Crashes and Glitches Drive Everything: Scientists Map the Hidden Chain of App Frustrations

Every online shopper knows the feeling: a checkout page that refuses to load, a shopping cart that vanishes mid-purchase, a refund that never seems to arrive. For fashion e-retail platforms, where impulse buying and visual appeal drive billions in revenue, these moments of friction can be fatal to customer loyalty. Yet most research into user experience has treated such problems as isolated annoyances, examining each one separately without asking how they connect. A new study published in Humanities and Social Sciences Communications takes a fundamentally different approach, mapping the entire web of user experience challenges in fashion e-retail applications and revealing that a handful of technical root causes quietly generate most of the misery shoppers experience downstream.

The research, conducted by Himanshu M. Shukla of Symbiosis Institute of Business Management, Nagpur, and Mangesh Joshi of Ramdeobaba University, applies a pair of modelling techniques borrowed from systems engineering to the messy world of mobile shopping apps. The first, Interpretive Structural Modelling, or ISM, builds a hierarchy of problems by establishing contextual relationships among them, showing which issues sit at the base of the pyramid and which are merely symptoms. The second, MICMAC analysis, classifies each challenge according to its driving power, meaning how strongly it influences other problems, and its dependence power, meaning how much it is influenced by others. Together, the two methods transform a scattered list of complaints into a causal architecture that managers can actually act upon.

To build this architecture, the researchers employed a mixed-method design that combined three streams of evidence. They began with an extensive review of the existing literature on user experience in digital retail, then analysed real user feedback to capture the complaints that shoppers themselves raise most often. Finally, they consulted experts drawn from three professional worlds: app development, user experience design, and fashion retail. These consultations allowed the team to validate which challenges matter most in practice and to establish the contextual relationships needed for the structural model. The study received ethical approval from the Academic Integrity Committee of SIBM Nagpur, and informed consent was obtained from all participants, with confidentiality guaranteed throughout the process.

The central finding is striking in its simplicity. The challenges with the highest driving power are not the glamorous design questions or the marketing concerns that dominate industry conversation, but foundational technical factors: device compatibility problems, poor layout and design, buffering delays, and app crashing. These four issues sit at the bottom of the hierarchy, exerting strong influence on nearly everything above them. In the language of systems modelling, they are the root causes of the user experience ecosystem. A shopper who abandons a cart because of a refund dispute may appear, on the surface, to have a customer service problem, but the model suggests that the true origin may lie in a poorly optimised app that crashed during checkout in the first place.

Above this technical foundation, the researchers identified an intermediate layer of challenges that both depend on the root causes and drive further problems. This layer includes login failures, unresponsive customer support, and security concerns. These issues occupy a middle position in the model, possessing meaningful driving power of their own while remaining heavily shaped by the technical base beneath them. A login failure, for instance, may stem from device incompatibility or a crashed session, but once it occurs it can trigger a cascade of its own, locking a customer out of an order, forcing them to contact support, and exposing them to doubts about whether their payment information is safe.

At the top of the hierarchy sit the most dependent challenges: refund and return issues, incorrect amount display, and failures in real-time updates. These are the problems shoppers notice most acutely and complain about most loudly, yet the analysis shows they have little independent driving power. They are outcomes, not origins. An incorrect price displayed at checkout is rarely a standalone bug in isolation; it is the visible end of a chain that may have started with buffering, a crash, or a compatibility failure on a particular device. This insight inverts the usual managerial instinct, which is to fix the problem the customer complains about rather than the one that caused it.

The practical implication of this layered structure is what the authors describe as cascading improvement. Because the high-driving-power challenges influence so many others, addressing them first can generate improvements across multiple dimensions of the user experience simultaneously. Fixing device compatibility and eliminating crashes does not merely make the app feel smoother; it reduces the pressure that feeds login failures, weakens the triggers for security concerns, and ultimately shrinks the volume of refund disputes and pricing errors that reach the customer. For fashion e-retailers operating on thin margins and fierce competition, this suggests that engineering investment in the technical core may deliver returns that customer service patches alone never can.

The methodology itself represents a novel contribution. While ISM and MICMAC have been applied in fields ranging from supply chain management to manufacturing, their use to model user experience challenges in fashion e-retail applications is new. The approach answers a criticism long aimed at user experience research: that by studying challenges in isolation, it limits understanding of how different issues interact and influence overall app performance. By structuring the challenges hierarchically, the study provides what the authors call a systematic understanding of UX challenge interdependencies, replacing a flat checklist of problems with a map of cause and effect.

The timing of this work is significant. Fashion e-retail has grown rapidly, intensifying the need to deliver seamless user experiences that enhance customer satisfaction, engagement, and retention. As shopping migrates from desktop browsers to mobile apps, the technical foundations of the experience become more fragile and more varied, since apps must perform across a bewildering range of devices, operating systems, and network conditions. A model that identifies which of these technical variables matter most, and in what order they should be addressed, offers a rare piece of quantitative guidance in a field often guided by intuition and anecdote.

For retailers, app developers, and customer service managers, the message of the study is ultimately one of prioritisation. Rather than spreading resources thinly across every complaint in the support queue, the framework suggests concentrating effort on the small set of foundational technical factors with the highest driving power. Doing so, the authors argue, can enhance customer satisfaction, trust, and long-term engagement with fashion e-retail platforms. In an industry where a single frustrating session can send a shopper permanently to a competitor, knowing which glitch to fix first may prove to be one of the most commercially valuable insights a data-driven retailer can possess.

Subject of Research: Modelling interdependencies of user experience challenges in fashion e-retail applications using ISM and MICMAC analysis

Article Title: An integrated systemic approach to modelling user experience challenges in fashion e-retail apps

Article References: An integrated systemic approach to modelling user experience challenges in fashion e-retail apps. (n.d.). https://doi.org/10.1038/s41599-026-09126-3

Image Credits: AI Generated

DOI: 10.1038/s41599-026-09126-3

Keywords: user experience, fashion e-retail, mobile apps, Interpretive Structural Modelling, MICMAC analysis, app crashing, device compatibility, customer satisfaction, digital retail, hierarchical modelling, customer retention, app design