Nowadays, online shopping plays a vital role in providing services and delivering goods to customers in the context of business intelligence and e-commerce. This research analyzes the customer purchase data of an Iranian online shopping company in Tehran. Among the available datasets provided by the company, 200 thousand records of one week of transactions have been selected for the present study. Several classification methods (i.e., Random Forest, gradient-boosted trees, K-Nearest Neighbor (KNN), Naïve Bayes, Kernel Naïve Bayes, and Neural Networks) and clustering approaches have been applied to discover the knowledge and patterns. The results show that before balancing the dataset, the KNN algorithm with K=5 is the best classification method among the existing methods. However, after balancing, gradient-boosted trees outperform the other classification methods. For clustering methods, the results show that the K-Means algorithm with K=3 is more efficient regarding the average within centroid distance for each cluster. Finally, concluding remarks and suggestions for future studies are stated.
Warm air infiltration is a hidden phenomenon that can go unnoticed for weeks, months, or even years in cold storage envelopes. It is a common source of energy wastage that can be explored to achieve significant energy and cost savings. This research assesses warm air infiltration into fruit cold storages using a case study approach for an international fruit exporter based in Kenya, covering baseline study, root cause analysis, and developing a risk-based mitigation strategy to minimize the infiltration rates. Thermal graphic measurements, electricity bills, and on-site observation of the operation patterns provided source data. An Ishikawa diagram and a risk-based Failure Mode and Effect Analysis (FMEA) were used to identify and prioritize root causes, respectively, and a modified decision tree was then utilized to structure the mitigation strategy. The study established a lack of awareness of cold storage operations, irregular and untimed maintenance of components, broken door seals, and inconsistency in the frequency of cold storage door openings as the critical root causes for the warm air-infiltration challenge. It was further revealed that cold storage facilities need to take advantage of the available sensory and operational data to introduce maintenance management systems, temperature-airflow monitoring systems, and environmental control devices to complement the functionality of cold storage components. To operate fruit cold storages optimally and efficiently, facilities management must comprehensively understand the sources of temperature variations and adopt mitigation strategies that minimize warm air infiltration. There is no one-size-fits-all approach to reducing warm air infiltration; thus, both systemic and behavioral approaches must be adopted and integrated into cold storage operations.
This study introduces an advanced performance measurement system for 31 municipalities in Tehran and Shahriar, integrating the Balanced Scorecard (BSC) and Data Envelopment Analysis (DEA) methodologies. The combination of BSC and DEA was chosen because BSC offers a multidimensional framework for assessing performance from diverse perspectives, while DEA provides a quantitative tool for evaluating efficiency, particularly useful when dealing with multiple inputs and outputs. Together, they allow for both qualitative and quantitative evaluation of municipal performance, addressing the need for comprehensive performance assessment. However, traditional DEA models often fail to account for dynamic changes and intermediate linkages between these perspectives over time. The Dynamic Network Slacks-Based Model (DNSBM) of DEA, proposed in this study, addresses these limitations by incorporating both network interdependencies and dynamic changes in performance evaluation. Field studies and expert interviews revealed interconnections between BSC perspectives, and dynamic changes were modeled by linking networks over multiple periods. The model estimated efficiency values for each period, showing an average overall score of 0.857, with specific scores for financial (0.94), learning and growth (0.83), internal processes (0.96), and customer (0.34). Statistically significant correlations were found between most perspectives, except financial and learning/growth. The model identified dynamic performance trends, inefficiency levels, and strategies to improve underperforming DMUs, offering a comprehensive approach to enhancing municipal performance.
Human resources are undoubtedly the most crucial resources of organizations. A significant part of the human resources includes retirees of the organization. Organizations must provide adequate support to acknowledge their years of service to facilitate retirees' adaptation to new circumstances. This study investigates retirement adjustment among personnel of the Yazd Electricity Distribution Company (YEDC). For this purpose, the challenges and problems that discourage people from retiring are identified first. Based on these challenges, retirement adjustment solutions are proposed. The retirement adaptation solutions have been ranked based on three criteria: financial promotion, identity improvement, and interaction improvement, using Shannon’s Entropy and TOPSIS techniques. The extraction of factors in two categories of challenges and solutions represents a contribution of this research. Furthermore, this research examines the different views of personnel with varying job levels, work experience, and genders through statistical analysis, which is another contribution of this research. Finally, the results of this research show the ranking of solutions using combined Shannon’s Entropy and TOPSIS techniques, which emphasize the novelty of this research.
The increase in the number of tourists around the world has increased the necessity of planning for the promotion and development of tourism in order to minimize the environmental effects of tourism and maximize the social and economic benefits of tourism destinations. According to the current necessity, in this article, the identification and evaluation of the cultural performance of the ecotourism residences of Mazandaran province from the point of view of tourists has been discussed. The data of the present study is from the narratives related to the cultural strategies of the ecotourism centers of Mazandaran province in online social media. Narratives and data were obtained by searching tourism websites. In this article, the efficiency value of 39 ecotourism centers in Mazandaran province of Iran has been obtained with CCR input nature models and ranked with the Andersen-Petersen super-efficiency model. These ecotourism centers were evaluated with three entrances and three exits, and the inputs were the total land area of the ecotourist residence (square meters), the number of rooms in the ecotourism residence, and the maximum capacity of the ecotourism residence (persons). Also, the overall cleanliness of the ecotourism residence, the way of hosting the ecotourism residence personnel and staff, and the services of the ecotourism residence personnel and staff from the point of view of tourists were considered as the outputs of this study. The ranking of Decision-Making Units (DMUs) is also given. And finally, some solutions have been proposed to improve the situation of ineffective ecotourism resorts.
