{'fraction_non_alphanumeric': 0.01792573623559539, 'fraction_numerical': 0.0, 'mean_word_length': 5.766233766233766, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Customer centred community application design: Introduction of the means‐end chain framework for product design of community applications

Abstract This paper discusses the application of the means‐end chain (MEC) framework for investigating customers cognitive”; structure regarding community applications. It is argued that the understanding of customers cognition is crucial for the development of sustainable communities. MEC analysis is seen as a mean to support the community design tasks, especially concept development. The MEC analysis within concept development helps to improve the success rate of a newly designed community by the early integration of customer needs and benefits. Based on theoretical considerations about the MEC framework and its limitations a case study regarding an information community is illustrated. Data was collected conducting individual laddering interviews online at a major information portal in Germany. Dividing answers into attributes, consequences, and values and using content analysis hierarchical value maps (HVM) for both, messaging applications and information ‐portals, were constructed. To support concept development of a new information community, as a distribution platform for content, the findings of both HVMs were considered. Examples illustrate, that the MEC analysis helps to create a community concept that is focused on the targeted customers. It is supporting the creative process of finding community functions and features that are fitting or can be linked to the existing cognitive structures.