The past decade has witnessed significant progress in synthesizing structurally diverse and biologically relevant pyrano[2,3-c]pyrazole derivatives through the integration of green methodologies. A straightforward and environmentally friendly one-step method has been developed to synthesize divergent pyranopyrazoles in good yields with the aid of zinc acetate as a Lewis acid catalyst in toluene as solvent under reflux conditions.

Airline planning involves various issues that, in a general, can be grouped as network planning, schedule design and fleet planning, aircraft planning, and crew scheduling decisions. This study mainly aims to optimize the Crew Scheduling (CS) decisions considering the operational constraints related to Aircraft Maintenance Routing (AMR) regulations. Since, after fuel, crew costs are vital for airlines, and aircraft maintenance constraints are important operationally, the integrated Crew Scheduling and Aircraft Maintenance Routing (CS-AMR) problem is an important issue for the airlines. The present research addresses this problem using the Revenue Management (RM) approach under some disruption scenarios in the initial schedule. The proposed approach enables airlines to make more efficient decisions during disruptions to prevent flight delay/cancellation costs and recaptures an acceptable part of the spilled demand caused by disruption through the fleet stand-by capacity. This approach considers a set of disruptions in the flight schedule under different probable scenarios and provides the optimal decisions. Accordingly, airlines have two decision-making stages: Here-and-Now (HN) decisions related to the initial schedule for crew, aircraft routing and stand-by capacity to face probable disruptions and Wait-and-See (WS) decisions that determine what the executive plan of each crew and aircraft should be under each scenario, and how to use different options for flight cancellation and substitution. To this end, a novel Two-Stage Robust Scenario-based Optimization (TSRSO) model is proposed that considers the HN and WS decisions simultaneously. A numerical example is solved, and its results verify the applicability and evaluate the performance of the proposed TSRSO model. Regarding the complexity of the proposed MILP model categorized as NP-hard problems, we develop a computationally efficient solution method to solve large-scale problem instances. A single-agent local search metaheuristic algorithm, Adaptive Large Neighborhood Search (ALNS), is applied to solve the CS-AMR problem efficiently. According to the result obtained by applying the proposed revenue management approach for the CS-AMR problem, airlines can drive a robust solution under disruption scenarios that not only minimizes the total delay/cancellation costs but also increases the profit by recapturing the spilled demand.

Through the implementation of a simple, environment friendly one-pot multicomponent reaction with 1 mmol of methyl acetoacetate, 2 mmol of different substituted aromatic aldehydes, and 2 mmol of different substituted aromatic anilines in the presence of triethylammonium hydrogen sulfate [Et3NH][HSO4] bronsted acid as an ionic liquid catalyst and Ethanol: water as a green solvent at 60°C temperature. We have developed an affordable and dynamic procedure for the synthesis of novel, medicinally essential tetrahydropyridine derivatives. One-pot multicomponent synthesis is an energetic topic in heterocyclic chemistry due to its vital advantages of simple reaction process, high atom economy, low cost, less amount of waste generation, and simple workup procedures, which make this process economically productive for industrial applications. The final compounds were confirmed via FTIR, ¹H-NMR, and ¹³C-NMR spectroscopy and were in contrast with their reported methods.

This study aimed at investigating the impact of marketing change capabilities on marketing strategic change collecting data using a questionnaire from a sample consisting of executives and managers in manufacturing firms. Performing data analysis by SmartPLS software, the results indicate that the three dimensions of marketing change capabilities (micro, meso, and macro change capabilities) exerted significant effects on marketing strategic change. Theoretically, this study fills a considerable gap in marketing literature concerning such effects and identifying 12 marketing-related change capabilities. Empirically, the study calls decision makers in manufacturing firms for start building marketing change capabilities to be ready to face marketing strategy failure due to the changing nature of market arrangements.

In today's rapidly evolving business environment, driven by technological advancements and increasing stakeholder expectations, firms must strategically innovate to ensure long-term success and competitiveness. This study examines the interconnections between co-creation, resource-based management, environmental policy, organizational learning support, and organizational performance within the framework of Industry 4.0, grounding its analysis in the resource-based view theory. Focusing on the emerging market context of Vietnam, the research utilizes data collected by means of a survey of 321 managers across various industries, applying Partial Least Squares Structural Equation Modeling to explore these respondents’ perspectives on the relationships between the factors listed above. The findings provide actionable insights and strategic recommendations of relevance to companies which aim to thrive in the dynamic landscape of Industry 4.0, particularly in emerging markets. This study contributes to the existing literature by offering practical implications for the optimization of resource management and enhancement of organizational performance in the context of ongoing industrial transformation.

This paper studies the marketplace channel introduction of contract manufacturers and the response of the platform with an option to introduce a private brand. We develop a game-theoretical model to examine a three-tier e-commerce supply chain including a contract manufacturer (CM), an original equipment manufacturer (OEM) and a platform and derive the equilibrium results. We find that the marketplace channel introduction of the CM and the platform's private brand introduction influence each other. More specifically, marketplace channel encroachment may discourage the platform from introducing a private brand, and this preference is reinforced as the referral fee increases. Interestingly, the introduction of the platform's private brand increases the likelihood of contract manufacturer encroachment, which is mediated by the difference between the two private brands of the CM and platform--as the difference increases, the CM prefers to enter the marketplace channel. Furthermore, only contract manufacturer encroachment (or private brand introduction for the platform) can always benefit the whole supply chain, but the supply chain may be hurt when the platform and the CM perform their strategies simultaneously. In the extension section, in addition to demonstrating the validity of our main results when the CM and the OEM act as a single entity, we also find that the first-mover advantage of the platform may reduce the possibility of the contract manufacturer encroachment.

Production scheduling is a crucial task in the manufacturing process. In this way, the managers must decide the job's production schedule. However, this task is not simple, often requiring complex software tools and specialized algorithms to find the optimal solution. In this work, a multi-objective optimization model was developed to explore production scheduling performance measures to help managers in decision-making related to job attribution under three simulations of parallel machine scenarios. Five important production scheduling performance measures were considered (makespan, tardiness and earliness times, number of tardy and early jobs), and combined into three objective functions. To solve the scheduling problem, three multi-objective evolutionary algorithms are considered (Multi-objective Particle Swarm Optimization, Multi-objective Grey Wolf Algorithm, and Non-dominated Sorting Genetic Algorithm II), and the set of optimum solutions named Pareto Front, provided by each one is compared in terms of dominance, generating a new Pareto Front, denoted as Final Pareto Front. Furthermore, this Final Pareto Front is analyzed through an automatic bio-inspired clustering algorithm based on the Genetic Algorithm. The results demonstrated that the proposed approach efficiently solves the scheduling problem considered. In addition, the proposed methodology provided more robust solutions by combining different bio-inspired multi-objective techniques. Furthermore, the cluster analysis proved fundamental for a better understanding of the results and support for choosing the final optimum solution.

Trust is a key attribute of social cohesion that is a major phenomenon in social relationships. This research aims to trust levels in social relationships and understand how social relationships affect trust levels. This research uses the theory of social relationships as an understanding of the level of trust in modern organizations, the theory of trust based on three dimensions namely trust in information, motives, and competence. Statistical descriptive qualitative research method is used as an approach supported by Delphi analysis, Analytical Hierarchy Process (AHP), and TOPSIS (Technique for Others Preference by Similarity to Ideal Solution). In identifying factors in the social relationship between policy and community, nine social relationship factors were obtained, including Communication (A1); Trust (A2); Cultural (A3); Procedural Justice (A4); Problem-Solving (A5); Transparency (A6); Engagement (A7); Collaboration (A8); Empowerment (A9). On the one hand, in the context of relative importance, the weight value at the criteria level is trust in Information (C1) (19.8%); Trust in Motives (C2) (31.2%); Trust in Competence (C3) (49%). Based on the results of the 3D trust level-based mapping analysis on social relationships, of the nine alternatives there are no factors with complete level (level 5) and Ignorance (Level 1). Overall, there are two alternative social relationship factors with high trust level (level 4), namely Trust (A2) and Collaboration (A8). These findings suggest that social relationship factors, such as trust (A2) and Collaboration (A8), play an important role in increasing the trust value of institutions related to trust from the community.

This study conducts a bibliometric analysis of data mining publications in the Scopus database, examining the evolution of the field from 2015 to 2024. The study examines the bibliometric structure of data mining in management. Analyzing 2,942 publications, the research identifies significant growth in data mining studies. It reveals gaps in integrating data mining with decision-making, artificial intelligence, forecasting, and sentiment analysis. Despite a large number of publications, interdisciplinary applications of data mining are limited. The scientific publication on data mining and its relationship with decision-making, artificial intelligence, forecasting, and sentiment analysis is found to be weak, showing significant research gaps in these areas. China and the USA are prominent contributors, indicating geographical concentration. The study highlights the need for broader interdisciplinary exploration in data mining beyond traditional areas, urging global researchers to diversify contributions. The analysis focuses solely on publications indexed in Scopus, potentially excluding relevant studies from other databases or sources. This study provides insights into the evolution of data mining research and identifies areas for further interdisciplinary exploration, contributing to the advancement of the field's boundaries.

The present work intends to optimize a hybrid delayed differentiation multiproduct economic production quantity-EPQ model with the scrap and end-products multi-shipment policy. Since the requirements of multi-goods have a standard part in common, our fabrication planning adopts a two-phase delayed differentiation strategy to make the standard components first and produce the finished multi-goods in the second phase. Implementing a partial subcontracting option (with the additional expense) for the standard parts helps us to expedite the required uptime in the first phase. A screening process identifies the faulty items that need to be removed to ensure the in-house production quality. A multi-shipment plan delivers the finished lot of end-products to clients in fixed time intervals. This study optimizes the overall operating expenses of this intra-supply chain system, including fabrication, delivery, and client stock holding, through our proposed modeling, formulation, and optimization procedure. In addition, this study gives a numerical demonstration of the obtained results’ applicability and usefulness to managerial decision-making.