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Introduction: This chapter examines the impact of Financial Technology (Fintech) on Environmental, Social, and Governance (ESG) goals to promote a sustainable financial system. Digital payment platforms, blockchain applications, and AI-powered analytics have revolutionised the financial landscape in recent years. These advancements have made integrating ESG principles into investment decisions and business practices easier.

Purpose: The main aim of this chapter is to analyse the connections and possibilities that Fintech offers to achieve ESG goals. Understanding how Fintech can facilitate sustainable finance practices is crucial for promoting investment in Fintech.

Methodology: A series of indexes have been examined, including the Global FinTech Index (GFI) in Global and Regional Rank, the Global Sustainable Competitiveness Index, and performing the Green Growth Index, the Green Economic Opportunity Index, the Global Green Finance Index (GGFI), and the Financial Inclusion Index.

Findings: Through comparative analysis, it can be concluded that the countries with the highest rankings are Sweden, Finland, Denmark, Switzerland, and Germany. Sweden ranks highly in the GFI. These results show that these countries rank highly in achieving ESG objectives. Balkan countries, specifically Albania, Bosnia and Herzegovina, and Montenegro, have the weakest results compared to other countries. Policymakers can benefit from the study’s findings to design better regulations and frameworks that promote responsible fintech practices and foster sustainable finance.

Practical Implications: Regulators and agencies responsible for measuring fintech and ESG should strive to align the indexes associated with these two domains as closely as possible. In addition, businesses can utilise the findings of this study to increase awareness about the diverse solutions that fintech offers to achieve the objectives of ESG.

This chapter investigates the potential of integrating multiple criteria decision-making (MCDM) techniques with decision support systems of digital supply chain management (DSCM) to achieve optimal outcomes. Digital supply chain (DSC) employs digital technologies (DTs) such as artificial intelligence (AI), Internet of Things (IoT), and big data analytics to provide extensive datasets and valuable insights pertaining to supply chain operations. MCDM techniques employ these realizations to facilitate informed decision-making through the assessment of multiple competing criteria. Usually MCDM approaches are used in the academic research with comparatively lesser application in industry. We argue that MCDM methodologies can play an instrumental role in DSCM, specifically in the areas of supplier selection, demand forecasting, and inventory management. Nevertheless, the integration of MCDM like AHP, ANP, DEMATEL, etc., with decision support systems presents several challenges, including concerns regarding the quality of data and the intricate task of assigning weights to various factors.

In particular, it is worth mentoring new and more efficient solutions that can meet the increasingly specific needs of each company, especially in food management. A business intelligence (BI) solution can help your food company better understand and manage business processes more effectively. Management information is essential for all levels of an organisation to make quick and correct decisions. However, what exactly is BI, and what can it mean for a food company?

The PRISMA stands for (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and content analysis strategy used the SLR (systematic literature review) methodology to examine 151 papers published in peer-reviewed academic journals and industry reports between 2016 and 2023.

The findings show that artificial intelligence and digitalisation are linked to the UN 2030 Agenda. BI management ranks first (66%), followed by crop and land mapping systems (40%), agricultural machinery monitoring tools (39%) and decision support systems (31%). The road to digital transformation remains extended, with the main impediments being more compatibility between enterprise systems and a shortage of expertise.

The section relating to methodological perspective adopts the PRISMA methodology for systematic review. Interoperability is easily managed by assigning qualified teams to projects. The added value of a consulting firm with extensive project management experience in the food industry is closely related to the results achieved.

BI: What exactly is it, and why a data-driven culture is essential in the food and beverage industry?

Introduction: In the context of Sri Lanka, this study compares how institutions and financial development (FD) affect economic growth (EG) and inclusive growth (IG).

Purpose: The well-structured administration and judicial system at the provincial level have been established against the socioeconomic vulnerabilities in the country for an extended period. Still, the country as a whole and provincial level is experiencing huge income and social inequality, though there are required provisions for enhancing the well-being of the people.

Methodology: The study consists of data from the nine provinces from 2013 to 2019. The analysis used the Dynamic Spatial Durbin Model (D-SDM) to explore the spatial dependencies between the provinces. Two models were developed: the interaction of the financial service activities (FSA) and insurance, reinsurance, and pension (INPEN), representing the FD with the EG and IG with and without. The IG index was estimated by principal component analysis (PCA) using indicators of the four dimensions. The results indicated spatial dependency among FD’s interaction with EG when provincial tax (PROTAX) and provincial expenses (PROEXP) are the provincial institutions.

Findings: The IG model results showed the IG’s spatial dependency moderated by the FD and only the IG model between the provinces. PROEXP showed a significant positive spillover impact among provinces towards the IG.

Practical Implications: The finding inform economic policy making while identifying weaknesses in existing local governments. Attention must be given to how poverty can be reduced, enhancing the well-being of the people with the proper channelling of finance and government institutional mechanisms.

Banks play a vital role in the economy. Investigating their competitive environment is crucial to ensuring economic stability and development. The FinTech disruption has risks and opportunities for incumbent banks, and it can be valuable to investigate its effects on banking performance. Therefore, the aim of this study is to assess whether investment in FinTech is associated with better performance of Indian banks during 2012–2018.

To do this, a sample of Indian banks was investigated between 2012 and 2018 using k-means and hierarchical cluster analysis, ANOVA, and pairwise comparison tests.

Results of the analysis strongly suggest that investment in FinTech is associated with better banking performance. Higher FinTech investments, represented by mobile transaction volume, are associated with higher efficiency scores and accounting-based performance. In particular, banks that invest in FinTech and have relatively low non-performing loans have a 7.7% higher Return on Employment (ROE) than banks with exceptionally low FinTech use and no significant investment in smart branches.

Therefore, it can be recommended that Indian banks adopt a forward-looking strategic approach when making investment decisions regarding new technologies. Failing to adapt to the FinTech disruption may result in poor value creation prospects in the long run.

To the best of the authors' knowledge, this is the first study that analyses. We are not aware of any similar study on whether investment in FinTech is associated with better performance of the Indian banks during 2012–2018.

Purpose: The prominence of quality education for building sustainable development is undeniable and is distinctly pointed out in 1 of the 14 sustainable development goals (SDGs). In the same context, this study intends to investigate the role of university commitment, perceived organisational prestige, student satisfaction, and perceived employability in enhancing sustainability in higher education.

Need of the Study: To evaluate how student satisfaction mediates the relationship between university commitment, perceived organisational prestige, and perceived employability with sustainable university institutes.

Methodology: An adapted questionnaire was used in this study to capture the perception of 458 management graduates selected through the purposive sampling method. Partial least squares structural equation modelling (PLS-SEM) technique was used to analyse the data with the help of Smart PLS software.

Findings: The results of this study show that student satisfaction is the strongest predictor of sustainable university institutes. University commitment was found to lead to student satisfaction significantly. Furthermore, student satisfaction wasn’t found to play the role of mediator in the proposed model.

Practical Implications: This study aims to fulfil theoretical, research, and management implications for students, higher education institutes (HEIs), and policymakers. HEIs are recommended to instil university commitment, perceived organisational prestige and student satisfaction via various practices and amendments in their curriculum. Students are recommended to enhance their perceived employability to achieve career sustainability.