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This research intends to develop a model for predicting employees at a high-risk attrition and identify the most important factors affecting them.

In this study, using the triangulation technique of a mixed research method, the employee attrition problem is investigated by identifying its affecting factors. For that matter, data related to the human resources department of a pharmaceutical company in Iran are used. And to achieve the intended goal, advanced data mining algorithms and interviews with human resource managers are applied.

A model for predicting employees at a high-risk attrition is presented based on the gradient boosting machine algorithm with 89% accuracy. The use of the mixed research approach shows that qualitative and quantitative methods can be more effective in identifying the factors affecting employee churn or loss of staff. The results also contain a new situation arising out of the COVID-19 pandemic and remote working scenarios having impact on employee attrition. Finally, human resource policies are presented based on variables related to each of the identified factors.

The novel contributions of this study include real data related to a leading pharmaceutical company as well as a combination of two quantitative and qualitative methods. The hybrid approach can identify the reasons for attrition and, consequently, retention policies to benefit from the advantage of both approaches. Data mining can be useful to identify the factors, which are usually not mentioned in termination interviews, such as direct managers. On the other hand, the results obtained from termination interviews can also include features that the authors cannot identify through data mining, which are specifically related to the characteristics of the pharmaceutical industry such as building a more professional career path. From a practical perspective, since this company specializes in pharmaceutical marketing in a new way and is primarily comprised graduates, it is important to note that the churn of specialized people disperses organizational and technological know-how. On the other hand, the pharmacist community in Iran is small, and their attrition might adversely affect not only the reputation of an organization but the employer's brand as well. So, this research would help other similar firms in retaining their valuable human capital.

This paper aims to explore product pricing and green promotion effort policies and further analyzes the influences of financing interest rate, green promotion effort and free-riding behavior on the optimal strategies.

Research will be conducted with the aid of Stackelberg game research method, considering that the manufacturer has financial constraints and financing from e-commerce platform, and consumers have dual preferences, based on the two models of no green promotion effort for physical store and green promotion effort for physical store to explore dual-channel green supply chain strategies.

This research puts forward the following findings, in the two models: the rise in financing interest rate leads to an increase in wholesale and selling prices of dual channels and a decrease in demand of dual channels. The green promotion effort has a positive impact on wholesale prices, selling prices and demand of dual channels. The rise of free-riding rate makes offline wholesale and selling prices fall, whereas online wholesale and selling prices rise.

This research results can provide reference for the decision-making in the context of supply chain financing and free-riding.

This study aims to introduce a new methodology for generating synthetic images for facility management purposes. The method starts by leveraging the existing 3D open-source BIM models and using them inside a graphic engine to produce a photorealistic representation of indoor spaces enriched with facility-related objects. The virtual environment creates several images by changing lighting conditions, camera poses or material. Moreover, the created images are labeled and ready to be trained in the model.

This paper focuses on the challenges characterizing object detection models to enrich digital twins with facility management-related information. The automatic detection of small objects, such as sockets, power plugs, etc., requires big, labeled data sets that are costly and time-consuming to create. This study proposes a solution based on existing 3D BIM models to produce quick and automatically labeled synthetic images.

The paper presents a conceptual model for creating synthetic images to increase the performance in training object detection models for facility management. The results show that virtually generated images, rather than an alternative to real images, are a powerful tool for integrating existing data sets. In other words, while a base of real images is still needed, introducing synthetic images helps augment the model’s performance and robustness in covering different types of objects.

This study introduced the first pipeline for creating synthetic images for facility management. Moreover, this paper validates this pipeline by proposing a case study where the performance of object detection models trained on real data or a combination of real and synthetic images are compared.

The aim of this paper is to explore the implementation of an integrated lean and ISO 14001 approach in meat industry for environmental performance and examine a proposed conceptual framework by capturing insights from lean and ISO 14001 experts in New Zealand (NZ).

Semi-structured interviews have been conducted with a group of consultants (lean and ISO 14001) to evaluate the suitability of an integrated lean and ISO 14001 approach in the meat industry for environmental performance. A conceptual framework from literature has guided this study leading to its further development based on the empirical evidence collected.

Findings have illustrated a synergistic positive impact of lean and ISO 14001 implementation as an integrated approach for sustaining environmental performance in the meat industry. A joint implementation program provides more clarity in aligning ISO 14001 operational procedures with lean tools and techniques for an enhanced environmental performance outcome.

The application of an integrated lean and ISO 14001 framework is proposed in this paper, which can help industry practitioners and academia in developing a joint implementation strategy and conducting future research.

To the best of the author’s knowledge, this study is the first to assess the effective implementation of lean and ISO 14001 as an integrated approach in the NZ meat industry.