Into the Future: Exploring AI-Enhanced Person-Organization Fit through Cultural Understanding and Supportive Work Climate

This study integrates the person-organizational fit perspective with the technology-organization-environment (TOE) model to investigate how newcomers\u27 AI integration (T) affects their organizational culture comprehension (O) and person-organizational fit, as well as the role of a supportive work climate (E) in this mechanism. We surveyed 229 newcomers from technology firms in China and tested the hypothesized relationships using Mplus 8. Our results suggest that newcomers’ AI awareness is positively associated with their organizational culture comprehension, which mediates the relationship between AI awareness and person-organizational fit. We also find that a supportive work climate moderates the impact of organizational culture comprehension on person-organizational fit. These results shed light on a newcomer-focused perspective on the TOE and AI-facilitated HRM practices, with important theoretical and practical implications

Research on Optimization of Delivery Routing with Time Window for Enhancing Economic and Sustainable Goals Using an Improved PSO-SA Algorithm

61 pagesThis paper addresses two significant challenges facing the e-commerce logistics sector: optimizing next-day delivery routing with strict time windows and determining the optimal fleet composition of electric and diesel vehicles. We introduce a mixed-integer linear programming model for the Next-Day Green Hybrid Vehicle Routing Problem with Time Windows (NDGVRP-TW), simultaneously aimed at reducing carbon emissions, enhancing profitability, and improving customer satisfaction. Three fleet configurations—pure electric, pure diesel, and hybrid—are comparatively analyzed to identify the most profitable and environmentally sustainable composition. To effectively address this NP-hard problem, we developed a modified Particle Swarm Optimization algorithm integrated with Simulated Annealing (mPSO-SA). This algorithm uniquely incorporates random reshuffling of personal best positions and perturbation steps of the global best solution, mitigating premature convergence commonly observed in traditional optimization approaches. Computational experiments utilizing real-world data demonstrate that the mPSO-SA algorithm significantly surpasses conventional Genetic Algorithms (GA) and standard Particle Swarm Optimization (PSO), achieving over 25% improvements in convergence speed and solution quality. Our results reveal that hybrid fleets substantially outperform homogeneous fleet configurations, achieving considerable operational advantages including an 18.8% reduction in labor costs, a 26.3% decrease in distance-related expenses, and an impressive 77.7% reduction in carbon emissions compared to pure diesel fleets. Additionally, the hybrid approach notably decreases late-delivery penalties by 28.6% relative to pure electric fleets, effectively balancing the environmental benefits of electric vehicles against their operational limitations, particularly their constrained driving ranges. Our sensitivity analyses generate important managerial insights, emphasizing that fleet managers should strategically align vehicle capacities to prevent route inefficiencies, proactively adapt routing strategies in response to increasing operational costs, and meticulously schedule deliveries to minimize late penalties. Implementing these insights facilitates substantial improvements in profitability, resource optimization, and customer satisfaction compared to conventional benchmarks, providing enterprises with actionable, data-driven strategies for sustainable competitive advantage

Calciphytoliths (calcium oxalate crystals) analysis for the identification of decayed tea plants (Camellia sinensis L.)

AbstractThe history of tea is poorly known, mainly due to the questionable identification of decayed tea plants in archaeological samples. This paper attempts to test the utility of calciphytoliths (calcium oxalate crystals) for the identification of tea in archaeological samples. It provides the first survey of the macropatterns of calciphytoliths in several species of Theaceae and common non-Theaceae plants. Crystals were extracted from 45 samples of tea, Theaceae and common non-Theaceae plants and detected microscopically between crossed polarizers. In tea plants, druse and trichome base are the most distinctive crystals. Druses have the smallest diameter (11.65 ± 3.64 μm) and trichome bases have four distinctive straight and regular cracks, similar to a regular extinction cross. The results provide morphological criteria for distinguishing tea from other plants, specifically the presence of identifiable druses together with calcified trichome bases. The implications are significant for understanding the history of tea and plant exploitation, especially for plants for which the preservation of macrofossils is poor.</jats:p

Exploring the Relationship Between Learning Goal Orientation and Knowledge-Sharing Among Information Communication Technology Consultants: The Role of Incentive Schemes

Knowledge sharing (KS) is critical for consulting companies to develop sustainable competitive advantages. While the importance of KS in the information communication technology (ICT) sector has been proved, the assumed linear relationships in KS mechanisms are confronted with KS dilemmas: consultants’ intention to maximize personal gains from KS resulting in restrained KS efforts, for fear of losing value after sharing knowledge with colleagues. Drawing on motivation theory and goal orientation perspective, this study examines the roles of learning goal orientation (LGO) and incentive schemes in KS among ICT consultants. The multiple regression analyses of 389 consultants’ responses from 14 Chinese and 8 Korean ICT consulting companies demonstrated an inverted U-shape relationship between LGO and knowledge sharing; incentive schemes moderate this relationship. The findings shed light on the knowledge-sharing dilemma, with theoretical implications to research regarding goal-orientation, knowledge sharing, and managerial practices about the motivation and incentives of ICT consultants.</jats:p

Data_Sheet_1_Exploring the Relationship Between Learning Goal Orientation and Knowledge-Sharing Among Information Communication Technology Consultants: The Role of Incentive Schemes.docx

Knowledge sharing (KS) is critical for consulting companies to develop sustainable competitive advantages. While the importance of KS in the information communication technology (ICT) sector has been proved, the assumed linear relationships in KS mechanisms are confronted with KS dilemmas: consultants’ intention to maximize personal gains from KS resulting in restrained KS efforts, for fear of losing value after sharing knowledge with colleagues. Drawing on motivation theory and goal orientation perspective, this study examines the roles of learning goal orientation (LGO) and incentive schemes in KS among ICT consultants. The multiple regression analyses of 389 consultants’ responses from 14 Chinese and 8 Korean ICT consulting companies demonstrated an inverted U-shape relationship between LGO and knowledge sharing; incentive schemes moderate this relationship. The findings shed light on the knowledge-sharing dilemma, with theoretical implications to research regarding goal-orientation, knowledge sharing, and managerial practices about the motivation and incentives of ICT consultants.</p