediated effects are examined through a three-path mediation model with structural equation modelling (SEM).

Direct relationship analysis of FS on FWB exhibits an insignificant relationship, and FK also does not mediate the relationship; instead, FB acts as a potent mediator in both relationships.

The study enriches existing literature as it contributes to understanding the FWB of internal migrant labour, highlighting the pivotal role of FS and FB. Further, it provides insights for policymakers to enhance FWB through targeted interventions and inclusive policies, promoting social inclusion, economic empowerment and inclusive development.

Despite the significant economic role of unskilled internal migrant labours, studies have not focused on their FWB. Hence, the study delves into their FWB through FS directly as well as indirectly using a three-path mediation model for achieving sustainable development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2024-0044

This study advances research on cognitive diversity from the perspective of public employees by studying the effect of cognitive diversity on team viability, the mediating effect of transactive memory systems (TMS) and the moderating effect of technology integration.

We used SmartPLS to analyze a unique data set from 193 public employees. The information was collected through an online questionnaire administered by the LimeSurvey Professional platform. In addition to analyzing the data through partial least squares structural equation modeling with higher-order latent variables, we analyzed mediating and moderating effects.

The results show that TMS act as partial mediators between cognitive diversity and team viability. Although technology integration (for both external diffusion and internal integration) moderates this relationship to mitigate negative effects, technological infrastructure does not.

This study expands previous research on TMS and technology integration. Our findings support the significance of TMS and technology integration in a context of cognitive diversity, identify ways to develop good management behavior and assess the results of these practices for team viability. We recommend that public managers in contexts of cognitive diversity work to create effective workplace environments. Training programs can foster TMS capabilities and support implementation of technology integration to improve team viability and results for public service delivery to citizens.

This study aims to examine the potential of artificial intelligence (AI) to advance sustainability practices in universities, focusing on stakeholder perceptions and factors influencing the successful implementation of AI-driven initiatives.

Using a quantitative approach, a survey was administered to 539 university stakeholders (faculty, staff and students) from universities in Saudi Arabia. The survey measured awareness, perceived effectiveness and the importance of AI applications in energy management, waste reduction, transportation optimization and conservation.

Stakeholders exhibited moderate familiarity with AI for sustainability, with perceptions varying significantly by gender, university role and awareness level. Positive correlations were found between awareness and perceptions of AI’s effectiveness and importance. Transportation, energy efficiency and waste management emerged as key areas for AI application. Challenges identified include ethical concerns, financial constraints and infrastructure needs.

This research provides novel insights into integrating AI into university sustainability strategies. It highlights stakeholder perspectives, identifies priority areas for AI application and offers practical recommendations for enhancing AI-driven sustainability. The study emphasizes interdisciplinary collaboration and policy development to ensure ethical and effective AI use in higher education.

According to Dr. Martin Luther King Jr., justice delayed is justice denied. Recently, delayed justice has become one of the biggest threats to mankind since it restricts access to justice. COVID-19’s technological issues left Indian and international judicial systems in chaos and unable to address the problem. This allowed online dispute resolution (ODR) platforms to grow, which cured slow justice. As the disease spreads, many individuals have lost their employment. Private sector workers face volatility and uncertainty, and the financial market is poor. This darkness will take time to settle. But what about the resulting disagreements?

The COVID-19 epidemic prompted a new legal protocol. A virtual courthouse allows real-time case hearings and rulings. Conflicts that arise soon after COVID-19 may be resolved via ADR. ADR is only operating at a fraction of its ability due to isolation and confinement. Innovating the conflict resolution ecosystem with technology is the future of justice. ODR or electronic alternative dispute resolution (e-ADR) leads to this global trend. After seeing its potential, government agencies have adopted the ODR programme in recent years. Niti Ayog’s ODR manual details the roadmap and specifics of this conflict resolution approach.

ODR is still in its infancy, hence this study focuses on its legal foundation. The chapter also highlights ODR-coordinated projects. The report also evaluates ODR framework shortcomings and suggests measures to bridge them to establish a strong, effective, and fast justice system for one of the world’s largest democracies.

Knowledge management (KM) is a process that depends on changes and transfers to different levels of understanding among individuals and acts as a powerful tool to strengthen the organization to remove the barriers, affect the decision-making process and enable individuals and organizations to achieve sustainable advantages. This study aims to explore the role of digitization on knowledge conversion modes and its subsequent impact on related outcomes with reference to higher education institutions (HEIs). Prospects and paradigms of digitation for HEIs have also been explored.

The systematic review method has been used to organize and analyze the existing literature on digitization, knowledge conversion and related outcomes with reference to HEIs. To increase the scope of the research, the authors anticipated 30 research articles published between 2010 and 2022 in Google Scholar, Scopus, ProQuest and EBSCO databases. The study used PRISMA to conduct a systematic literature review. The study used “knowledge conversion, “SECI model,” “Digitalization” and “Higher education institutions” keywords to search the most suitable articles. To ensure the quality of this research, the study used quality journals.

The increasing significance of knowledge-building practices and a technology-driven environment insinuates the adoption of information and communication technology (ICT)-enabled equipment and devices to transfer knowledge, which further leads toward enhancing the effectiveness of education. This study offers a review of enabling factors based on Nonaka and Takeuchi’s (1995) knowledge spiral and provides an in-depth insight into the significance of digitization for the higher education sector.

The study’s main contribution was to explore the interrelationship among digitization, knowledge conversion and outcomes. Both technological and non-technological/conventional interventions have been discussed with reference to teaching and knowledge dissemination patterns based on Nonaka’s (1994) Socialization, Externalization, Combination, and Internalization (SECI) knowledge spiral.

The authors synthesize the previous literature research dimensions and recommend future research.