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The coating process increases the durability, quality and effectiveness of the web, is used in manufacturing of wallpapers, adhesive tapes, wrapping, protection of fabrics and metals, X-ray and photographic films, beautification, books and magazines, film foils, magnetic records, coated paper, etc.

This paper gives a detailed study of the Oldroyd-4 constant fluid rheology during blade coating technique to check the sensitivity of velocity slippage on blade surface and magnetohydrodynamics (MHD) on final coating thickness and other mechanical properties. Heat transfer effects are also considered with viscous dissipation. The governing expressions under Lubrication Approximation Theory (LAT) are shortened and non-dimensionalized. A numerical technique with root finding algorithm is employed to determine the velocity profile, pressure and pressure gradient, shear stress, coating thickness, blade load and temperature profile. Figures and tables are exploited to show and discuss the effects of Hartmann number, slip parameter, geometrical parameter and viscoelastic fluid parameters on the flow and mechanical quantities. Comparison is also presented with previous literature under specific conditions.

From a technical vantage point, blade load and pressure are significant results of research as they lead to varying coating thickness, which gives an efficient coating process and extends substrate life. Shear stress is directly proportional to the magnetic parameter and inversely proportional to velocity slippage on blade surface. Temperature curve increases with increment in magnetic parameter and Brinkman number, while decrease in temperature is detected from slip parameter.

In literature, this investigation fills a gap in the numerical prediction of slip and MHD effects on the thin layer coating of rheological viscoelastic fluid during blade coating phenomena.

The boundary layer flow of immiscible fluids plays a crucial role across various industries, influencing advancements in industrial processes, environmental systems, healthcare and more. This study explores the thermally radiative boundary layer flow of a shear-driven Ree–Eyring fluid over a nanofluid. The investigation offers valuable insights into the intricate dynamics and heat transfer behavior that arise when a nanofluid, affected by thermal radiation, interacts with a non-Newtonian Ree–Eyring fluid. This analysis contributes to a deeper understanding of the complex interactions governing such systems, which is essential for enhancing efficiency and innovation in multiple applications.

The simulation investigates the convergence of boundary layers under varying shear strengths. A comparative analysis is conducted using γAl2O3 and Al₂O₃ nanoparticles, with water as the base fluid. The model’s numerical outcomes are derived using the bvp4c method through the application of appropriate similarity transformations. The resulting numerical data are then used to produce graphical representations, offering valuable insights into the influence of key parameters on flow behavior and patterns.

The temperature of the Al₂O₃ nanoparticles is always higher than the γAl2O3 nanoparticles, and hence, Al₂O₃ nanoparticles become more significant in the cooling process then γAl2O3 nanoparticles. It is also observed that the fluid velocity for both regions is enhanced by increasing values of the Ree–Eyring fluid parameter.

The results stated are original and new with the thermal radiative boundary layer flow of two immiscible Ree–Eyring fluid and Al₂O₃/γAl2O3 nanofluid.

Agri-entrepreneurship is considered a promising strategy to address poverty, particularly in developing countries. However, embarking on an agri-entrepreneurial venture poses significant challenges. The existing literature on agri-entrepreneurship in developing countries, particularly focusing on smallholders’ constraints, is often scattered and fragmented, focusing mainly on individual barriers rather than providing a comprehensive understanding of the multifaceted constraints. Therefore, this study aims to fill the gap by conducting a systematic review to identify, categorize, and prioritize the smallholders’ constraints.

By systematically reviewing literature retrieved from Scopus and Web of Science, published between 2013 and 2023, and following the PRISMA guidelines, this study identifies agri-entrepreneurial constraints through content analysis and categorizes and prioritizes them using thematic analysis.

This study revealed a range of constraints which are categorized into thematic areas including market-related challenges, financial constraints, limitations in human capital, institutional barriers, socio-cultural factors, technological shortcomings, and infrastructural challenges. Moreover, the study examines the role of social networks and their impacts on the livelihoods of smallholders in developing countries.

The study’s scope is limited to constraints for agri-entrepreneurship, particularly for smallholders in developing countries. The review considers English articles published between 2013 and 2023, and ABS 3 and above ranked journal articles.

The study systematically identifies, categorizes, and prioritizes the significant constraints to agri-entrepreneurship in developing countries by conducting a systematic review and identifying research gaps and future directions.

This research focuses on the controlling irreversibilities in a radiative, chemically reactive electromagnetohydrodynamics (EMHD) flow of a nanofluid toward a stagnation point. Key considerations include the presence of Ohmic dissipation, linear thermal radiation, second-order chemical reaction with the multiple slips. With these factors, this study aims to provide insights for practical applications where thermal management and energy efficiency are paramount.

Lie group transformation is used to revert the leading partial differential equations into nonlinear ODE form. Hence, the solutions are attained analytically through differential transformation method-Padé and numerically using the Runge–Kutta–Fehlberg method with shooting procedure, to ensure the precise and reliable determination of the solution. This dual approach highlights the robustness and versatility of the methods.

The system’s entropy generation is enhanced by incrementing the magnetic field parameter (M), while the electric field (E) and velocity slip parameters (ξ) control its growth. Mass transportation irreversibility and the Bejan number (Be) are significantly increased by the chemical reaction rate (C_r). In addition, there is a boost in the rate of heat transportation by 3.66% while 0.05⩽ξ⩽0.2; meanwhile for 0.2⩽ξ⩽1.1, the rate of mass transportation gets enhanced by 12.87%.

This paper presents a novel approach to analyzing the entropy optimization in a radiative, chemically reactive EMHD nanofluid flow near a stagnation point. Moreover, this research represents a significant advancement in the application of analytical techniques, complemented by numerical approaches to study boundary layer equations.

The purpose of this paper is to integrate job demands–resources theory with core self-evaluation theory to examine how and when sustainable project leadership stimulates sustainable project performance. Psychological empowerment is used as a mechanism between sustainable project leadership and sustainable project performance, whereas core self-evaluation acts as a moderator between sustainable project leadership and psychological empowerment.

This study adopts a time-lagged two-phase approach to collecting data from 257 software engineers working in medium-sized and large companies in the Polish financial sector.

This study reveals the direct and indirect (through psychological empowerment) effects of sustainable project leadership on sustainable project performance. It also confirms that the “sustainable project leadership–psychological empowerment” relationship strengthens with increasing level of project team members’ core self-evaluation.

This article explores a unique research framework. It significantly enriches the literature on sustainable project management, increasing the understanding of effective leadership practices that address the needs of software engineering teams to support sustainable project performance.

The paper discusses sustainability, in terms of creating purposive social value, which is increasingly an inherent characteristic of project leading and doing. Consequently, project scholars are currently grappling with what purposive social value creation means to initiation and execution of projects.

In line with recent development we offer reflections on the empowering nature of leadership enabling social value, its underlying forms of power and the dilemmas involved. Our theorizing is based on recent developments in literature on the value of sustainability in the context of projects, combined with literature on project leadership and reflections on the processes of power.

Based on a process ontology, we suggest that leadership for purposive social value creation calls for a rethinking of leadership as an inclusive patterning of actions, making it relational, boundary spanning and socialized in nature and essentially entailing a politics of representation.

The paper is conceptual, so it has all the limitations of any conceptual paper that innovates a new field of inquiry. It is a not a hypothetic-deductively structured paper but is abductive in nature, combining disparate literary studies in a conceptual framework for further inquiry.

The legitimacy of leadership for purposive social value does not reside in the singular formal position of a project leader but in its broader vesting and representation.

The paper calls for a rethinking of the nature of project leadership power relations, processes oriented toward the achievement of purposive social value and representation of interests.

This paper fulfills an identified need to study how purposive social value can be enabled by socialized and distributed project leadership that represents a broad-based and coherent conception of interests.

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.

The study assesses the most significant architectural core technological system that converges into a Battery Electric Vehicle (BEV).

Conceptually grounded in the convergence phenomenon and utilizing the graph theory-based network construction approach, based on the Betweenness Centrality (BC) metric, core International Patent Classifications (IPCs) have been empirically identified. Based on these IPCs, the ownership structure of the patents was established through assignee analysis.

Analyzing the networks obtained at different IPC levels, we found that multiple technologies have converged in a BEV, from battery chemistry to electrical engineering and thermal management of electrical machines.

The outcome of this work has led to the identification of BEV technologies, which can be further developed to assess the trends of technologies and associated gaps and aid technology management for the selection, acquisition, and exploitation of technology.

The outcome of this work will aid technology management practitioners in better planning the selection, acquisition, and exploitation of technologies associated with BEV.

The paper adds an evidence-based approach to the body of knowledge to identify the built-in technologies that produce a BEV.

The present paper makes an attempt to investigate the determinants that affect FDI inflows distribution among Indian states. Together with traditional determinants, the impact of institutional determinants on state-level FDI inflows distribution in India has been analysed.

The study uses panel data for a period of 20 years (2000–2019) for 17 groups of Indian states (29 states and 7 UTs). The empirical evidence is based on the panel data method and the findings support Dunning's OLI theory. As the data for some indicators for the institutional environment is not available at the state level, hence we used component analysis to arrive at the single component for the institutional factor. The study takes into account corruption, legal system, industrial disputes, man-days lost, labour availability, political risk, protection of IPR and agglomeration as potential macroeconomic and institutional determinants.

Results show that FDI inflows into Indian states is driven mainly by institutional environment. From our analysis, the author infers that the institutional variables such as legal system, IPR, corruption, political instability play an important role in determining the distribution of FDI inflows at the state level in India. Together with that GFCF and agglomeration are also important determinants of state-wise FDI inflows.

The major limitation of the study is that it doesn't include moderated impact of economic and institutional determinants of FDI inflows in Indian states, which can be an avenue for future research. Future research can also carried out taking district-level data to further examine the determinants at district level in India.

The contribution of the present paper is three-fold, first, the author constructs a measure of different institutional variables, after normalization of data for the period 2000–2019, and the author choose the highest explaining factor with the highest variance explained then we constructed the indices for select variable, which further has been used in the panel data analysis technique. The author has found that macroeconomic variables, as well as institutional variables, are significant to attract FDI at the state level in India. The paper shows that corruption, political risk, IPR and legal system are the major institutional determinants of FDI inflows in India at the state level. States with higher domestic investment attract more FDI inflows, moreover, agglomeration is a very important determinant as the investors are more confident in investing at the same location, the reason behind this may be that the investors want to avoid the registration procedure for new land, administrative formalities or they feel more secure at the same place and keen to invest at the same place again.

Managers and scholars alike claim that artificial intelligence (AI) represents a tool to enhance supply chain collaborations; however, existing research is limited in providing frameworks that categorise to what extent companies can apply AI capabilities and support existing collaborations. In response, this paper clarifies the various implications of AI applications on supply chain collaborations, focusing on the core elements of information sharing and trust. A five-stage AI collaboration framework for supply chains is presented, supporting managers to classify the supply chain collaboration stage in a company’s AI journey.

Using existing literature on AI technology and collaboration and its effects of information sharing and trust, we present two frameworks to clarify (a) the interrelationships between information sharing, trust and AI capabilities and (b) develop a model illustrating five AI application stages how AI can be used for supply chain collaborations.

We identify various levels of interdependency between trust and AI capabilities and subsequently divide AI collaboration into five stages, namely complementary AI applications, augmentative AI applications, collaborative AI applications, autonomous AI applications and AI applications replacing existing systems.

Similar to the five stages of autonomous driving, the categorisation of AI collaboration along the supply chain into five consecutive stages provides insight into collaborations practices and represents a practical management tool to better understand the utilisation of AI capabilities in a supply chain environment.