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The purpose of this study is to assess the impact of Covid-19 on sustainable fashion consumption behavior by proposing a conceptual framework combining consumer-specific factors and product-specific factors with a special emphasis on consumer value perceptions.

Theory of consumption value was integrated into the knowledge, attitude behavior model in the conceptual framework having consumer-specific and product-specific aspects. Perceived value (PERVAL) scale was used to measure value perceptions. The model was verified by a survey conducted among a random sample of 520 participants. The factors were extracted by using exploratory factor analysis and then confirmed by using confirmatory factor analysis. The hypotheses in the conceptual model were tested for different consumer groups, and the strength of the relationships was calculated by using multigroup analysis in structural equation modeling.

It was observed the environmental concern raised the need for getting knowledge about the environment. The impact of environmental knowledge on the value perception of sustainable fashion products varied for the consumers affected by Covid-19 at different levels. Quality perception and price perception were influenced most by environmental knowledge in that order for the consumers with “high fear and uncertainty” and “low fear and uncertainty”. Similarly, the perceived emotional and social values were influential on purchase intention for consumers with high fear and uncertainty, whereas price and social value perceptions were influential for the consumers with low fear and uncertainty.

This study is the initial study that investigated the impact of the Covid-19 pandemic on the consumption of sustainable fashion products. The integration of theory of consumption value into the knowledge, attitude behavior model allowed identifying the relationship between environmental issues and sustainable fashion consumption. Using the PERVAL scale for measuring perceived value, the study provided valuable insights for understanding the most important value dimensions for sustainable fashion products for consumer groups affected by Covid-19 at different levels. The results regarding the changes in the rankings related to the impact of environmental knowledge on dimensions of perceived value and the impact of perceived values on purchase intention enabled the integrated model to explain the attitude–behavior gap.

Customer segmentation is an important research area that helps organizations to improve their services according to customer needs. With the increased information that shows customer attitudes, it is much easier and also more necessary than before to analyze customer responses on different campaigns. Recency, frequency, and monetary (RFM) analysis allows us to segment customers according to their common features. In this chapter, customer segmentation and RFM analysis are explained first, then a real case application of RFM analysis on customer segmentation for a Fuel company is presented. At the end of the application part, possible strategies for the company are generated.

The purpose of this paper is to propose a new integrated method for evaluating inventory of slow-moving items by introducing the application of fuzzy AHP method with interval Type-2 fuzzy sets (IT2FSs) and ABC analysis.

In the study, fuzzy analytic hierarchy process (AHP) method with IT2FSs is employed to set the importance of criteria. The weights obtained from IT2 fuzzy AHP are used to classify slow-moving items in ABC analysis. In the application part, a real-life case study is presented.

The result of this study indicates that an integrated approach utilizing IT2 fuzzy AHP and ABC analysis can be used as a supportive tool for classification of slow-moving items. The problem is solved under fuzzy environment to handle uncertainties and lack of information about slow-moving items.

Actual data are provided from an automotive company for prioritizing a various criteria to evaluate and classify stocks and a hypothetical model integrated with IT2 fuzzy AHP and ABC analysis is demonstrated.

Apart from inventory classification literature, the study integrates fuzzy AHP method by employing interval IT2FSs and ABC analysis to solve the real-life inventory classification problem.