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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.

The purpose of this study is to find out what is the relationship between sustainability toward consumer behavior. Consumer behavior is the method of choosing, buying and using goods and services with an attachment to needs and wants. Now consumers are aware about sustainability, they make purchase decisions according to environmental safety, benefit to the society and increase economic growth.

This study validates the result through experts in textile industry by using the Decision-Making Trial and Evaluation Laboratory approach. This method has many benefits which provide decision makers and experts to understand the interdependence and influential relation between the criteria by hierarchical approach.

According to the results, green culture (F8) and green brand (F3) are the most influential (causal) factors and exert a substantial amount of influence over other factors for achieving organizational performance and sustainability. On the other hand, past experience (F14) and time pressure (F12) are the most influenced (effect) factors that are highly influenced by other factors.

The study conducted in Pakistan underscores the significance of maintaining a healthy and pristine environment for future generations. Both consumers and organizations play a vital role in this endeavor. It is imperative that they actively promote and support goods and services that advocate for sustainability.

Mangers should use long-term strategies that meet the high product value to enhance the organization’s reputation, so it will have positive consumer perception. If managers make policies to implement natural resources in their raw material, so this policy avoids conflicts and maintains a balance in our society.

This research delves into the complexities and subtleties associated with the identification and examination of the interconnections between the success factors of sustainability and consumer behavior.

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by incorporating Industry 4.0 technological innovations into existing quality management frameworks, signifying a significant evolution in quality control systems. Despite the evident advantages, the practical deployment in the Indian manufacturing sector encounters various obstacles. This research is dedicated to a thorough examination of these impediments. It is structured around a set of pivotal research questions: First, it seeks to identify the key barriers that impede the adoption of Quality 4.0. Second, it aims to elucidate these barriers' interrelations and mutual dependencies. Thirdly, the research prioritizes these barriers in terms of their significance to the adoption process. Finally, it contemplates the ramifications of these priorities for the strategic advancement of manufacturing practices and the development of informed policies. By answering these questions, the research provides a detailed understanding of the challenges faced. It offers actionable insights for practitioners and policymakers implementing Quality 4.0 in the Indian manufacturing sector.

Employing Interpretive Structural Modelling and Matrix Impact of Cross Multiplication Applied to Classification, the authors probe the interdependencies amongst fourteen identified barriers inhibiting Quality 4.0 adoption. These barriers were categorized according to their driving power and dependence, providing a richer understanding of the dynamic obstacles within the Technology–Organization–Environment (TOE) framework.

The study results highlight the lack of Quality 4.0 standards and Big Data Analytics (BDA) tools as fundamental obstacles to integrating Quality 4.0 within the Indian manufacturing sector. Additionally, the study results contravene dominant academic narratives, suggesting that the cumulative impact of organizational barriers is marginal, contrary to theoretical postulations emphasizing their central significance in Quality 4.0 assimilation.

This research provides concrete strategies, such as developing a collaborative platform for sharing best practices in Quality 4.0 standards, which fosters a synergistic relationship between organizations and policymakers, for instance, by creating a joint task force, comprised of industry leaders and regulatory bodies, dedicated to formulating and disseminating comprehensive guidelines for Quality 4.0 adoption. This initiative could lead to establishing industry-wide standards, benefiting from the pooled expertise of diverse stakeholders. Additionally, the study underscores the necessity for robust, standardized Big Data Analytics tools specifically designed to meet the Quality 4.0 criteria, which can be developed through public-private partnerships. These tools would facilitate the seamless integration of Quality 4.0 processes, demonstrating a direct route for overcoming the barriers of inadequate standards.

This research delineates specific obstacles to Quality 4.0 adoption by applying the TOE framework, detailing how these barriers interact with and influence each other, particularly highlighting the previously overlooked environmental factors. The analysis reveals a critical interdependence between “lack of standards for Quality 4.0” and “lack of standardized BDA tools and solutions,” providing nuanced insights into their conjoined effect on stalling progress in this field. Moreover, the study contributes to the theoretical body of knowledge by mapping out these novel impediments, offering a more comprehensive understanding of the challenges faced in adopting Quality 4.0.

The purpose of this study is to investigate the influence that technological, environmental and organizational factors have on the rate of Internet of Things (IoT) adoption within the logistics industry. In addition, the moderating effect that the risk factor has on the technological, environmental and organizational factors regarding the implementation of IoT in logistics.

For the purpose of testing the models and hypotheses, a survey was carried out in order to collect the responses from currently employed individuals at various companies working in the field of logistics or IoT. For the purpose of analysis, the authors made use of the partial least squares structure equation model (PLS-SEM) technique.

Findings of this study concluded that technology- and environmental-related factors significantly affect the adoption of IoT in logistics, while risk acts as a moderator for the technological-related factor only in the adoption of IoT in logistics.

The relevance of the authors' study lies in the growing importance of IoT in logistics and the need for logistics companies to understand the factors that impact the adoption of IoT in their operations. By identifying and analyzing the factors that influence IoT adoption in logistics, the authors' study provides valuable insights that can help logistics companies make informed decisions about whether and how to adopt IoT.

The research will help organizations make strategies for the successful adoption of IoT and ease the lives of all the stakeholders.

In this research, the authors attempted to find the factors that influence the adoption of IoT in logistics management. The influence of the technological, environmental, organizational and risk-related factors on the adoption of IoT in logistics management was studied. The moderating effect of risk over these factors on the adoption of IoT in logistics was also analyzed. This is original work and has never been done earlier.

In today’s business world, adopting social commerce for day-to-day operations has increasingly become an important phenomenon. Several factors have been identified by previous researchers regarding the adoption of social commerce, but academic research is scarce on the relationship between the factors influencing social commerce adoption and small and medium-sized enterprises (SMEs) in the post-COVID-19 situation. This study aims to identify the impact of technological, environmental and entrepreneurial factors on the adoption of social commerce by SMEs in Sri Lanka.

A quantitative study utilised the deductive approach and collected data through a field survey by distributing a five-point Likert scale questionnaire to conveniently selected respondents from Sri Lankan SMEs. Structural equation modelling (SEM) was used for the analysis of 384 responses.

The results revealed that technological factors [technology availability (TA) and cost-effectiveness (CE)], environmental factors [bandwagon effect (BE)] and entrepreneurial factors [attitude (AT), innovativeness (IN) and IT knowledge (IK)] have a significant impact on the social commerce adoption of SMEs in Sri Lanka. This study, as the first of its type, offers insightful information on the influence of variables on the adoption of social commerce after the COVID-19 pandemic.

Similar to any research, this study also has inherent limitations. Due to time and financial restrictions, the study’s convenience sampling method was adopted. The study’s possible limitation is its narrow focus, which could mean that it only examines a select few social media (SM) networks. The study’s conclusions might be less generalised since it focused on the western province of Sri Lanka. Future studies should take a cross-cultural strategy to explore the influence of social commerce adoption to improve the generalisability of research findings.

This study provides an in-depth assessment of critical factors, facilitating policymakers, owners, leaders and managers (decision-makers) to gain insight into the real influencing factors on social commerce adoption and the significance of SM. The study helps them comprehend how outstanding governance and knowledge of influencing factors can boost SME success in various ways. For example, research reveals that various factors have a major influence on social commerce adoption.

There has been limited research conducted on social commerce adoption after the COVID-19 pandemic period; thus, this study looked at the variables influencing it amongst SMEs in a South Asian developing country like Sri Lanka after the pandemic lasted for two years. By placing a strong emphasis on the role of entrepreneurial characteristics and the available technology within one single framework in the context of SMEs and their involvement with social commerce adoption, this study contributes to the past literature by emphasising the role of several significant factors in SMEs' adoption of social commerce. Whilst previous studies looked at multiple factors influencing the adoption of social commerce globally, this study focussed on how these factors have a significant impact on SMEs in Sri Lanka.

This study developed a multi-perspective framework combining technological, environmental and entrepreneurial factors influencing SMEs to adopt social commerce. The study provides a contribution to the literature on social commerce adoption from the perspective of SMEs in a developing country like Sri Lanka after COVID-19. Exclusively, it examines the impact of entrepreneur-related factors on social commerce adoption.

The global emphasis on sustainability is driving organizations to embrace financial technology (Fintech) solutions as a means of enhancing their sustainable performance. This study seeks to unveil the intermediary role played by green finance and competitiveness, along with the moderating impact of digital transformation (DT), in the intricate relationship between Fintech adoption and sustainable performance.

Drawing on existing literature, we construct a comprehensive conceptual framework to thoroughly analyse these interconnected variables. To empirical validate of our model, a dual structural equation modelling–artificial neural network) SEM–ANN approach was employed, adding a robust layer of validation to our study’s proposed framework. A sample of 438 banking employees in Pakistan was collected using a simple random sampling technique, with 411 samples deemed suitable for subsequent analysis. Initially, data scrutiny and hypothesis testing were carried out using Smart-PLS 4.0 and SPSS-23. Subsequently, the ANN technique was utilized to assess the importance of exogenous factors in forecasting endogenous factors.

The findings from this research underscore the direct and significant influence of Fintech adoption and DT on the sustainable performance of banks. Notably, green finance and competitiveness emerge as pivotal mediators, bridging the gap between Fintech adoption and sustainable performance. Moreover, DT emerges as a critical moderator, shaping the relationships between Fintech adoption and both green finance and competitiveness. The integration of the ANN approach enhances the SEM analysis, providing deeper insights and a more comprehensive understanding of the subject matter.

This study contributes to the enhanced comprehension of Fintech, green finance, competitiveness, DT and the sustainable performance of banks. Recognizing the importance of amalgamating Fintech adoption, green finance and transformational leadership becomes essential for elevating the sustainable performance of banks. The insights garnered from this study hold valuable implications for policymakers, practitioners and scholars aiming to enhance the sustainable performance of banks within the competitive business landscape.

The main purpose of this paper is to examine the adoption of big data analytics (BDA) in the Tanzania banking industry by investigating the influence of technological, environmental and organizational (TOE) factors while exploring the moderating role of perceived risk (PR).

The study employed a qualitative research design, and the research instrument was developed using per-defined measurement items adopted from prior studies; the items were slightly adjusted to fit the current context. The questionnaires were distributed to top and middle managers in selected banks in Tanzania using the snowball sampling technique. Out of 360 received responses, 302 were considered complete and valid for data analysis. The study employed partial least squares structural equation modeling (PLS-SEM) to examine the developed conceptual framework.

Top management support and financial resources emerged as influential organizational factors, as did competition intensity for the environmental factors. Notably, bank size and perceived trends showed no significant impacts on BDA adoption. The study's novelty lies in revealing PR as a moderating factor, weakening the link between technological readiness, perceived usefulness and the intent to adopt BDA.

This study extends literature by extending the TOE model, through examining the moderating roles of PR on technological factors. Furthermore, the study provides useful managerial support for the adoption of BDA in banking in emerging economies.

This study aims to investigate the factors influencing the adoption intention of artificial intelligence (AI) by micro, small and medium enterprises (MSMEs) in Jordan.

The study adopts the technology–organization–environment (TOE) model. It examines the moderating effects of innovation culture, employee digital skill level and market competition on the relationships between the independent and dependent variables. A survey was utilized to collect data from 537 MSME owners or managers in Jordan and employed partial least squares structural equation modeling to test the hypotheses.

The results of the study support seven out of eight hypotheses. Business innovativeness, management support, perceived benefits and technological infrastructure have positive and significant effects on AI adoption intention, while perceived costs have no significant effect. However, the innovation culture, employee digital skill level and market competition were found to moderate the relationships between some of the independent variables and dependent variables.

The study provides valuable insights and recommendations for MSME owners, managers, employees, policymakers, educators and researchers interested in promoting and facilitating AI adoption by MSMEs in Jordan.

The current attempt extends the TOE framework by adding significant constructs representing the three contexts. Moreover, it is one of the few studies that analyzed the factors influencing the adoption intention of AI by MSMEs in Jordan, which are significant to the Jordanian economy and represent 99.5% of enterprises.

This study aims to examine the feasibility of adopting blockchain technology in Jordan’s industrial sector and its intangible benefits. It also analyzes the influence of factors like technological, process, cultural and leadership readiness on the willingness of enterprises to adopt blockchain.

To gain insights into the potential adoption of blockchain technology and its intangible benefits for enterprises in the Jordanian industrial sector, this study gathered perspectives from a broad range of professionals, including financial managers, internal control staff, accounting departments, IT department managers and IS-related personnel. This was achieved through the administration of a comprehensive questionnaire designed to capture their opinions.

This study highlights the importance of technological and leadership readiness in adopting blockchain. It also shows that blockchain adoption can yield significant intangible benefits for enterprises. However, the study did not find a significant relationship between process readiness, cultural readiness and the intention to adopt blockchain.

The study’s outcomes underscore the importance of prioritizing technological and leadership readiness for enterprises and policymakers intending to adopt blockchain technology. By doing so, they can increase their willingness to adopt this technology and leverage its benefits.

This pioneering study investigates the adoption of blockchain technology and its intangible benefits for Jordanian businesses. It also examines the influence of factors like technological, process, cultural and leadership readiness on the decision to adopt blockchain in the industrial sector.

Cause-related B2B marketing programs involve sponsoring organisations working with B2B suppliers with the help of non-profit organisations (NPOs) on practises relating to environmental friendliness, workforce diversity, human rights, safety, philanthropy and business ethics. The study aims to identify the combinatory factors driving the adoption of Digital B2B platforms for managing cause-related B2B marketing programs.

The study adopts an innovative approach of fuzzy-set qualitative comparative analysis (fsQCA) on data collated from top corporations in India supporting cause-related B2B marketing programs. Sponsoring organisations and NPO dyads (i.e. survey both) filled out an email survey on 264 cause-related B2B marketing programs.

The study establishes that the combination of technological, organisational and environmental factors would lead to the adoption of Digital B2B platforms in managing cause-related B2B marketing programs. The study identifies six combinations of these factors for adopting Digital B2B platforms within and across sponsoring organisations and NPOs.

The study findings would aid cause-related B2B marketers in developing Digital B2B platforms’ capabilities by understanding the different combinations of factors driving adoption. Digital B2B platforms’ capabilities can improve market performance if developed as core competencies.

The study findings would enable improvements in the implementation and performance of cause-related B2B marketing programs. Better management of cause-related B2B marketing programs would help increase beneficiary coverage and the realisation of societal goals.

To the author’s knowledge, this is the first study to apply the TOE framework in conjunction with complexity theory to explain the diffusion of adoption of Digital B2B platforms for managing cause-related B2B marketing programs.