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The purpose of this paper is to assess the feasibility of analytical models, specifically the radial basis function method, Akbari–Ganji method and Gaussian method, in conjunction with the finite element method. The aim is to examine the impact of processing parameters on temperature history.

Through analytical investigation and finite element simulation, this research examines the influence of processing parameters on temperature history. Simufact software with a thermomechanical approach was used for finite element simulation, while radial basis function, Akbari–Ganji and Gaussian methods were used for analytical modeling to solve the heat transfer differential equation.

The accuracy of both finite element and analytical methods was validated with about 90%. The findings revealed direct relationships between thermal conductivity (from 100 to 200), laser power (from 400 to 800 W), heat source depth (from 0.35 to 0.75) and power absorption coefficient (from 0.4 to 0.8). Increasing the values of these parameters led to higher temperature history. On the other hand, density (from 7,600 to 8,200), emission coefficient (from 0.5 to 0.7) and convective heat transfer (from 35 to 90) exhibited an inverse relationship with temperature history.

The application of analytical modeling, particularly the utilization of the Akbari–Ganji, radial basis functions and Gaussian methods, showcases an innovative approach to studying directed energy deposition. This analytical investigation offers an alternative to relying solely on experimental procedures, potentially saving time and resources in the optimization of DED processes.

The purpose of this study is to examine the association between the combined roles of chief executive officer (CEO)-chairman titles (CEO duality) and investment efficiency, defined as a lower deviation from expected investment for targeted S-curve firms used to propel an innovation-driven economy. This study also aims to investigate the moderating effect of financial reporting quality on this association.

This paper focuses on the ten targeted S-curve industries – under the definition of the Thailand 4.0 model – listed on the Stock Exchange of Thailand (SET) from 2000 to 2019. Data related to CEO/chairman titles and investment supports were manually collected from the annual reports, the SET market analysis and reporting tool database and the company websites. Financial data used to estimate investment behaviors and discretionary accruals were extracted from 1999. The study analyzes unbalanced panel data using fixed-effects regressions. Additional tests embrace replacing the sample with nontargeted firms, partitioning into granted and nongranted firms, adding CEOs’ demographic moderators, using alternative variable measures and analyzing for lagged independent variables.

The main findings show that CEO duality reduces overinvestment but worsens underinvestment in targeted firms. Financial reporting quality (FRQ) appears to strengthen CEO duality in mitigating extreme spending but has no impact on the association between CEO duality and underinvestment. Additional results, for example, conclude that CEO duality has no association with both over- and underinvesting at nontargeted firms, but its effect becomes positively significant on overinvestment when financial reporting quality is high. The negative association between CEO duality and overinvestment is found only in government-granted and targeted firms. FRQ encourages CEO duality in lowering overinvestment among targeted firms without grants. CEOs’ female and serviced early years appear to elevate those main findings.

These findings assist innovative corporations in choosing a proper leadership structure to cope with investment inefficiency. The research gives the government and regulatory bodies an insight into the qualifications of the leadership structure and financial information that helps them put forward effective policies.

To the best of the author’s knowledge, this study is among the first to establish the association between CEO duality and investment efficiency for innovation-driven firms in a transforming economy. The study fills the gap in the literature on management, accounting and finance by unveiling the interplay between dual leadership and financial reporting in affecting the efficiency of investments.

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.

While most West European nations were formed around pre-existing entities that could be called “countries” before the modern age, this was not the case in the Middle East. Some entities, like Egypt, did have a clear political and cultural identity before colonialism, others, like Algeria, did not. This chapter discusses the four states of the Maghreb: Morocco, Algeria, Tunisia and Libya, through the perspective of “country creation” going into and coming out of colonial rule. We can see here two “models” of fairly similar types of historical development, one showing a gradual process through a protectorate period to relatively stable modern nations, another through violent conquest and direct colonization ending in violent liberation and military and wealthy but fragile states. The article asks whether these models for the history of country creation and the presence or absence of pre-colonial identities can help explain the modern history and nature of these states in the Arab Spring and the years thereafter. Then, a more tentative attempt is made to apply these models to two countries of the Arab east, Syria and Iraq. While local variations ensure that no model can be transferred directly, it can show the importance of studying the historical factors that go into the transition from geographical region to a country with people that can form the basis of a nation.

This study employs Stein Rokkan's methodological approach to analyse state formation in the Greater Middle East. It develops a conceptual framework distinguishing colonial, populist and democratic pacts, suitable for analysis of state formation and nation-building through to the present period. The framework relies on historical institutionalism. The methodology, however, is Rokkan's. The initial conceptual analysis also specifies differences between European and the Middle Eastern state formation processes. It is followed by a brief and selective discussion of historical preconditions. Next, the method of plotting singular cases into conceptual-typological maps is applied to 20 cases in the Greater Middle East (including Afghanistan, Iran and Turkey). For reasons of space, the empirical analysis is limited to the colonial period (1870s to the end of World War 1). Three typologies are combined into one conceptual-typological map of this period. The vertical left-hand axis provides a composite typology that clarifies cultural-territorial preconditions. The horizontal axis specifies transformations of the region's agrarian class structures since the mid-19th century reforms. The right-hand vertical axis provides a four-layered typology of processes of external intervention. A final section presents selected comparative case reconstructions. To the authors' knowledge, this is the first time such a Rokkan-style conceptual-typological map has been constructed for a non-European region.

The goal of the study is to underline “Cinematic Architecture” as another source of architectural thinking and research. This study is also a response to the shortage in empirical research on architecture in the cinema. Moreover, the study introduces the architectural components that qualify the cinematic spaces to be influential cinematic experience. This is in addition to investigating the impact of these components on the viewers' cognitive and emotional experience of films.

In the reported study, an empirical experiment examined scenes from three different movies as experienced by a selected group of audience of movies fans (architects and laypersons). The audience was asked to report feelings the audience had about each scene using a questionnaire that was designed for this purpose, and the audience was asked to write down the aspects that affected the audience's emotions. The experiment evaluated selected emotional states and could specify the architectural features and/or objects that significantly contributed in inducing these emotions.

This study's findings concluded that emotions, which exist in the positive margin of the emotions “circumplex model,” were influenced by architectural components that were different from those that influenced emotions which lie in the negative margin of the model.

As for filmmakers, the study contributes in developing filmmakers' knowledge about the role of architecture in scenic creation and thus how that knowledge enhances filmmakers' film narrative and the narrative's spatial imagery. As for academia, this study contributes in developing the knowledge about film cognition as related to architectural semiotics. In the context of behavioral approach to architectural design, a behavior setting which is the basic element in environmental design can be dramatized by applying a cinematic narrative to a human activity system within a milieu of architectural design elements.

This study is important for architects, as the study provides architects with an alternative tool for fictional experience and for testing architectural ideas through cinematic architecture. This study also helps in developing new venues for the practice of architecture into the world of fiction. This study also contributes in developing the trend that architectural design thinking can learn from cinematic thinking and practice.

This study introduces an empirical approach to evaluate architectural entities as part of cinematic experience. This study also comes as a response to the shortage in empirical research on architecture in the cinema.

This paper aims to explore the relationship between owner-manager or leader’s ambidextrous leadership style and its effect on human resource management (HRM) practices, contextual ambidexterity and knowledge-intensive small- and medium-enterprises (SMEs) strategic agility.

This study presents an in-depth qualitative case study analysis of two knowledge-intensive SMEs from India’s information technology and health-care products industry serving a range of global clients. Using the theoretical lenses of empowerment-focused HRM practices, ambidextrous leaders, contextual ambidexterity and strategic agility, semi-structured interview data of leaders, managers and employees of the case organizations were analysed. Through a two-staged analytical process, we abductively developed a novel conceptual framework at the intersection of the above theoretical lenses.

The findings suggest that the knowledge-intensive SME’s strategic agility, ambidexterity and empowerment-focussed HRM approach was influenced by the owner-manager or leader’s ambidextrous leadership style and their philosophy towards managing people and had a positive impact in creating a culture of trust, participation, risk-taking and openness, and led to delivering innovative products and services as well as several positive employee-level outcomes.

Recent literature reviews on HRM In SMEs highlight several gaps, including the impact of owner-manager or leader’s philosophy of managing people in shaping HRM practices and employee outcomes. This paper thus adds to the existing literature on HRM and knowledge-intensive SMEs.

This study explores the extent of undergraduate students' engagement in interdisciplinary learning experiences across their academic journey and its potential correlation with elevated levels of self-efficacy in learning. Furthermore, the research investigates how the clarity of career decisions and future goals contributes to the perception of relevance, value and alignment of interdisciplinary learning experiences among undergraduate students.

Data were collected using a self-report questionnaire in a longitudinal survey administered annually to undergraduate students at a university in northern Taiwan over four waves from 2018 to 2021. The sample analyzed for this study consisted of 123 undergraduate students who willingly and continuously participated in the research throughout the specified period.

The results showed that self-efficacy within interdisciplinary learning experiences could be classified into three clusters: high efficacy, moderate efficacy and fluctuating efficacy. The determinants influencing these clusters include career decisions and years spent in university. Undergraduate students who have determined their career decisions and are in their latter two years of undergraduate studies demonstrate higher self-efficacy in interdisciplinary learning. Conversely, students who have yet to determine their career decisions exhibit a fluctuating pattern of self-efficacy across the three interdisciplinary learning categories.

Two key limitations of this research include a small sample size and a confined university-specific context, potentially constraining the applicability of the results to a broader population.

This study contributes to the interdisciplinary learning experience in higher education by explaining the significance of undergraduates' self-efficacy and career-related factors. Whereas most research has focused on the effects of self-efficacy, this study investigated the factors that influence undergraduates' self-efficacy.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.

This chapter addresses one of the most crucial areas for critical thinking: the morality of turbulent markets around the world. All of us are overwhelmed by such turbulent markets. Following Nassim Nicholas Taleb (2004, 2010), we distinguish between nonscalable industries (ordinary professions where income grows linearly, piecemeal or by marginal jumps) and scalable industries (extraordinary risk-prone professions where income grows in a nonlinear fashion, and by exponential jumps and fractures). Nonscalable industries generate tame and predictable markets of goods and services, while scalable industries regularly explode into behemoth virulent markets where rewards are disproportionately large compared to effort, and they are the major causes of turbulent financial markets that rock our world causing ever-widening inequities and inequalities. Part I describes both scalable and nonscalable markets in sufficient detail, including propensity of scalable industries to randomness, and the turbulent markets they create. Part II seeks understanding of moral responsibility of turbulent markets and discusses who should appropriate moral responsibility for turbulent markets and under what conditions. Part III synthesizes various theories of necessary and sufficient conditions for accepting or assigning moral responsibility. We also analyze the necessary and sufficient conditions for attribution of moral responsibility such as rationality, intentionality, autonomy or freedom, causality, accountability, and avoidability of various actors as moral agents or as moral persons. By grouping these conditions, we then derive some useful models for assigning moral responsibility to various entities such as individual executives, corporations, or joint bodies. We discuss the challenges and limitations of such models.