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Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

Operationnal excellence has emerged as a critical factor for organisations competitiveness. Companies in developing countries are striving to elevate their operational performance to new heights. This study aims to explore the effective best practices, drivers and challenges to operational excellence in North African business.

To address the objectives of this study, a qualitative approach is adopted. A total of 13 experienced professionals holding leads initiatives within North African enterprises are surveyed. Following, content analysis method is employed to extract, categorise and analyse the knowledge from the interviews.

The findings indicate that the implemented best practices include process optimisation, performance measurement, standardisation, customer-centric approach, lean manufacturing and total quality management. For a successful adoption, the results shed light on the importance of leadership commitment, upskilling, digitalisation and employee’s empowerment. However, the implementation faces several challenges incorporating unsustainable engagement, resistance to change, disconnected practices, insufficient investment, deficient improvement assessment and limited access to digitalisation.

This study contributes to exploring the best practices, enablers and barriers to successful implementation of operational excellence in emerging economies. Its findings can be used by scholars and decision-makers to advance knowledge around operational excellence, broaden the existing strategies to tailor specific contexts and promote operational performance.

The study aims to explore the dimensions of Quality 4.0 adoption, prioritization of these dimensions and the influential dimensions and their causal relationships that can guide the smooth adoption of Quality 4.0 to boost organizational performance.

The Quality 4.0 dimensions are explored from the extant literature. The qualitative data were captured from 12 highly experienced experts from diverse industries and academia through structured interview questions and group discussions in multiple phases. The inputs obtained from the experts were analyzed using Fuzzy-Technique for Order of Preference by Similarity to Ideal Solution for dimension priority, and Fuzzy-Decision-Making Trial and Evaluation Laboratory was employed to reveal the influential relationship between them.

The analysis reveals that quality scalability, quality culture and quality conformance are investigated as primary drivers of Quality 4.0 adoption. Data-driven analytical thinking and customer centricity emerge as dynamic dimensions that act as quality deliverable ends. Integrating these methodologies provides a robust framework for understanding and managing Quality 4.0 complexities, offering actionable insights for prioritizing initiatives and addressing interdependencies to ensure successful adoption and implementation.

The practical implications guide industries in creating strategic action plans tailored to their needs and fostering a quality-focused culture. The study also offers valuable insights into government policies, promoting sustainability, efficiency and a circular economy.

The study’s novelty lies in its prioritization and examination of the most influential causes and effects within the Quality 4.0 dimensions. This approach highlights core drivers and critical factors, providing a comprehensive framework for successful implementation.

Rhetoric has long had a bad reputation, as synonymous with “false and empty speech”. In the last century, rhetoric has undergone an important reappraisal, which has seen it applied also to corporate communication, corporate social responsibility (CSR), and, most recently, sustainability communication. However, the bad reputation that rhetoric has accumulated over the years continues to weigh on the legacy of the discipline, creating theoretical and methodological bias. This research represents a work that aims to map and systematize the academic literature related to rhetorical analysis in the context of CSR and sustainability communication. After a systematic literature review, a state-of-art literature mapping was carried out in order to create typological clusters of current approaches within traditional rhetoric theory, holding firm the assumption that the rhetorical discipline should be considered as a set of reasoned and structured techniques useful for corporate discourse and its persuasive effectiveness. The analysis has enlightened wide academic research regarding the study of rhetoric in corporate communications studies clustered in six typologies of topic endorsed by a specific goal that rhetoric would have in the studies.

This study aims to provide a comprehensive, textometric analysis of the evolving Quality 4.0 (Q4.0) research, identifying key themes, emerging trends and critical research gaps in the field.

A total of 129 peer-reviewed articles on Q4.0 were analyzed using IRAMUTEQ software. The textometric approach employed includes lexicographic analysis, descending hierarchical classification, factorial correspondence analysis and similarity analysis to uncover underlying patterns in the literature.

Three major clusters emerged from the analysis of Q4.0 research: (1) the digital transformation of quality management practices, (2) technological enablers of Q4.0 and (3) organizational implications of Q4.0 adoption. Key themes identified include the integration of Industry 4.0 technologies (e.g. IoT, AI and big data) into traditional quality management systems, the role of artificial intelligence in quality control and the challenges organizations face during Q4.0 implementation. This research also conceptualizes a comprehensive framework that outlines a strategic roadmap for Q4.0 adoption and integration, including the identification of antecedents and consequences of Q4.0 implementation. Additionally, the study proposes a measurement scale for assessing the dimensions of Q4.0.

The research proposes valuable implications for practitioners and organizations seeking to implement Q4.0 strategies as well as for researchers in the field of digital transformation and quality management. The proposed conceptual framework serves as a practical guide for effectively navigating Q4.0 implementation in diverse organizational contexts.

This study presents an innovative approach by applying textometric analysis to the field of Q4.0, offering an objective, data-driven perspective on the existing literature. It identifies significant gaps in research and proposes future avenues for investigation. As one of the first studies to develop a conceptual framework for Q4.0, including its antecedents, consequences and a measurement scale, this research provides a foundational contribution to the growing body of knowledge on Q4.0.

The main aim of this study was to determine the scope of application for an innovation management assessment framework (IMAF) within innovation management. Two distinct geographical regions: ANZ (Australia and New Zealand) and TMSV (Thailand, Malaysia, Sri Lanka and Vietnam) were chosen to identify and analyse significant comparative differences.

A quantitative research approach was used using empirical data collected through an online questionnaire-based survey. Statistical data analysis, including descriptive statistics, univariate analysis of variance (ANOVA) and Hsu’s MCB (multiple comparisons with/to the best) post-hoc test results, was carried out to identify significant differences and similarities in innovation management capabilities within the two regions.

The descriptive statistics analysis reveals areas for potential enhancement in all the model constructs within both regions under investigation. Significant differences in innovation management capabilities between the two regions are identified, specifically in the design for lean six sigma (DFLSS) and the operation function commercial (COMM). However, when considering the remaining constructs of the IMAF, no significant differences in innovation management capabilities are observed between the regions.

The research is limited by the relatively small size of survey questionnaire responses from the targeted population. Future studies could be conducted on a global scale to increase responses.

The research findings serve as valuable insights into the development of important and useful guidelines for managers and innovation practitioners engaged in innovation planning and management.

The critical analysis conducted in this research, focusing on innovation management capabilities by region, represents a significant advancement in the existing body of work that utilises the IMAF model.

Purpose/Objective: This study aims to investigate the inferences of technological innovations introduced by companies, emphasised by firm investments in innovative products, the use of information technologies (ITs), and the number of innovative products in achieving economic and environmental sustainability.

Design/Methodology/Approach: Simple regression models with Driscoll–Kraay standard errors processed through the Pooled OLS method, and cluster analysis performed through the Ward method inset on hierarchical clustering. A newly compiled dataset with information extracted from the European Innovation Scoreboard (EIS) 2023 was employed in the analysis, covering the time lapse from 2016 to 2023 and integrating 28 European countries.

Findings: A statistically significant relationship between firm investments, technological innovations, and companies’ environmental and sustainability credentials. Clusters associated with the impact of innovative technologies on environmental and economic sustainability were identified. The results showed four different clusters, including countries that present similarities among the variables or distinctive tendencies from the countries belonging to other clusters.

Significance/Implications/Conclusions: New insights for firms, managers, entrepreneurs, and local or foreign investors and emphasise the need for innovation and technological investments within companies to improve their business activities and support more effective and sustainable development.

Limitations: The reduced availability of data and regarding the sample of representative indicators.

Future Research: Future research avenues might explore the importance of collaboration among technologists, financiers, policymakers, and environmentalists to harness technology’s full potential and navigate the complexities of integrating it with sustainable practices.

The hoped-for “just recovery” from the COVID-19 pandemic has not occurred. This chapter examines socioeconomic disparities laid bare by the pandemic in the United States. They have left a marked impression, suggesting that the concept of “American exceptionalism” has negative as well as positive connotations especially when compared with other high-income countries. Strikingly, democracy is not delivering for many Americans, and yet that is not a new situation, as much scholarship shows. These findings challenge received wisdom about how this country is in the aggregate labeled “developed” when many Americans live in conditions similar to or worse than those the World Bank categorizes as “developing.” Against this background, the chapter assesses experiential learning models for engaging students on the SDGs to assess these disparities. While researching social justice gaps in Pittsburgh and Atlanta with Carnegie Mellon students, however, the lack of disaggregated data emerged as a human rights issue and major barrier to fulfilling the SDG principle to “leave no one behind” (LNOB). These findings suggest a paradigm shift is needed, using the SDGs to advance human rights, elevating socioeconomic rights, localizing issues, generating disaggregated data to drive policy recommendations, and scaling up the community of practice that is engaged in this paradigm shift. Field building these aspects of sustainable development has the possibility to positively shape policies, outcomes, and help this democracy actually deliver for all, not just for some. For the United States to lead and bolster human rights and democracy around the world, inequalities at home must be addressed.

Some of the major concerns that still face Jordan include poverty and income inequality, which work to retard economic growth. Poverty and income inequality have been a prevailed issue in Jordan, particularly as it is more prevalent in the countryside than it is in urban areas. Beginning in the 1950s, a series of governmental efforts by the Hashemite Kingdom of Jordan has taken place with the intention of alleviating both poverty and unequal distribution of income. The next research is focused on the extent of poverty and unequal distribution of income in Jordan, together with government interventions for further economic development. Targeting the working population in Amman and Karak, this study uses the questionnaire dissemination method to identify information about the dynamics of poverty and unequal distribution of income and analyze the governmental strategies for improving the present situation. It also provides recommendations toward improvements in education policies and increased funding from the government and nongovernmental organizations to improve living standards among poor and low-income groups.

Current research in the field of behavioural finance has attempted to discover behavioural biases and their characteristics in individual investors’ irrational decision-making. This study aims to find out how biases in information based on knowledge affect decisions about investments.

In step one, through existing research and consultation with specialists, 13 relevant items covering major aspects of bias were determined. In the second step, multiple linear regression and artificial neural network were used to analyse the data of 337 retail investors.

The investment choice was heavily impacted by regret aversion, followed by loss aversion, overconfidence and the Barnum effect. It was observed that the Barnum effect has a statistically significant negative link with investing choices. The research also found that investors’ fear of making mistakes and their tendency to be too sure of themselves were the most significant factors in their decisions about where to put their money.

This research contributes to the expansion of the knowledge base in behavioural finance theory by highlighting the significance of cognitive psychological traits in how leading investors end up making irrational decisions. Portfolio managers, financial institutions and investors in developing markets may all significantly benefit from the information offered.

This research is a one-of-a-kind study, as it analyses the emotional biases along with the cognitive biases of investor decision-making. Investor decisions generally consider the shadowy side of knowledge management.