جستجوی مقالات مرتبط با کلیدواژه "customer loyalty" در نشریات گروه "صنایع"

In a competitive environment where business competition has become a fundamental challenge for managers, 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 and must choose the most appropriate one(s). 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 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. Afterwards, 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.Originality/Value: The problem of choosing a customer loyalty strategy is a decision-making problem that can be addressed with the help of decision-making knowledge. However, the literature suggests that classical strategic planning approaches Quantitative Strategic Planning Matrix (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.

The research was conducted with the aim of analyzing innovative factors affecting customer loyalty in multi-level marketing based on business intelligence. This research in terms of purpose; It is applied and in the field of quantitative-qualitative studies which was done with survey and data-mining methods. The statistical population of the research consists of 15 senior managers and experts in the field of research, i.e. Panh-Riz cosmetics and hygiene company, were selected by snowball method to identify the components and factors, and in the second part of the data warehouse of Panh-Riz company in the period of 2013 Data mining was done until 2018, which includes 5,200,000 records. The method of data analysis is data mining and customer clustering, which was done using R software. The results of data analysis showed that 6 indicators could be considered for the model, which are: the length of customer cooperation, purchase delay, repeat purchase, high purchase amount, profitability, and discounts to customers. In general, it can be stated that the loyalty of the customers of multi-level marketing companies is in accordance with the intelligence of the business, considering five clusters of customers, it is influenced by these six indicators, and in order to improve the level of customer loyalty and achieve a competitive advantage, the company must Active in this field should be considered. Also, for the development of multi-level marketing, it is suggested that the investigated companies pay more attention to the role of discounting and credit sales to customers, and on the other hand, keep their main customers more satisfied by providing better services and more support. It should be mentioned that so far no research has been done at the country level regarding the design and development of customer loyalty management model in MLM multi-level marketing and business companies based on business intelligence (BI) and this research as a project A new study with an innovative approach to the cosmetic and health products market can be a guide for network marketing managers in achieving greater customer loyalty.

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.

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.

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.

In today's world, the ultimate goal of many businesses is to reduce costs. Also, finding efficient ways to achieve the best results is important to make correct managerial decision. In supply chain system, minimizing costs due to the nature of the deterioration of certain products is concerned and also, finding ways to obtain optimum conditions is essential. The two-level supply chain system with suppliers, distributors and retailers was investigated in this research. Decision variables of this problem due to minimizing costs, are determining of the appropriate initial weight for packaging of deteriorating products and determining of appropriate inventory levels in multi-level supply chain. The Intended product is gradual deteriorating package that is produced and sent by the supplier with a value greater than unit. Shortages for the backlog and also lost sales have been considered. This study is based on a case study of detergent company data. In this study, through simulations to study the behavior of decision variables are discussed. Customers refer to retailers to provide their needs. Customer entrance rate is defined probability Poisson. Based on the considered (S-1,S) ordering policy caries out two operations as soon as entering a retail client. The first one is to order product to distributor and the other is to provide customer needs. Neighbor search method and ARENA software sub-program is used to find optimal points. Then using flexibility of ARENA software, study of cases that are very complex through mathematical modeling and increasing the amount of system uncertainty have been possible. The effect of the implementation period and the number of occurrences that led to the introduction of the points by choosing them can be trusted to extract the results. Using the duration and number of occurrences obtained optimum levels for retailers and distributors, and the surplus was calculated by neighbor search method. At last, the minimum cost for unit product and the extra amount required for a product are calculated by taking into account certain assumptions.

In this study, the satisfaction index of new product attribute in terms of development strategy, which includes a number of options for development using Kano questionnaire, in the automotive industry was calculated, and According to the relationship between satisfaction and loyalty, instead of loyalty index, we was used satisfaction Kano index. Then using customer purchase records data within a specified period of time (three years), and the Kano attribute allocation model to various stages of the product life cycle based on interviews with experts, the value of customer life-cycle stages, is calculated. This approach In comparison with other methods for calculating the customer lifetime value is future forwarding and strategic and is an effective method to value engineering and optimal allocation of resources because this method prevent the allocation of resources on features that do not increase the value and do not create satisfaction.