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This chapter explains how and why the knowledge economy will increase the demand for knowledge engineering. It defines and traces the evolution of knowledge engineering. It identifies the two components of knowledge engineering – elicitation and representation. It discusses the increased importance of tacit knowledge, specifically know-what and know-how, for organizations and companies. The increased demand for knowledge engineering calls for increased number of knowledge engineers. Knowledge engineering will expand beyond its current homes in systems development and cognitive science. The MASK methodology is an important intermediary between formal knowledge engineering and the methods needed to develop natural language and conceptual modeling for the knowledge economy.

Entrepreneurship of universities has a critical role due to its important effects. However, there is a significant gap in the literature regarding the methodology for evaluating university entrepreneurship. Evaluating university entrepreneurship provides valuable information to policymakers and governments. This research presents an evaluation methodology for assessing university entrepreneurship using a hybrid multi-criteria decision-making (MCDM) approach.

For this purpose, entrepreneurship data of 50 universities from Türkiye were used. The evaluation framework consists of 4 main criteria and 23 sub-criteria. The importance level was determined by weighting the main criterion and sub-criteria with the subjective Best-Worst Method (BWM) based on expert opinions and the objective CRiteria Importance Through Intercriteria Correlation (CRITIC) method. The importance levels were determined by weighting the main and sub-criteria using the subjective BWM based on expert opinions and the objective CRITIC method. The final rankings were obtained by integrating the different ranking values obtained with the Borda function.

Findings revealed that the most important main criterion in the entrepreneurship of universities is economic and social contribution activities, and the most important sub-criterion is international patents. The proposed method ranked all universities according to entrepreneurship. Sensitivity and validation analyses proved that the method is robust, stable and consistent.

This study also provides a new perspective to policymakers and decision-makers in evaluating university entrepreneurship.

This study, which uses a hybrid approach of MCDM methods to evaluate the entrepreneurship of universities, can be adapted to different national and regional higher education systems, and this study provides guidance to researchers in this regard.

Purpose: To systematically identify and critically analyse the challenges and opportunities for the development of internal controls in the insurance industry within the new technological revolution Industry 5.0.

Need for the study: Effective internal controls are essential for maintaining financial integrity, protecting policyholder interests and complying with regulatory requirements. Covering risk, the insurance industry helps to protect companies and households from financial losses resulting from adverse situations. Financial stability of these institutions is crucial for financial well-being of society, reinforced in the current period of technological revolution Industry 5.0.

Methodology: Detailed review of current literature and existing practices regarding traditional internal controls in the insurance industry including the framework analysis for further development related to a technological shift. We also use the impact analysis of Industry 5.0 characterised by the integration of novel technologies and cyber–physical systems that alters the landscape for internal controls.

Findings: The impact of Industry 5.0 on the insurance industry can be summarised in three areas: (1) changes in risk leading to changes in demand for insurance, (2) changes in internal processes and (3) changes in competition in the insurance industry. While insurance companies are complex institutions, developments in all these areas are closely linked to business success. We conclude that this technological shift could help insurers to reduce costs associated with previously manual and repetitive activities.

Practical implications: Adaptation of internal controls in insurance industry by technological innovations in Industry 5.0 could increase the transparency of financial integrity, following the increase in the protection of policyholders’ interests.

The authors mobilise stewardship theory, which delves into trust and collaboration dynamics, advocating for long-term gains through actions beneficial to the broader community. Used as a fundamental framework to conceptualise the model, stewardship theory enhances the understanding of the effect of purchasing social responsibility (PSR) practices to foster innovativeness and performance through the supply chain (SC). This study aims to examine the relationship between PSR, SC innovativeness (SC-INNO) and SC operational performance (SCOP). In addition, the moderating effect of sustainability labels on these relationships will be studied.

Based on survey data from 177 organisations analysed through partial least square structural equation modelling, the results suggest that PSR has a positive and significant effect on SC-INNO and SCOP. In addition, SC-INNO plays a partial mediation role since the direct effect between PSR and SCOP is validated. Furthermore, the moderating effects of holding a sustainability label and industry type about PSR and SCOP are supported.

The results indicate a significant positive influence of PSR on both SC-INNO and operational performance. SC-INNO is found to partially mediate the PSR–SCOP relationship. Moreover, sustainability labels and industry type significantly moderate the effects of PSR on SCOP.

The findings extend stewardship theory into the sustainable purchasing and supply management field by providing empirical support for PSR as a reflection of stewardship behaviours by fostering innovation and performance throughout the SC.

India’s rapid economic growth has triggered a significant transformation in its logistics sector, fueled by comprehensive reforms and digital initiatives outlined in the National Logistics Policy. Smart warehouses, equipped with cutting-edge technologies such as IoT, AI and automation, have taken center stage in this evolution. They play a pivotal role in India’s digital journey, revolutionizing supply chains, reducing costs and boosting productivity. This AI-driven transformation, in alignment with the “Digital India” campaign, positions India as a global logistics leader poised for success in the industry 4.0 era. In this context, this study highlights the significance of smart warehouses and their enablers in the broader context of supply chain and logistics.

This paper utilized the ISM technique to suggest a multi-tiered model for smart warehouse ecosystem enablers in India. Enablers are also graphically categorized by their influence and dependence via MICMAC analysis.

The study not only identifies the 17 key enablers fostering a viable ecosystem for smart warehouses in India but also categorizes them as linkage, autonomous, dependent and independent enablers.

This research provides valuable insights for practitioners aiming to enhance technological infrastructure, reduce costs, minimize wastage and enhance productivity. Moreover, it addresses critical academic and research gaps contributing to the advancement of knowledge in this domain, thus paving the way forward for more research and learning in the field of smart warehouses.

The qualitative modeling is done by collecting experts' opinions using the ISM technique solicits substantial value to this research.

Effective social inclusion of people from refugee backgrounds in host communities is vital to the success of their resettlement. This study focused on how an NGO-organised care-oriented programme may foster the social inclusion of migrant women from refugee backgrounds in Australia.

We looked at how the programme’s adoption of an ethics-of-care approach might affect migrant women’s social capital, hence social inclusion. About 55 migrant women from a regional city in Australia were recruited for the study, and quantitative and qualitative data were collected.

The study revealed that the NGO’s adoption of the care ethics and principles to design and implement the physical activity program significantly increased refugee migrant women’s bonding and bridging social capital, which in turn promoted their social inclusion in the host community.

This study highlights the importance of adopting care ethics and care practices to inform initiatives designed to promote the social inclusion of marginalised groups such as refugee migrant women settling in regional cities in Australia. It also emphasises the need for NGOs and other organisations supporting new migrant groups to focus on increasing opportunities for such community groups to develop bonding and bridging relationships with people within and outside their language groups or ethnicity.

Accurate prediction of port cargo throughput within Free Trade Zones (FTZs) can optimize resource allocation, reduce environmental pollution, enhance economic benefits and promote sustainable transportation development.

This paper introduces a novel self-adaptive grey multivariate prediction modeling framework (FARDCGM(1,N)) to forecast port cargo throughput in China, addressing the challenges posed by mutations and time lag characteristics of time series data. The model explores policy-driven mechanisms and autoregressive time lag terms, incorporating policy dummy variables to capture deviations in system development trends. The inclusion of autoregressive time lag terms enhances the model’s ability to describe the evolving system complexity. Additionally, the fractional-order accumulative generation operation effectively captures data features, while the Grey Wolf Optimization algorithm determines optimal nonlinear parameters, enhancing the model’s robustness.

Verification using port cargo throughput forecasts for FTZs in Shanghai, Guangdong and Zhejiang provinces demonstrates the FARDCGM(1,N) model’s remarkable accuracy and stability. This innovative model proves to be an excellent forecasting tool for systematically analyzing port cargo throughput under external interventions and time lag effects.

A novel self-adaptive grey multivariate modeling framework, FARDCGM(1,N), is introduced for accurately predicting port cargo throughput, considering policy-driven impacts and autoregressive time-lag effects. The model incorporates the GWO algorithm for optimal parameter selection, enhancing adaptability to sudden changes. It explores the dual role of policy variables in influencing system trends and the impact of time lag on dynamic response rates, improving the model’s complexity handling.

Warehouses, essential nodes in the supply chain, significantly contribute to sustainability issues, accounting for about 11% of emissions related to logistics activities. The purpose of this study is to review articles on sustainable warehouse management (SWM) from the Scopus database to analyze trends, synthesize existing knowledge, and identify research gaps for future studies.

The review uses text mining of initial relevant documents to create a search string for paper retrieval. Text mining is further used to generate a dendrogram of the most frequently used words in the research papers, which is then analyzed to identify themes and sub-themes in SWM.

The dendrogram reveals four major themes and their sub-themes within SWM, including two novel themes: sustainable warehouse in green logistics and sustainable warehouse location. In addition, 12 research recommendations are identified through content analysis and are subsequently linked to specific Sustainable Development Goals (SDGs).

The methodological innovation in keyword selection for searching relevant papers and identifying themes serves as a structured template for researchers to explore further.

The research recommendations, aligned with the SDGs, aim to assist managers in making informed decisions and operational strategies to enhance factors associated with the Building Research Establishment Environmental Assessment Method and the sustainable performance of warehouses.

This study is novel in its application of text-mining techniques to generate a search string for identifying relevant papers and discerning themes by analyzing the dendrogram.

Forests are negatively affected from rapid world population increase and industrialization that create intense pressures on natural resources and the possibility of an achieving circular economy. Forests can be considered as essential resources for providing sustainable society and meeting the requirements of future generations and circular economy. Therefore sustainable production tools as part of circular economy can be handled as one of the basic indicators for achieving circular economy. Accordingly the main purpose of this study is developing a novel rough – fuzzy multi-criteria decision-making model (MCDM) for evaluation sustainable production for forestry firms in Eastern Black Sea Region.

For determining 18 criteria weights a novel Rough PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method is developed. Eight decision-makers (DMs) participated in the research, and to obtain group rough decision matrix, rough Dombi weighted geometric averaging (RNDWGA) operator has been applied. For evaluation forestry firms fuzzy MARCOS (Measurement of alternatives and ranking according to COmpromise solution) method was utilized.

After application developed model the fourth alternative was found as the best. Sensitivity analysis and comparison were made to present the applicability of this method.

Development of novel integrated Rough PIPRECIA-Fuzzy MARCOS model with emphasis on developing new Rough PIPRECIA method.

This study aims to identify the reasons for unmet health-care needs and related barriers among the Roma population with chronic diseases in Jordan.

A descriptive survey with a cross-sectional design was conducted, involving a sample of 347 Jordanian Roma participants. Data collection was performed using a structured questionnaire based on the Canadian Community Health Survey.

The analysis revealed that within the three categories of reasons for unmet health-care needs (accessibility, availability and acceptability), “Transportation issues” under the accessibility category constitute the most reported reasons: (mean = 90.4%, SD = 22.6%), followed by “Cost” (mean = 89.0%, SD = 26.2%) and “Care not available in the area” (mean = 85.8%, SD = 23.6%). Predictors of unmet health-care needs were being married, having health insurance and self-perception of mental health (OR = 0.215, p = 0.044), (OR = 0.391, p = 0.008) and (OR = 0.302, p = 0.002) respectively.

Unmet health-care needs are highly prevalent among Jordanian Roma, rendering them a vulnerable group susceptible to other diseases. To address this pressing issue, concerted and comprehensive efforts should be made to improve the utilization and accessibility of health-care services within this community. Furthermore, efforts should be made to elevate their social standing and status. facilitate their integration into the broader community.