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This chapter examines the theoretical aspects of the financial stability of enterprises with different forms of ownership. The authors' approach to the financial stability of industrial enterprises is developed. Depending on the size (large, medium, small) and specific characteristics within sectors and industries, various indicators can be employed to evaluate the degree of financial stability. According to the authors, considering the specifics of construction materials enterprises, formed by seasonality of demand, capital intensity, investment volume, transportation costs, technological processes, etc., the assessment of their financial stability is based on the definition of absolute financial stability, normative financial stability, and precrisis level of financial stability. Using this methodology, the authors analyzed the financial stability of firms operating in Uzbekistan's construction materials sector. The outcomes resulted in crafting scientific recommendations and practical guidance to improve the financial robustness of these businesses.

This study aims to develop a predictive model using machine learning techniques to forecast construction dispute outcomes, thereby minimizing economic and social losses and promoting amicable settlements between parties.

This study develops a novel conceptual model incorporating project characteristics, root causes, and underlying causes to predict construction dispute outcomes. Utilizing a dataset of arbitration cases in Türkiye, the model was tested using five machine learning algorithms namely Logistic Regression, Support Vector Machines, Decision Trees, K-Nearest Neighbors, and Random Forest in a Python environment. The performance of each algorithm was evaluated to identify the most accurate predictive model.

The analysis revealed that the Support Vector Machine algorithm achieved the highest prediction accuracy at 71.65%. Twelve significant variables were identified for the best model namely, work type, root causes, delays from a contractor, extension of time, different site conditions, poorly written contracts, unit price determination, penalties, price adjustment, acceptances, delay of schedule, and extra payment claims. The study’s results surpass some existing models in the literature, highlighting the model’s robustness and practical applicability in forecasting construction dispute outcomes.

This study is unique in its consideration of various contract, dispute, and project attributes to predict construction dispute outcomes using machine learning techniques. It uses a fact-based dataset of arbitration cases from Türkiye, providing a robust and practical predictive model applicable across different regions and project types. It advances the literature by comparing multiple machine learning algorithms to achieve the highest prediction accuracy and offering a comprehensive tool for proactive dispute management.

The nickel-based alloys Inconel 625 and Inconel 718 stand out due to their high strength and corrosion resistance in important industries like aerospace, aviation and automotive. Even though they are widely used, current techniques of producing materials that are difficult to cut pose several problems from a financial, ecological and even health perspective. To handle these problems and acquire improved mechanical and structural qualities, laser powder bed fusion (LPBF) has been widely used as one of the most essential additive manufacturing techniques. The purpose of this article is to focus on the state of the art on LPBF parts of Inconel 625 and Inconel 718 for microstructure, mechanical behavior and postprocessing.

The mechanical behavior of LPBF-fabricated Inconel is described, including hardness, surface morphology and wear, as well as the influence of fabrication orientation on surface quality, biocompatibility and resultant mechanical properties, particularly tensile strength, fatigue performance and tribological behaviors.

The postprocessing techniques such as thermal treatments, polishing techniques for surface enhancement, mechanical and laser-induced peening and physical operations are summarized.

The highlighted topic presents the critical aspects of the advantages and challenges of the LPBF parts produced by Inconel 718 and 625, which can be a guideline for manufacturers and academia in practical applications.

Purpose: This chapter aims to evaluate the significant impact of Gandhian values on sustainable consumption behaviour (SCB) by applying the value-attitude-behaviour (VAB) framework. This chapter contributes by incorporating Gandhian values as one influencing factor for SCB.

Need for the Study: Values are considered as guiding principles in people’s lives. Studies suggest that values and other social and psychological factors can be vital in determining consumers’ behaviour towards sustainable consumption. There needs to be more empirical research on consumer behaviour facets of sustainable consumption for markets in India.

Methodology: The study uses partial least square structural equation modelling to empirically test proposed hypotheses and the research model of the relationship. The study results are based on data collected by administering a survey through a questionnaire confined to India.

Findings: The results indicated that Gandhian values, attitude, and sustainable consumption intention significantly influence SCB. Intention acts as a mediator between both outward and inward environmental attitudes and behaviour. The study provides directions for further research.

Practical Implications: This research study is helpful for researchers, marketers, and policymakers.

Additive manufacturing became the most popular method as it enables the production of light-weight and high-density parts in effective way. Selective laser melting (SLM) is preferred by means of producing a component with good surface quality and near-net shape even if it has complex form. Titanium alloys have been extensively used in engineering covering a variety of sectors such as aeronautical, chemical, automotive and defense industry with its unique material properties. Therefore, the purpose of this review is to study the tribological behavior and surface integrity that reflects the thermal and mechanical performances of the fabricated parts.

This paper is focused on the tribological and surface integrity aspects of SLM-produced titanium alloy components. It is aimed to outline the effect of SLM process parameters on tribology and surface integrity first. Then, thermal, thermal heat, thermomechanical and postprocessing surface treatments such as peening, surface modification and coatings are highlighted in the light of literature review.

This work studied the effects of particle characteristics (e.g. size, shape, distributions, flowability and morphology) on tribological performance according to an extensive literature survey.

This study addresses this blind spot in existing industrial-academic knowledge and goals to determine the impact of SLM process parameters, posttreatments (especially peening operations) and particle characteristics on the SLMed Ti-based alloys, which are increasingly used in biomedical applications as well as other many applications ranging from automobile, aero, aviation, maritime, etc. This review paper is created with the intention of providing deep investigation on the important material characteristics of titanium alloy-based components, which can be useful for the several engineering sectors.

Based on the reception of the principle of self-organization, the core of Heinz von Foerster's operational theories, I hypothesize how Heinz von Foerster's theory can be an orientation model for the epistemological problem of complexity. I have chosen this study to demonstrate complexity as an epistemological problem. This is because the question of how order arises - the core problem of complexity - is an epistemological question for which Heinz von Foerster developed an epistemology of self-organization. I do not present new research because HvF already had the complex organization of systems in mind. Rather, I build a critical approach to complexity on the research and work on operational epistemology in HvF.

This article aims to provide an orientation for a philosophical and epistemological understanding of complexity through a reading of Heinz von Foerster's operational theory. The article attempts to establish complexity as an epistemological phenomenon through the following method: (1) a conceptual description of the science of complexity based on the turn to thermodynamic time, (2) a genealogy of complexity going back to the systemic method, and (3) Heinz von Foerster's cybernetic approach to self-organization.

Based on the reception of the principle of self-organization, the core of Heinz von Foerster's operational theories, the conclusion is drawn that complexity as a description is based on language games.

The results present complexity not as an object of science, but as a description that stands for the understanding of complex description.

The hypothesis that complexity is a question of description or observation, i.e. of description for what language serves, has enormous social implications, in that the description of complexes and the recognition of their orders (patterns) cannot be left to algorithmic governmentality, but must be carried out by a social agency.

HvF's operational epistemology can serve as an epistemological model for critical complexity theory.

This study drawing upon opportunity-ability-motivation (OAM) theory focuses on digital entrepreneurship opportunities (DEOs), knowledge generation capabilities (EKGCs) and enterprise market-sensing capabilities (EMSC) affecting digital innovation in terms of exploitative and exploratory DIs.

Employing quantitative methodology on a sample of 352 software SMEs' managers, the study employed a hierarchical regression analysis to investigate whether and how digital entrepreneurship opportunities and knowledge generation capabilities support and nurture both DIs. Additionally, the moderated–mediation effect of market-sensing capabilities on the relationships among digital entrepreneurship opportunities, enterprise knowledge generation capabilities and DIs are considered.

The study findings reveal that digital entrepreneurship opportunities influence exploitative and exploratory DIs. Knowledge generation capabilities partially mediate the relationship between digital entrepreneurship opportunities and exploitative and exploratory DIs, respectively. Moreover, market-sensing capabilities strengthen not only the effect of digital entrepreneurship opportunities on knowledge generation capabilities but also the effects of knowledge generation capabilities on exploratory DI. The moderated–mediation outcomes reveal that the mediating role of knowledge generation capabilities on the relationship between digital entrepreneurship opportunities and both DIs is stronger when EMSC are high.

This research integrates the opportunity-ability-motivation perspective to present a comprehensive framework that reveals the intricate interdependencies among digital entrepreneurship opportunity, knowledge generation and market-sensing capabilities in driving both exploratory and exploitative digital innovation in software SMEs. This approach significantly enhances our understanding of how software SMEs can strategically strengthen their internal skills and resources, ultimately leading to superior digital innovation outcomes.

Digitalization is changing the way entrepreneurs pursue opportunities. We have elaborated a conceptual framework to gain a better understanding of digital entrepreneurship. Using this framework, we have developed the Global Index of Digital Entrepreneurship Systems (GIDES), an analytical tool designed to measure and comprehend the impact of digitalization on entrepreneurship. This study aims to answer the research question of what specific bottlenecks are hindering the performance of digital entrepreneurial systems in the countries under investigation, with a particular focus on developing Asian economies.

GIDES is a composite indicator that evaluates the performance of digital entrepreneurial systems on a national scale. Unlike traditional entrepreneurship or most entrepreneurial ecosystem measures, GIDES adopts a systemic approach using the Penalty for Bottleneck (PFB) algorithm to spot bottlenecks that potentially degrade overall system performance.

GIDES assesses the digital entrepreneurship systems of 113 countries, with a specific focus on 21 developing Asian economies. Singapore is ranked first among developing Asian countries globally. However, most developing Asian economies have significant room for improvement. While developing Asia excels in terms of physical infrastructure, it needs to work on its culture and informal institutions.

Digital transformation is not happening in isolation. Instead, it is closely linked to and happens within the context of entrepreneurship. The level of digitalization of the economy, described by digital framework conditions, impacts entrepreneurial activity through their influence on national-level general and systemic framework conditions. Thus, GIDES monitors all the general, structural and digital frameworks that support digital entrepreneurship. Consequently, it offers a deeper understanding of how digitalization impacts entrepreneurship.

This article explores the impact of systematically designed online collaborative activities in two engineering undergraduate modules and key considerations for student interaction in Moodle.

The educational design research approach was chosen to improve educational practices through iterative needs analysis, design, development and implementation. The study followed design-based research (DBR) approach, with a mixed-method research design used to uncover the critical factors in designing, developing and implementing online collaborative learning activities for improving student interaction. Two iterative cycles of online collaborative learning activities were implemented using the Moodle learning management system for two modules of an engineering undergraduate degree programme at a state university in Sri Lanka.

Results indicate that students had demonstrated increased motivation for collaborative activities, and they had not experienced any significant difficulties in accessing materials or instructions. This study emphasizes that the design of learning activities has a greater influence on determining the level of interaction between the learner interface and the learner content. Also, a higher number of interactions on the wiki page improved learner-learner interactions, likely due to clear instructions and reduced complexities compared to previous Moodle activities. Overall, appropriately designed online activities can enhance students' motivation and improve communication, collaboration, cooperation and a sense of community among peers.

The study's constraints included a small sample size of 93 students in two courses, which limits generalization of the results. The study's findings should be carefully considered before being applied to courses with nontechnical content. The second constraint was the number of courses on which the activities were carried out. The activities were designed specifically for two Earth Resources engineering courses, and the developed activities addressed technical course content. The effect of the activities on students' engagement and motivation in various courses with nontechnical content must be investigated, and a complete generalization of the study's results may be called into question. As a result, careful consideration must be given to generalizing the study's findings.

The study found that authentic collaborative learning activities using online technologies increased student participation and helped them discover their engineering design skills. Future research can focus on developing activities for other technical courses and incorporating additional tools into the instructional process. The use of a design-based research approach was recommended for future studies to obtain more comprehensive results than traditional comparative study designs.

The findings of this study suggest mechanisms to improve student interaction through online collaborative activities, particularly for delivering technical content. Such an understanding of learner interactions with course content, peers, teachers and interfaces will assist in the effective transformation of traditional technical content to online delivery mode. This is a unique study of converting in-class delivered engineering module content to online delivery within an equal time frame under restricted facilities and conditions resulting from a pandemic environment.

This study aimed to optimize the dyeing scheduling process with uncertain job completion time to reduce resource consumption and wastewater generation, and while reconciling the conflicting objectives of minimizing the makespan and the need to limit the production on specific machines to minimize rework.

We employed a UNISON framework that integrates fuzzy decision tree (FDT) to optimize dyeing machine scheduling by minimizing the makespan and water consumption, in which the critical attributes such as machine capacity and processing time can be incorporated into the scheduling model for smart production.

An empirical study of a high-tech textile company has shown the validity and effectiveness of the proposed approach in reducing the makespan and water consumption by over 8% while high product quality and efficiency being maintained.

High-tech textile industry is facing the challenges in reducing the environmental impact of the dyeing process while maintaining product quality and efficiency for smart production. Conventional scheduling approaches have not addressed the relationship between machine groups and reworking, resulting in difficulty in controlling the makespan and water consumption and increasing costs and environmental issues. The proposed approach has addressed uncertain job completion via integrating FDT into the scheduling process to effectively reduce makespan and wastewater. The results have shown practical viability of the developed solution in real settings.