Sitma (Norway)

ABSTRACT This study examines the financial consequences of ISO 1400 stices. Based on a large international dataset and advanced econometric methods, the analysis reveals that ISO 14001 adoption is positively linked to financial performance. The effect is amplified when firms demonstrate stronger ESG engagement, with environmental, social, and governance pillars each contributing to improved outcomes. Interaction results indicate that certification combined with ESG practices yields the most substantial gains, particularly for smaller firms and those operating in weaker institutional environments. These findings highlight the strategic importance of aligning environmental certification with ESG initiatives to enhance competitiveness, satisfy stakeholder expectations, and promote sustainable transitions. The study provides actionable implications for managers, policymakers, and investors seeking to integrate environmental management with responsible corporate governance.

Purpose:The study aimed to compare customers' perceptions of the effect food and service quality on satisfaction and repatronage intention in Tshwane and Manila.Methodology: A quantitative correlational design was employed based on an online survey in which three hundred and twenty-two self-completion questionnaires were successfully completed for data analysis.Results were analysed using the Partial Least Squares Structural Equation Modelling and Multi-Group Analysis.Findings: Both food quality and service quality had significant positive effect on customer satisfaction and repatronage intention for both South Africans and the Filipinos.All other associations showed no statistically significant differences, while food quality and customer satisfaction exhibited a statistically significant difference across the two groups, suggesting that most relationships in the structural model operated similarly across both contexts.Managerial implications: Restaurant managers are therefore encouraged to inculcate strong values in employees about the criticality of food and service quality as strategic marketing weaponry for satisfaction and repatronage intention.Originality: The current study contributes significantly to extant literature on food quality and service quality and their effect on customer satisfaction and repatronage intention within the fast foods restaurant industry.Further study: Although this study proffers different insights, more studies could expand its scope on numerous fronts, one of which could be to explore a comparative study on the determinants of satisfaction and revisit intentions in retail, hotel or air transport business in order to ascertain whether customers' perceptions of the effects of food and service quality differ due to different geographic locations or industrial classification.

Immunization programs in low- and middle-income countries (LMICs) rely on large fleets of powered cold chain equipment (CCE), much of which is now aging, inefficient, or technologically obsolete. While substantial investments have expanded and modernized CCE inventories, formal frameworks for end-of-life management lag behind, and obsolete units frequently accumulate in facilities, yards, and warehouses. Inadequate decommissioning and disposal create environmental, occupational, programmatic, and financial risks that are poorly documented and weakly integrated into cold chain and healthcare waste management policies.We conducted a narrative, process-focused review of electrical vaccine refrigerators and freezers in low- and middle-income settings. Normative guidance from global health, environment, and waste agencies was combined with national policies, program and evaluation reports, healthcare waste management assessments, and selected peer-reviewed literature. Sources were included if they described policies, procedures, or practices for decommissioning, removing, or disposing of vaccine CCE. Extracted information was organized along end-of-life lifecycle stages and synthesized narratively.The review identifies a systems framework in which end-of-life CCE presents a complex hazard profile, including ozone-depleting and high-GWP (global warming potential) refrigerants, compressor oils, foams, electronics, and, for some solar units, batteries. Decommissioning can be structured into a governance setup followed by six operational steps from notification and technical condemnation through decontamination, removal, transport, and licensed final treatment, supported by cross-cutting documentation and reporting. When these steps are absent or weak, environmental and climate risks, occupational and community exposures, vaccine potency loss, ghost cold-chain capacity, and higher operating costs are common. Implementation is constrained by fragmented mandates, lack of dedicated financing and contract provisions, limited treatment infrastructure, weak inventories, operational and sociocultural barriers, and inequitable impacts on peripheral facilities and informal waste workers.Decommissioning and safe disposal of vaccine CCE should be treated as routine lifecycle functions and explicitly embedded in cold chain improvement plans, contracts, financing arrangements, and information systems. Applying a structured, stepwise process within existing asset management, healthcare waste management (HCWM), and environmental frameworks can reduce safety and climate risks, improve use of space and resources, and close a long-neglected gap in immunization supply chain performance in LMICs.

Order picking represents the most labor-intensive and costly operation in warehouse management, accounting for approximately 50-65% of total operational costs. This paper presents a comprehensive analysis of order picker path optimization using Traveling Salesman Problem (TSP) heuristics in modern warehouse environments. We develop and evaluate multiple heuristic algorithms including nearest neighbor, 2-opt, 3-opt, and hybrid genetic algorithms for optimizing picker routes in various warehouse configurations. Our approach incorporates real-world constraints such as item weight, congestion factors, and pick frequency distributions. Experimental results from simulations on warehouse layouts ranging from 5,000 to 50,000 square meters demonstrate that the proposed hybrid genetic algorithm with 2-opt local search refinement achieves an average path reduction of 23.7% compared to traditional S-shape routing, with computational times suitable for real-time implementation. The framework has been validated using data from multiple distribution centers, showing consistent improvements in picker productivity and overall warehouse throughput.

High velocity data streams as it is generated by large-scale digital ecosystems presents key challenges for anomaly detection in real-time because of non-stationarity, high dimensionality, and dynamic temporal correlations. This research proposes a novel hybrid deep learning architecture to overcome the abovementioned challenges, which uses adaptive spatiotemporal encoding with hierarchical feature fusion. The proposed framework is inspired by a combination of temporal convolutional blocks characterized by lightweight operations with recurrent memory augmented attention layers which can efficiently capture both short term fluctuation and long-range dependency. To counteract the problem of false-positives when there are rapid distributional changes, a dynamic embedding alignment mechanism is proposed which dynamically re-calibrates latent feature spaces with changing baseline patterns. A dual-path inference pipeline isolates structural anomalies from those caused by the context thereby ensuring that the process is scalable without sacrificing detection fidelity. The architecture is optimized for inferencing with low-latency operation using parallelized streaming operators, and is therefore deployable in high throughput environments. The experimental results indicate high localization of illicit behaviors and the capacity of generalized adaptability and diversity types of the real-time data to dispel the traditional detection benchmark.

Purpose – This study investigates the role of AI-driven business analytics in strengthening financial risk management within the banking and insurance sectors. It examines the extent of AI adoption, its impact on organizational resilience, the challenges encountered during implementation, and the future prospects of AI integration in risk management practices. Design/methodology/approach – A quantitative research design was employed using a structured questionnaire administered to 350 professionals across banking and insurance organizations. The survey measured four core constructs—AI adoption, impact on risk management, challenges, and future prospects—using a five-point Likert scale. Descriptive statistics, reliability testing, and Pearson’s correlation analysis were conducted to ensure measurement validity and to examine interrelationships among constructs. Findings – Results indicate moderately high adoption of AI (M = 3.72, SD = 0.64) and a strong positive impact on risk management (M = 3.88, SD = 0.59). Respondents acknowledged moderate challenges (M = 3.41, SD = 0.70), including cost, regulatory uncertainty, and lack of skilled professionals. Despite these barriers, future prospects of AI in financial risk management were viewed with high optimism (M = 4.12, SD = 0.55). Correlation analysis confirmed significant positive associations between AI adoption, enhanced risk management, and future outlook, while challenges were negatively correlated with all other constructs. Originality/value – This study contributes to the growing body of knowledge on digital transformation in financial services by providing empirical insights into how AI-enabled analytics are reshaping risk management. The results indicate that the strategic role of AI in banking and insurance is not only significant but also that organizational, regulatory, and ethical issues are urgent in order to achieve the maximum benefit.

Purpose Total quality management (TQM) has traditionally been viewed as an enabler of operational excellence, yet its role as an indispensable driver of sustainability performance (SP) remains underexplored. Drawing on the natural resource-based view (NRBV) and dynamic capabilities theories, we investigate whether TQM practices constitute necessary rather than merely helpful conditions for driving SP among SMEs in the manufacturing sector. Design/methodology/approach Quantitative data were collected from 200 owner-managers of manufacturing firms in Ghana. Using Necessary Condition Analysis (NCA), this study identifies which TQM practices are “must-have” conditions for achieving sustainability performance. Findings The NCA results revealed that supplier quality management (SQM) is the most critical TQM dimension and is a significant bottleneck for achieving sustainability performance. Proactive risk management (PRM), management leadership (MGL) and data transparency (DTS) also emerged as necessary conditions. Although product design (PRD), quality circles (QCS) and cross-functional team development (CTD) show medium-necessity effects, they remain essential supporting conditions. The findings emphasise that all seven TQM dimensions must reach minimum threshold levels to enable high levels of sustainability performance. Practical implications TQM dimensions provide a bundle of complementary capabilities that support the development of a sustainability strategy. These capabilities enable SMEs in the manufacturing sector to establish resilient value chains aligned with global sustainability goals. Among these capabilities, firms should prioritise supplier quality management and proactive risk management, as both dimensions consistently support sustainability goals across environmental, social and economic domains. Data transparency is foundational but requires integration with other dimensions for sufficiency. From the NRBV perspective, TQM should be viewed as a strategic capability that enables manufacturing firms to achieve sustainability through resource-efficient and green manufacturing practices. Manufacturing firms are encouraged to integrate environmental thinking into product design, adopt zero-waste innovations, and build strong partnerships with environmentally responsible suppliers. Originality/value The study extends the sustainability and quality management literature by demonstrating that TQM practices are not only contributors but also critical prerequisites for SP. It offers operational directions and recommendations for manufacturing firms, particularly in emerging economies, on prioritising and committing to quality initiatives essential for sustainable competitiveness. Ultimately, sustainability in manufacturing firms cannot be achieved through isolated practices but requires a consistent and stepwise application of these practices in the appropriate order and proportions.