Ali Reza Afshari

International peer-review E-Journal.

Last-mile delivery (LMD) is essential in supply chains, and providers of logistics services are aware that they must adapt to changing customer and society expectations, competition challenges, and modern technologies. In light of the importance of artificial intelligence (AI) in modern technologies, this article employed a narrative literature review to recognize impacts of AI-powered technologies that aid in optimizing the LMD component. For this study, two possible classes of technologies were considered: tangible technologies, such as robots, drones, and autonomous vehicles, and intangible technologies, such as decision support tools and operating systems. Thus, this article frames potential developments in modern LMD, taking into account the fact that technological advancement brings both opportunities and challenges. According to this literature review, the modern version of LMD is capable of providing services that are both more productive and more sustainable, thus satisfying demands for better services. Last but not least, another goal of this article was to look into the challenges that limit the benefits of modern LMDs. Finally, suggestions are provided as a resource for practitioners and policymakers working in the supply chain to improve performance.

This study has been done with the aim to identify and rank the financial parameters of public and private banks in the North Khorasan Province. The method of this study was quantitative and cross-sectional survey and based on comparative and field study. In this research, after studying library research and studies and oral interviews, a researcher-made questionnaire was set of the financial parameters of banks. In addition, among 120 employees and 60 managers of government owned branches and privately distributed in the North Khorasan Province. To analyze the information obtained AHP technique for ranking the factors by using Expert Choice software. Results showed that an instantaneous factor with a relative weight of 0,106 is in the first rank followed by the operating cash flow attributable to operational activities with a relative weight of 0,103 ranked as the second and a long-term debt ratio with a relative weight of 0,084 ranked as the third that have importance for the financial parameters of banks.

Information Technology (IT) project success is a research topic that has received attention of academics and practitioners, at least, in the lasted two decades. The selection of an IT project manager with the right skills and competencies is critical to the IT project success. Selecting the best IT project manager among many alternatives is a multicriteria decision making (MCDM) problem. This paper presents a comprehensive literature review of the applying MCDM techniques in IT project manager selection problem. Also, it provides an overview on various criteria used. While there are a few chapters or sections in different books related to this topic, we have not seen any comprehensive review papers or book chapter that can cover it. We end our review paper with recommendations for future research. This paper provides useful insights into the MCDM method and suggests a framework for future attempts in this area for academic researchers and practitioners.

Many Software development organizations suffer chronic problems of cost overruns, schedule slips and projects that do not meet the originally specified functions in almost all software projects. This study is commenced by reviewing existing risk management models. Thereafter, a survey that involved software project managers in Iran was conducted to gather empirical data about the practice of risk assessment. Thirty Software Project managers participated and were interviewed. Structured questionnaires were used to capture information. Observation made from the study show that in Iran, risk assessment is poorly practiced and many projects do not yet practice systematic risk assessment. This is because 83% of software project managers implicitly assess risks and the same percentage (83%) of them uses unstructured approaches, poor risk identification and analysis techniques. It additionally shows that risks are not documented and experiences not properly utilized. This has led to recurring problems. The conclusion drawn indicates that Iran's software project managers need to start assessing risks using proper approaches. Review of existing models showed that these models are complex and may not help address the existing shortcomings. This study proposes a risk assessment framework, which helps managers to simply start assessing, documenting major risks, estimating risks using an objective approach that is based on frequently occurring risks to project likelihood of a risk occurring and subjective approach where objective approach is not applicable. It also supports qualitative risk estimation technique using prearranged risk estimation matrices and is supported by a tool that collects and stores risk data for analysis and improvement purposes.

The main objective of this paper is to develop a systematic method for identifying the best among the candidates in the process of construction project manager selection by applying two methods. The proposed method combines the Delphi method and the fuzzy linguistic evaluation to enhance selection. The outcome of this study addresses the issue of high error in decision making, which is a very common problem in the construction industry. The models were examined using a case study in a project-based organization for selecting the most suitable project construction manager, in which three candidates under 14 different subcriteria are evaluated and prioritized by three decision makers. The results show that the proposed model performs very well and can improve efficiency in the decision-making process.