Strategic Planing
Zahra Joorbonyan; Ali Sorourkhah; Seyyed Ahmad Edalatpanah
Abstract
In a competitive environment , various ways to maintain, survive, or grow the organization are conceivable. Among these, marketing experts believe that customer loyalty is one of the most effective tools in facing this challenge. To achieve customer loyalty, various and diverse strategies have been mentioned ...
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In a competitive environment , various ways to maintain, survive, or grow the organization are conceivable. Among these, marketing experts believe that customer loyalty is one of the most effective tools in facing this challenge. To achieve customer loyalty, various and diverse strategies have been mentioned in the literature by researchers and experts, which organizations can use, depending on the conditions, one or a combination of them. In such circumstances, managers usually have several strategies at their disposal and must choose the most appropriate one(s) from among them. The present study aims to provide a combined approach for prioritizing customer loyalty strategies.
This research uses a matrix-based approach to robustness analysis, which can deal with both complexity and uncertainty. The proposed algorithm combines it with strategic planning tools (strategies derived from strategic objectives and SWOT analysis) for prioritizing and selecting strategies. The proposed approach was implemented in a case study on prioritizing customer loyalty strategies for a women's clothing boutique in Ramsar City. Available strategies, influential environmental variables, definitions of future scenarios, and the performance of strategies in different environmental conditions were determined based on the judgments of the problem owner.
The results showed that considering influential environmental variables (national currency value, market access and raw materials, lifestyle changes, investment security, government-private sector relations, and the speed of technological change), supplier selection, contractor selection, and attracting a sponsor have the highest priority strategies. Afterward, environmental advertising, collaborative production, and customer relationship management were placed in subsequent rankings. The outputs of the proposed approach indicate that considering the country's foreseeable future conditions, higher-priority strategies minimize environmental risks and their impact on the business.
The literature suggests that classical strategic planning approaches (QSPM) or multi-criteria decision-making approaches (MCDM) are used in most cases of such decision-making. Despite their capabilities and features, these approaches face challenges in dealing with variable and evolving conditions (future uncertainty). An alternative approach, robustness analysis, can consider alternative futures but cannot define available strategies. Based on this, combining the matrix approach to robustness analysis with classical strategic planning approaches will be a response to the above problem.
Decision based on Neural Networks/ Deep Learning
Mohamad Ali Khatami Firoz Abadi; Mona Jahangir Zade; Amir Mazyaki; Seyed Soheil Fazeli
Abstract
Purpose: Nowadays insurance companies, same as other companies, are facing massive competition. This issue indicates the value of customer loyalty also a predictive model. Customers play a crucial role in the sustainability of organizations by constant repurchasing. Companies with loyal customers have ...
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Purpose: Nowadays insurance companies, same as other companies, are facing massive competition. This issue indicates the value of customer loyalty also a predictive model. Customers play a crucial role in the sustainability of organizations by constant repurchasing. Companies with loyal customers have more market share, and more money may return on investment. This article's main aim is to identify the factors affecting customer loyalty in insurance companies.Methodology: This research was quantitative, analytical-descriptive. In gathering information, Data was collected through the survey, and the findings are practical. In this way, two methods, Confirmatory Factor Analysis (CFA) and Artificial Neural Networks (ANN) were used. For localizing the factors extracted from other similar prior literature, first, the elements were examined by CFA with SMART PLS application due to some conflicts in the literature to evaluate whether each factor affects customer loyalty or not. Then, the elements were introduced to the ANN for training by this program.Findings: In this article, by using the MORGAN table, the sample size detected 384 people in 0.05 error. Questionnaires were distributed randomly between four Iranian insurance companies, ASIA insurance company, ALBORZ insurance company, and PARSIAN insurance company. Based on Confirmatory Factor Analysis, elements of commitment, perceived quality, trust, perceived value, empathy, brand image, the attraction of other alternatives, and customer satisfaction impact the customer loyalty of insurers in these companies. The cost of change, nevertheless, did not have a significant effect on customer loyalty. Then, the factors used as inputs for the multi-layer perceptron training also customer loyalty are indicated as output. The model was designed with eight inputs, 110 nodes in the hidden layer, and one output the error was E= 0.00992 and the regression = 0.98684.Originality/Value: the finding of this research is, expanding a model for predicting customer loyalty in Iranian insurance companies.