Improving the quality of strategic decision-making process in universities through employing expert systems: A case study from a developing country

Strategic decisions represent the fundamental core of the strategic planning process and strategic management in universities and they are essential in shaping the universities' policies and achieving their strategic goals. Without those strategic decisions, the universities stand unable to achieve their strategic goals and mission; therefore, specialists realized the critical importance of improving the quality of strategic decision-making in the current complex fast-changing environment that its dynamism continuously increases and which is based on the use of cutting-edge information and communications technology (ICT). Undoubtedly strategic decision-making process requires processing a huge amount of information with different robust smart methods and the extensive use of experts knowledge. There are many discussions about the uses and applications of expert systems (ESs), which are evolving rapidly in solving real problems in many fields that require experienced experts with deep sound experiences, and despite these many applications in many different fields and domains. Literature reveals that there is a scarcity of scientific research on how to employ expert systems to raise the quality of strategic decision-making processes in universities. Thus the purpose of the research is to fill this research gap by investigating how expert systems will enhance the quality of the strategic decision-making process in universities. The research design is a case study applied in Ain Shams University as a model of public universities in a developing country. This research makes a new research contribution by suggesting a futuristic proposal for improving the quality of the strategic decision-making process in universities through employing expert systems that are based on the theoretical framework of the research and the results of the field study.

Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network

In this paper, RNN (Recurrent Neural Network) algorithm is used to conduct an in-depth analysis of HR strategic decision-making and an HR strategic decision model is constructed for simulation. The four evaluation dimensions of index screening are extracted, the generalized gray correlation analysis is applied to screen the initial selection indexes of HR strategic decision-making, and then the HR strategic decision-making index system of power supply enterprises is constructed. On this basis, the applicability of the BP neural network in HR strategic decision-making is analysed and demonstrated, a BP neural network-based HR strategic decision-making model for power supply enterprises is constructed, and the rationality of the model is illustrated through the model training and testing. Finally, an empirical study is conducted with S power supply company as an example to illustrate the operability of the BP network model for HR strategic decision-making. The results of this paper provide a scientific basis for human resource decision-making in power supply enterprises and provide theoretical support for promoting the healthy development of power supply enterprises. Improving the level of human resource management can make fuller use of human resources and realize the strategic goals of the enterprise. A strategy for optimizing the training of hybrid convolutional neural networks is proposed, using an exponential linear unit activation function to solve the problem of neuron dead zones, a hybrid pooling strategy is used to improve the problem of feature information loss in maximum pooling processing, and an improved cross-entropy loss function is used to solve the problem of insufficient learning of difficult classification samples. The optimization of the model training process is finally completed, and the recommendation quality is improved. The Bayesian probability distribution table is learned to be filled in the expert data set; finally, the accuracy and effectiveness of the model are tested on the experimental platform. The results of the experiments show that the established Bayesian model beats the platform’s built-in intelligent method with a 78.2% win rate. That is, the model can make intelligent recommendations for strategies in staffed and unmanned platform decision-making and command-and-control combat units to execute tactical actions to achieve the best operational effectiveness.

Evaluating Nurse Data Navigation Training Program: A Quality Improvement Project

Nursing ability to navigate data by sourcing, visualizing, and managing data provides for skill and insights development. Effectiveness of clinical, operational and strategic decision making is underpinned by sound understanding of the data. The object of this quality improvement project is to design, deliver and evaluate a nursing specific training program using spreadsheet software Excel to improve nurse competence and confidence in data navigation.

Artificial Intelligence potential within airlines: a review on how AI can enhance strategic decision-making in times of COVID-19

Purpose: Airline strategy relies on the competitive environment analysis and the management of resources. Artificial Intelligence (AI) algorithms are being increasingly deployed throughout several industries. COVID-19 has further stressed a sector where firms have historically struggled to sustain profitability.The purpose is to explore the potential of AI applications regarding strategic decision-making in airlines in times of crisis and to depict a roadmap to encourage scholars and practitioners to jointly implement these tools within corporations.Design/methodology/approach: This study firstly reviews the state-of-the-art regarding transport organization trends with focus on airline strategy and finance as well as AI tools, supported by the collaboration of a former airline digitalization strategist. Secondly, the potential of the latter to be applied in those functions is analyzed, considering different Machine Learning (ML) methods and algorithms.Findings: Some applications or pathways are identified as of particular interest for the airlines’ strategic decision-making process. Most of them are based on ML algorithms and training methods that are currently underused or disregarded in certain business areas, such as Neural Network models for unsupervised market analysis or supervised cost estimation.Research limitations/implications: Focus is on airline strategy and finance, keeping engineering or operational applications out of the scope.Practical implications: Proposed guidance may promote the deployment of AI tools which currently lack practical implementation in certain business areas.Social implications: Showcased guidance may revert into a closer collaboration between business and academia.Originality/value: Comprehensive review of current airlines’ strategic levers and identification of promising AI pathways to be further explored.

Rojiroti: innovative microfinance in India

Case overview Micro Finance Institution (MFI) named Rojiroti had been doing good work for weaker sections of the society and had brought about significant transformation in the lives of poor people, especially the Scheduled Castes, in villages of Patna district, the capital city of Bihar, India. Rojiroti was run by Centre for Promoting Sustainable Livelihood (CPSL) and had tested successfully a unique innovative model in micro financing which focused on helping the weaker sections by addressing their imminent needs which usually required very small loan amounts. With the various types of benefits people got from buying government subsidized ration to health and education in family to construct home or buy small livelihood assets. The beneficiaries developed high level of respect and trust for the MFI, Rojiroti. Rojiroti had received international recognition from universities such as University of Nottingham, UK; the University was not only researching on the model and its contributions to society, but also had supported it with funding to cater to its audience. Rojiroti did not believe in just providing finance to people like other microfinance institutions (MFI) or corporate social responsibility (CSR) funding by private and public sector organizations; its model focused more on creating capacities in the beneficiaries to sustain their livelihoods. However, after a decades time, Sunil, the protagonist in the case found himself in a situation where he had to decide for the future journey of Rojiroti after having reached a decent stage of growth The case discusses the journey of Rojiroti where the protagonist Sunil had a significant role to play and dwells upon the Rojiroti business model, its beneficiaries and value offerings to them, the changing environment outside and leaves the discussion open on the question of the choice of best road suited for Rojiroti. Teaching objectives The case is intended for the course on Strategic Management with a focus on business models topic. The case introduces the working of social cooperative business model and the nuances around it which is very much pertinent in today’s times where social enterprises have gained space in business and where businesses work around inclusive business models. The case is designed to provide supplemental support or discussion piece while dealing with business model / cooperative enterprise business model. This case provides opportunity to discuss strategic framework for an organization from the promoter’s perspective. The teaching notes is written from the perspective of the entrepreneur (the protagonist in this case, Sunil) who initiated the enterprise, with a learning goal to empathize and develop skills to have strategic decision making for a social enterprise. Leaning objectives The case is designed to provide supplemental support or discussion piece while dealing with business model / cooperative enterprise business model. This case provides opportunity to discuss strategic framework for an organisation from the promoter’s perspective. The teaching notes is written from the perspective of the entrepreneur (the protagonist in this case, Sunil) who initiated the enterprise, with a learning goal to empathize and develop skills to have strategic decision making for a social enterprise. Supplementary materials Teaching notes are available for educators only. Subject code CSS: 3 Entrepreneurship.