Recommender systems are increasingly threatened by profile injection attacks. However, most existing defenses focus on detecting fake users, which becomes unreliable as modern attacks generate highly concealed profiles and operational platforms often lack attacker labels or attack priors. To address this limitation, we propose TIGER (Target Item Identification via Graph-Enhanced Representations), a hybrid auditing-oriented framework that reframes the final defensive output from user-level fake user labels to item-level suspicious target item candidates. Importantly, TIGER does not eliminate user-side analysis; instead, it uses unsupervised suspicious user discovery as an intermediate support step for downstream auditing. Specifically, TIGER first leverages a small trusted reference set to learn stable item embeddings and aligns unknown data into a shared semantic space. It then constructs graph-enhanced user representations by integrating rating statistics, preference patterns, and item semantics, enabling the extraction of informative suspicious user candidates for target item auditing. Finally, suspicious target item candidates are flagged through a rank-shift auditing strategy that compares recommendation outcomes before and after reintroducing suspicious users. Extensive experiments on three widely used datasets under ten representative attack scenarios demonstrate the effectiveness and robustness of TIGER. Across ten attacks, TIGER achieves average DR@5/DR@10 values of 0.4430/0.6120, 0.5550/0.7500, and 0.2670/0.3400 on ML-100 K, ML-1M, and Automotive, outperforming the average results of the best baseline selected for each attack by 106.20%/28.25%, 72.36%/64.84%, and 154.29%/111.18%, respectively. These results indicate that TIGER provides a reliable auditing tool for identifying high-risk target item candidates in adversarial recommender systems.
Despite growing interest in cultivated meat, most consumer-related evidence remains based on hypothetical assessments rather than real product exposure, limiting understanding of actual sensory-driven acceptance. To address this gap, the present study investigated consumer responses to a commercially available hybrid cultivated chicken product through a controlled affective sensory evaluation with young Singaporean consumers. Participants (n = 82) evaluated overall liking and sensory liking for appearance, smell, taste, texture, and aftertaste, completed Just-About-Right (JAR) diagnostics and were segmented according to Net Promoter Score (NPS) responses. JAR penalty analysis suggested that deviations from optimal sensory intensity systematically affected overall liking, with excessive intensity perceived in taste, smell, and aftertaste generating the largest penalties. Across sensory dimensions, oral attributes exerted a stronger influence on liking than appearance, with taste emerging as the primary driver of acceptance and texture showing a secondary contribution. Multiple regression analysis confirmed taste liking as the strongest predictor of overall liking, whereas the remaining sensory aspects showed weaker or non-significant effects. NPS segmentation further revealed clear differences in recommendation behaviour across detractors, passives, and promoters, closely mirroring hedonic liking patterns and supporting consistency between sensory evaluation and recommendation-oriented behavioural responses. Overall, this study provides an initial empirical benchmark of consumer responses to a commercially available hybrid cultivated meat product under controlled conditions, highlighting the central role of taste quality and sensory balance in shaping hedonic responses and consumer satisfaction. The findings offer a reference point for future research as cultivated meat products potentially enter broader markets.
Impact investing is widely expected to direct capital to locations where social and environmental challenges are most severe. Yet such opportunities are often found in places geographically distant from major pools of investment capital. We examine how geographic distance affects the realisation of impact investment deals and how host-country conditions alter that relationship. Integrating transaction cost economics with the location logic of the eclectic paradigm, we argue that impact investment decisions reflect the joint consideration of anticipated transaction value and governance costs. Distance raises the costs of screening, contracting, monitoring, and supporting ventures, while severe sustainability challenges can increase a location's mission-specific attractiveness by signaling greater unmet need and potential scope for additionality. By contrast, trade and investment risk increases transaction hazards that make distant deals harder to execute. We test these arguments using PitchBook data on 3126 impact deals closed in 2022-2023. We analyse 3606 realised investor-venture ties against matched unrealised alternatives in a choicebased sampling design. Distance reduces the likelihood of deal realisation. Challenge severity modestly weakens the distance penalty for a subset of sampled dyads, whereas trade and investment risk strengthens it across most observations. These findings contribute to impact investing by explaining why severe unmet need does not automatically translate into realised investment relationships. They extend transaction cost reasoning in entrepreneurial finance by incorporating mission-adjusted transactional value. They refine international business location logic by distinguishing mission-specific locational attractiveness from host-country transaction hazard.
Post-productivist transition (PPT) in rural China is well-documented at the structural level, but its micro-level mechanisms remain undertheorized, especially the limited participation of indigenous villagers in amenity provision. This paper addresses that gap by arguing that habitus adaptation is the micro-level mechanism that determines both whether villagers participate in the commercial opportunities PPT creates and how fully they benefit from doing so. Drawing on eight years of ethnographic fieldwork (2016–2024) and interviews with 124 respondents in Gaoshan, a Yao village in Xishuangbanna, Yunnan, we develop a two-level analytical framework. At the first level, field legitimacy and capital profile explain who participates and who does not. At the second, differential depths of habitus adaptation across three practice domains explain variation in participation quality. Adaptation depth is governed by field-side conditions (field legitimacy and legibility) and actor-side conditions (capital profile and field exposure), which together determine the quality and sustainability of participation. The paper provides the first longitudinal, individual-level account of how habitus adaptation unfolds across a village population navigating PPT in tourism.
