In today’s rapidly changing business environment, franchisees’ market responsiveness is a way to create a sustainable competitive advantage. Drawing on the resource-based view, dynamic capability perspective and relational view, this study examines the relationships between franchisor resources, relational capital, market responsiveness, and franchisee performance. Based on data collected from 152 franchisees in a convenience store chain in Taiwan, the analysis revealed that market responsiveness, franchisor resources and relational capital are all positively related to franchisee performance. Franchisor resources and relational capital positively affect franchisee performance both directly and indirectly through market responsiveness. Furthermore, relational capital has the strongest effect on franchisee performance.

In this charge we designated a Hilbert-Johnson process by coupling of heterocyclic N-silylated with benzyl chloride at 100°C using the calcined red algae (CRA) doped with ammonium sulfate (AS), AS@CRA as a heterogeneous catalyst. The resulting examination systems, which included atomic absorption, BET methodology and X-ray diffraction (XRD), scanning electron microscopy (SEM/EDX), and Fourier transform infrared spectroscopy (FT-IR), were employed to describe these catalysts. The effect of catalyst and alkylated agent were extensively studied. This catalyst can also be recycled several times in this condensation, and lastly, we suggested a probable answer mechanism for this process. Moreover, our molecular docking investigation revealed the anti-tuberculosis potential of the synthesized compounds. Notably, the drug isoniazid exhibited higher binding energies compared to the products 2a, 2b, and 2c. Additionally, the ADME study suggests that highly efficacious synthetic compounds may possess anti-tuberculosis properties.

This study investigates the complex relationship between organizational structure and strategic planning, emphasizing how business process mapping contributes to decision-making frameworks in organizational design. Through a qualitative case study approach, it illustrates the benefits of integrating organizational structure with business processes to enhance the implementation of an organization's strategic plan. The research highlights the RACI Matrix as a crucial analytical tool in organizational design, ensuring clarity in roles, responsibilities, and accountability while supporting effective decision-making in business processes. Findings underscore the importance of structuring organizations based on optimized business processes to drive efficiency and strategic alignment. The novelty of this research lies in its methodical approach to translating strategic objectives into actionable business process maps, which subsequently serve as the foundation for designing organizational structures through RACI matrix analysis to achieve enhanced role clarity and adaptability. This alignment optimizes operational coherence and strengthens long-term organizational resilience. The study offers a structured framework for objectively designing organizational structures that directly support strategic objectives, providing valuable insights for practitioners and decision-makers in organizational science.

The maximum tardiness reflects the worst level of service associated with customer needs; thus, the principle that seru production reduces the maximum tardiness is investigated, and a model to minimize the maximum tardiness of the seru production system is established. In order to obtain the exact solution, the non-linear seru production model with minimizing the maximum tardiness is split into a seru formation model and a linear seru scheduling model. We propose an efficient cooperative algorithm using a genetic algorithm and an innovative reinforcement learning algorithm (CAGARL) for large-scale problems. Specifically, the GA is designed for the seru formation problem. Moreover, the QL-seru algorithm (QLSA) is designed for the seru scheduling problem by combining the features of meta-heuristics and reinforcement learning. In the QLSA, we design an innovative QL-seru table and two state trimming rules to save computational time. After extensive experiments, compared with the previous algorithm, CAGARL improved by an average of 56.6%. Finally, several managerial insights on reducing maximum tardiness are proposed.

A preparatively convenient method is proposed for the synthesis of new 1-oxo-3,4-dihydro-1H-pyrrolo[2,1-с][1,4]oxazine-8- 4a-e and 4-oxo-4H-pyrrolo[2,1-c][1,4]benzoxazine-3-carboxylic acids 5a-f that is based on the interaction of methyl (2-oxomorpholin-3-ylidene)ethanoates 1a-e and methyl (2-oxo-2H-1,4-benzoxazine-3(4H)-ylidene)ethanoates 2a-f with 2-bromo-1,1-diethoxyethane. Obtained acids were transformed into the corresponding tert-butyl carbamates 6a-e, 7a-f and N-alkyl(aryl)carboxamides 11a-i, 12a-d. By treating tert-butyl carbamates 6a-e, 7a-f with hydrogen chloride, 8-amino-3,4-dihydro-1H-pyrrolo[2,1-c][1,4]oxazin-1-ones 8a-e and 3-amino-4H-pyrrolo[2,1-c][1,4]benzoxazin-4-ones 9a-f were obtained. By acylation of amines 8a-e, 9a-f with acetic anhydride, benzoyl chloride, methanesulfonyl chloride, and p-toluenesulfonyl chloride, corresponding N-acetamides 13a,b, 14, N-benzamides 15, 16, N-methanesulfonamides 17, 18, and N-p-toluenesulfonamides 19, 20 were synthesized. In total, 30 new derivatives of 1-oxo-3,4-dihydro-1H-pyrrolo[2,1-c][1,4]oxazinones and 27 new 4-oxo-4H-pyrrolo[2,1-c][1,4]benzoxazinones were obtained.

Corporate social responsibility (CSR) has gained research attention as the result of the Sustainable Development Goals (SDG), which focus on responsible consumption and production (SDG-12). However, previous studies mainly focused on Carroll’s pyramid of CSR and other facets of CSR practices need to be further explored. The objective of the study is to examine the impact of CSR practices on customer purchase intention in the clothing industry by integrating the Triple Bottom Line (TBL) model and ISO26000 best practices with the Signalling theory as the theoretical foundation. Through an online survey, a total of valid 182 responses were obtained via purposive sampling. Multiple regression was utilized for data analysis. The results show that economic CSR had the strongest impact on customer purchase intention, followed by environmental, social, and customer issues. Surprisingly, there was no significant impact between fair operating practices and customer purchase intention. The current study is unique by integrating the TBL framework with the customer-related ISO26000 CSR practices in a single framework and utilizing the Signalling Theory as the underpinning theory to explain the relationships, which is novel in an emerging market. The results provide insightful implications to the clothing company's management to emphasize the (social, economic, environmental, and customer issues) CSR attributes to guarantee business sustainability and attract consumers in this competitive marketplace.

Diabetes mellitus is a serious health disease that affects people all over the world. The number of persons identified with diabetes mellitus rises each year. α -Glucosidase is a digestive enzyme used to control diabetes mellitus. The searching for new potent α-glucosidase inhibitors capable of delaying carbohydrate digestion in the human body is an important strategy towards control of diabetes mellitus. In this work, a series of quinoline-based Schiff base derivatives already identified as α-glucosidase inhibitory activity was studied by using 2D/3D-QSAR approach. The best HQSAR/A-B-C-H-Ch-DA and CoMSIA/SEDA models were constructed using thirteen molecules in the training set, resulting in favorable values of Q2 (0.834 and 0.607), and high values of R2 (0.985 and 0.912), respectively. The generated HQSAR/A-B-C-H-Ch-DA and CoMSIA/SEDA contour plots were precious for designing and enhancing the α-glucosidase inhibitory activity of quinoline-based Schiff base molecules. Considering these results, two novel α-glucosidase compounds were designed to possess significant activity. The newly suggested molecules showed good outcomes in the preliminary in silico ADME/Tox evaluations. Molecular docking results revealed that the new designed inhibitors have a good stability in the active pocket of the studied receptor compared to voglibose, clinically used as an α-glucosidase inhibitor. MD simulation and MM-GBSA results confirmed the molecular docking outcomes. Finally, DFT analysis was useful in determining the most electrophilic and nucleophilic centers of the two designed α-glucosidase inhibitors.

Production management operating in recent competitive marketplaces must satisfy the client desired quality and shorter order lead-time and avoid internal fabricating disruption caused by inevitable defects and stochastic equipment failures. Achieving these operational tasks without undesirable quality goods, missing due dates, and fabrication interruption help the management minimize operating expenditures. Motivated by assisting manufacturing firms in the situations mentioned this study explores a manufacturing system that features quality reassurances through reworking or removal of defectives, correction of probabilistic failures, and partial overtime and outsourcing options for reducing uptime. This study finds the function of system operating expenditures through model building, mathematical formulations, optimization approaches, and algorithm proposition, shows its convexity, and derives the optimal batch time for the studied manufacturing model. Finally, this study offers numerical illustrations to confirm our work’s applicability and disclose its capability to provide various profound crucial system information that helps the management make strategic operating decisions.

In an increasingly advanced digital era, micro, small, and medium enterprises (MSMEs) face new challenges and opportunities in enhancing their sales performance. The use of innovative technologies, such as ChatGPT and Customer Relationship Management (CRM), is key to improving operational efficiency and strengthening MSME competitiveness. This study aims to analyze the impact of integrating ChatGPT and CRM on MSME sales performance with operational efficiency as a mediating variable. The research employs a quantitative approach using SEM-PLS methodology to explore the relationships between relevant variables. The study was conducted on 100 MSMEs in Subang Regency, Indonesia, using an online questionnaire as the data collection tool. The findings indicate that the integration of ChatGPT and CRM significantly affects MSME sales performance in Subang Regency, with operational efficiency as a mediating variable. First, ChatGPT has been shown to have a significant positive impact on MSME sales performance. This technology facilitates the adoption of new technologies, enhances customer interaction, and enables better service personalization, which directly impacts increased sales volume, sales growth, and revenue. Second, effective CRM implementation also demonstrates a significant positive influence on MSME sales performance. Good customer data management, customer satisfaction, and customer loyalty contribute to increased sales volume, sales growth, and revenue. Third, operational efficiency proves to play a significant mediating role in the relationship between ChatGPT and CRM integration and MSME sales performance. Improvements in operational efficiency through reduced processing times, optimized resource use, and cost reduction support increased sales volume, sales growth, and revenue.

In an increasingly advanced digital era, micro, small, and medium enterprises (MSMEs) face new challenges and opportunities in enhancing their sales performance. The use of innovative technologies, such as ChatGPT and Customer Relationship Management (CRM), is key to improving operational efficiency and strengthening MSME competitiveness. This study aims to analyze the impact of integrating ChatGPT and CRM on MSME sales performance with operational efficiency as a mediating variable. The research employs a quantitative approach using SEM-PLS methodology to explore the relationships between relevant variables. The study was conducted on 100 MSMEs in Subang Regency, Indonesia, using an online questionnaire as the data collection tool. The findings indicate that the integration of ChatGPT and CRM significantly affects MSME sales performance in Subang Regency, with operational efficiency as a mediating variable. First, ChatGPT has been shown to have a significant positive impact on MSME sales performance. This technology facilitates the adoption of new technologies, enhances customer interaction, and enables better service personalization, which directly impacts increased sales volume, sales growth, and revenue. Second, effective CRM implementation also demonstrates a significant positive influence on MSME sales performance. Good customer data management, customer satisfaction, and customer loyalty contribute to increased sales volume, sales growth, and revenue. Third, operational efficiency proves to play a significant mediating role in the relationship between ChatGPT and CRM integration and MSME sales performance. Improvements in operational efficiency through reduced processing times, optimized resource use, and cost reduction support increased sales volume, sales growth, and revenue.