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Customer experience management (CXM), which aims to achieve and maintain customers' long-term loyalty, has attracted the attention of many organizations. Improving customer experience management in organizations requires that, first, their relevant capabilities be evaluated. The present study aimed to offer a set of key performance indicators for evaluating customer experience management in commercial banks.

The study, first, attempted to identify the components of evaluating customer experience management by reviewing the related literature and conducting interviews with experts. Then, the extracted components were transformed into assessable metrics using the goal question metric method, and the key performance indicators relevant to customer experience management in commercial banks were selected according to the experts' opinions and the Fuzzy Delphi method.

According to the findings of the study, 21 key performance indicators were identified for customer experience management in commercial banks, and customer satisfaction, the mean number of calls to resolve an issue in customer journey touchpoints, the NPS, and the ratio of the budget allocated to the CXM department to the budget of the marketing department were found as the most significant performance indicator according to banking experts.

The present study was among the first research projects intended to evaluate CXM and offer key performance indicators that could help the managers of commercial banks assess the maturity levels of their CXM.

Although Iran is one of the largest producers and exporters of saffron in the world, the organic saffron market in Iran is still in its early stages, and there is scarce empirical evidence in this regard. Therefore, the study's primary purpose is to segment the organic saffron market in Mashhad, Iran using neobehavioristic theory and machine learning methods.

Considering the neobehavioristic theory of consumer behavior, the organic saffron market was segmented using crisp and fuzzy clustering algorithms. Also, to assess the relative importance of the factors affecting the intention to buy organic saffron in each market segment, a sensitivity analysis was performed on the output of the artificial neural network (ANN). A total of 400 questionnaires were collected in Mashhad, Iran in January and February 2020.

In contrast to the belief that psychological factors are more important in market segmentation than demographic characteristics, findings showed that the demographic characteristics of consumers, especially education and income, are the dominant variables in the segmentation of the organic food market. Among the 4 A’s marketing mix elements, the results showed that a low level of awareness and accessibility are obstacles to organic saffron market development. Advertising, distribution channel improvement, package downsizing and online business development are suggested strategies for expanding the organic saffron market in Iran.

The results of the present study will help policymakers and suppliers of organic saffron to identify their target markets and design short- and long-term marketing strategies to develop the organic saffron market.

Machine learning methods and the neobehavioristic theory of consumer behavior were used to segment the organic food market.

Benzene contamination has been reported in some food groups. This study aims to identify high-risk foods groups to assess exposure to benzene.

Benzene is a hazardous volatile organic compound commonly used in the production of chemicals, detergents, paints and plastics. In addition, benzene is present in food and beverages.

Citrus juice-based beverages are usually more contaminated with benzene than other beverages. Benzene was also detected in carbonated beverages, fruit juices, pickles, lime juices, mayonnaise and salad dressing. Smoked and canned products have higher content of benzene. Aromas that are used in food contained benzene. Food packaging is one of the sources of benzene contamination of food. One of the reasons for its formation in food staff is due to the reaction of vitamin C (or similar acid) with benzoate, which is mainly used as a preservative in various foods.

Foods contaminated with benzene were determined. Moreover, mechanisms of its formation and some preventive measures were discussed.

This review determined the amount of benzene in foods, mechanism of formation and suggestion for prevention of benzene contamination in food.