Search Results (132)

The continuous expansion of digital tourism has increased the need to understand tourists’ intentions to book hotels online in competitive digital marketplaces. Previous studies have generally relied on symmetric analytical approaches, which have limited the understanding of the complex causal mechanisms underlying online hotel booking intention, especially in emerging tourism markets such as Thailand. This study aimed to investigate the determinants of online hotel booking intention (OBI) among Thai tourists by integrating partial least squares structural equation modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The study collected data from 1884 Thai tourists who had prior experience with online hotel booking. Furthermore, PLS-SEM was used to examine the linear relationships among the study constructs, whereas fsQCA was employed to identify multiple causal configurations leading to OBI. The findings indicate that electronic word of mouth (E-WOM) was the strongest direct driver of OBI, while customer experience (CEX) significantly enhanced perceived value (PCV). Trust (TRU) emerged as a key relational mechanism that strengthened perceived usefulness (PU) and facilitated the development of E-WOM, while electronic promotion (EPM) indirectly influenced OBI. In addition, fsQCA identified multiple sufficient configurational pathways leading to high OBI, supporting the principle of equifinality. Collectively, these findings advance the theoretical understanding of OBI by demonstrating that the integration of symmetric and asymmetric analytical approaches provides complementary insights into tourists’ decision-making processes. Full article

Large online marketplaces increasingly rely on multi-stage ranking pipelines where a learned relevance model is complemented by business-aware constraints such as contractual pacing, exposure caps and commercial alignment objectives. This paper develops a second-stage, contract-aware re-ranking layer for real-estate recommendation that explicitly balances user–item relevance with plan fulfillment, lead value and operational guardrails. The proposed multi-objective re-ranker (PMOR) combines a calibrated base relevance score with multiplicative business adjustments and subtractive penalties for approaching contractual caps and for within-slate similarity. The method supports heterogeneous settlement models, including pay-per-action and fixed-fee contracts, via contract-specific weights. Because the scoring function is deterministic and structured, it admits exact component-wise contribution analysis and counterfactual ablations without relying on surrogate explainability methods. Offline evaluation on production logs from an anonymized marketplace covers 4219 recommendation requests and 184,147 candidate items, joined with daily business snapshots using an as-of strategy to prevent look-ahead bias. Under a profit proxy based on effective lead value, position discounting and billability, PMOR achieves an indexed expected-revenue proxy of 487.4 (baseline = 100), corresponding to a lift of 387.4% over a model-only baseline and 48.4% over a legacy production re-ranker (LPR). The gain is primarily associated with improved billable exposure, increasing the share of billable positions in TOP-3 to 78.22% compared with 37.85% for LPR. We discuss parameter sensitivity, operational considerations and limitations of offline proxy objectives for deployment. Full article

This study examines how the 4Es framework—Experience, Exchange, Everyplace, and Evangelism—influences online cosmetics purchase behavior in Thailand, addressing the growing importance of digital consumer engagement in emerging markets. A mixed-methods approach was employed, combining quantitative data from a structured survey with qualitative insights from semi-structured interviews. Binary logistic regression analysis was used to assess the effects and predictive power of the 4Es and selected demographic and behavioral variables. The results indicate that all four dimensions significantly influence purchase behavior, with Evangelism emerging as the strongest predictor, followed by Experience, Everyplace, and Exchange. The model demonstrates strong predictive capability, highlighting the importance of behavioral factors such as platform usage, purchase frequency, and social media engagement, while several demographic variables show limited influence. Qualitative findings further support these results, revealing that consumers place strong emphasis on social influence, emotional engagement, and convenience in their online shopping experiences. The study concludes that online cosmetics purchase behavior is shaped by a combination of experiential, relational, and socially driven factors, with social influence playing a dominant role. These findings demonstrate that the 4Es framework remains highly relevant in digitally mediated consumer environments, where purchase decisions are increasingly influenced by interactive experiences, omnichannel accessibility, value co-creation, and consumer advocacy. By integrating quantitative and qualitative evidence, the study extends the application of the 4Es framework beyond traditional marketing contexts and demonstrates its value as a comprehensive model for understanding consumer engagement and online purchasing behavior in contemporary digital marketplaces. The mixed-methods approach provides both generalizable and contextually grounded insights, offering theoretical contributions to digital marketing literature and practical guidance for marketers seeking to strengthen consumer engagement and brand advocacy in increasingly competitive online markets. Full article

Dark web drug market participants (both buyers and vendors) face frequent disruptions that affect their access to marketplaces. While these disruptions vary in their duration and the actors involved, existing research has largely concentrated on closures by law enforcement. Recognising the broader range of disruptions experienced by participants is essential for understanding how dark web markets adapt and evolve. This paper presents a typology of dark web drug market disruptions, informed by the current literature, categorising disruptions along two key dimensions: the duration of the disruption (temporary versus permanent) and the actor involved (internal versus external) in the disruption. This typology provides a comprehensive framework for analysing how different forms of disruption may influence market participant decision-making processes and the resilience of illicit online drug markets. In doing so, the typology highlights how disruptions that differ in duration and origin may have varying implications for participant behaviour and market resilience. Full article

With the increasing integration of artificial intelligence into e-commerce platforms, trust in algorithmic decision-making has become a critical issue. Recommender systems significantly shape consumer choices and influence visibility within digital marketplaces, yet remain largely opaque. This study aims to bridge the gap between algorithmic accuracy and perceived trustworthiness by conducting a bibliometric and topic modeling analysis of 163 peer-reviewed publications (2012–2025). Results indicate a paradigmatic shift from usability-focused approaches toward governance-aware frameworks encompassing fairness, explainability, and accountability. To capture this transformation, the Acceptance Triangle model is introduced, conceptualising algorithmic acceptability across three interdependent layers: trust calibration at the interface level, exposure fairness at the platform level, and accountability mechanisms at the institutional level. The model is further operationalised through the Trust UX Playbook—nine managerial design levers with associated key performance indicators—and a Composite Acceptability Score integrating accuracy, fairness, and complaint reduction. The findings suggest that trust alone may be insufficient for understanding long-term acceptability in e-commerce recommender systems. Instead, the alignment between user experience, market equity, and governance legitimacy is interpreted as an analytically useful condition for conceptualising algorithmic acceptability. This research contributes a structured framework for assessing and designing acceptable recommender systems, offering actionable guidance for designers, decision-makers, and regulatory stakeholders seeking to improve algorithmic transparency, fairness, and accountability in online commerce. Full article

In interactive digital commerce environments, negative electronic word-of-mouth (NeWOM)—particularly negative online reviews—profoundly shapes consumer perceptions and brand relationships. Yet, the underlying mechanisms through which NeWOM influences consumer conformity behavior remain underexplored from a qualitative, process-oriented perspective. This study adopts a grounded theory approach to analyze 1405 authentic negative smartphone reviews from a leading Chinese e-commerce platform. Through systematic open, axial, and selective coding, we develop a processual model that reveals how NeWOM triggers two interconnected yet distinct psychological mechanisms: the formation of generalized negative brand schema, driven by service/product failures and the internalization of psychological expectations, driven by unmet brand expectations and poor service attitudes. These mechanisms jointly shape consumer conformity behavior—the tendency to align one’s judgments and actions with perceived peer consensus reflected in negative reviews. Importantly, enterprises’ responsive improvements based on negative feedback operate as a feedback loop that can sustain or restore consumer–brand congruence. By reconceptualizing NeWOM as a dynamic, dialogic trigger within interactive marketing systems, this study extends electronic commerce theory and provides context-sensitive insight into how consumer conformity emerges and evolves in digital marketplaces. Full article

With growing interest in the effects of AI disclosure on user-generated content, empirical studies have produced mixed results. While some studies report negative consequences of disclosure, others suggest that transparent AI use does not necessarily reduce perceived authenticity or product evaluations. There is still limited knowledge about how AI disclosure in online reviews influences consumer perceptions when AI is presented as a support tool rather than a replacement for human input. To address this gap, the present study examines how AI disclosure and AI-related review cues influence consumer trust. The study compares three labeled review scenarios—reviews without AI-related information, AI-assisted labeled reviews, and AI-generated labeled reviews. The textual content of the reviews remained constant across conditions, while only AI-related labels and images were varied. This study also examines how these labeled scenarios relate to perceived authenticity and whether perceived authenticity mediates the relationship between labeled review scenarios and consumer trust. Based on survey data from 370 users of digital marketplaces in Latvia, analyzed using repeated-measures ANOVA, pairwise comparisons, and mediation analysis, this study found that: (1) reviews labeled as AI-generated showed the lowest levels of consumer trust and perceived authenticity, whereas AI-assisted labeled reviews were evaluated more favorably than AI-generated labeled reviews; (2) differences across the three scenarios were statistically significant for both consumer trust and perceived authenticity; and (3) perceived authenticity significantly mediated the relationship between labeled review scenarios and consumer trust. This study contributes to the literature by providing a more nuanced understanding of how AI disclosure and AI-related review cues shape consumer trust. It suggests that the key issue is not AI disclosure alone, but how AI-related cues shape perceived authenticity and, in turn, consumer trust. Full article

This article examines how platform-mediated crisis policy shaped inclusion and exclusion outcomes for small, medium, and micro enterprises (SMMEs) in the Western Cape during COVID-19. Integrating a market-failure perspective with entrepreneurial ecosystem theory, we present a theory-driven secondary analysis of 16 qualitative interviews and policy documents. We map five crisis-amplified failures—finance, markets, digital, institutions, and human capital—onto Isenberg’s six ecosystem domains and analyze how provincial interventions, particularly digital marketplaces, voucher schemes, and online coordination tools, functioned as governance mechanisms regulating access, visibility, and participation. The findings show that platform-mediated interventions accelerated coordination and digital market access but disproportionately benefited already connected firms, leaving institutional and inclusion gaps largely unresolved. We conceptualize sub-national crisis response as a form of platform governance and discuss implications for designing more inclusive digital policy infrastructures in middle-income contexts. Full article

Automated customer service and algorithmic governance are common in digital marketplaces, yet trust can erode when logistics, refunds, and escalation fail. Complaint-based risk and trust narratives in Turkey’s e-commerce marketplaces are analyzed for January 2019–December 2025 using 118,173 de-identified Turkish and English texts from Şikayetvar, a leading Turkish online consumer-complaint portal, and reviews of official marketplace apps on Google Play and the Apple App Store. BERTopic is implemented in Python with multilingual transformer embeddings, UMAP, HDBSCAN, and c-TF-IDF representations. The selected model identifies 35 micro-topics grouped into five macro-themes: fulfillment disruptions, remediation frictions, product-integrity risks, escalation failures, and governance threats. Monthly probability-weighted prevalence is estimated, and marketplace differences are evaluated with divergence measures, permutation tests, and multinomial regression controlling for time and language. Changepoint tests indicate a shift toward fulfillment grievances in April 2020, rising governance threats from June 2022, and increasing escalation failures linked to automated support from February 2023. These patterns suggest that barriers to human escalation convert operational incidents into platform-level trust judgments, offering monitoring signals for service recovery, marketplace governance, and AI oversight. By isolating escalation failures as a distinct complaint domain, the study links service automation to procedural justice mechanisms that translate operational breakdowns into platform-level trust and risk judgments. Full article

This study examines how different types of experienced harm influence trust in sellers and platforms in secondhand, platform-mediated markets. Drawing on attribution theory, we distinguish between fulfillment harm and integrity harm and investigate how these two forms of harm differentially affect seller trust and platform trust. Using data from the Consumer Market Evaluation Index on secondhand marketplaces, we find that both fulfillment and integrity harm are negatively associated with seller trust and platform trust compared to no-harm experiences. When both types of harm occur together, trust deterioration becomes more pronounced. Importantly, fulfillment harm is primarily associated with lower seller trust, whereas integrity harm is more strongly related to platform trust. These findings indicate that trust redistribution depends on attributional evaluations regarding causal locus and controllability. This study contributes to the existing literature by demonstrating how attribution processes allocate trust among multiple market actors and by revealing how different types of failures are attributed to these market actors. Moreover, the findings provide practical guidance for platform governance and seller behavior by highlighting the importance of targeted safeguards in sustaining trust in platform-mediated marketplaces. Full article

In the digital tourism marketplace, online reviews have become a decisive source of information for travelers who cannot directly assess the quality of hospitality services before purchase. However, it remains unclear how service-related and sustainability-related cues interact to shape guest perceptions in sustainable hotel contexts. This study investigates how intrinsic and extrinsic cues are reflected in online user reviews of sustainable hotels. Drawing on Cue Utilization Theory, a longitudinal content analysis was conducted on a worldwide online travel platform’s (OTP) reviews of hotels certified for their sustainability practices (2004–2024) by user selection. A coding framework was developed deductively based on prior studies on hotel service quality and sustainability practices, and data were analyzed using MAXQDA, Leximancer, and VADER sentiment analysis. Findings indicated that reviews primarily emphasize service quality attributes—particularly staff efficiency, food quality, and accommodation facilities—while sustainability themes appear less frequently, often in nature-related contexts. Sentiment analysis revealed a predominantly positive emotional tone shaped by service quality experiences. Overall, intrinsic cues play a central role in forming guest perceptions, highlighting the need for emotionally engaging sustainability communication strategies. Full article

This study addresses a pivotal strategic issue in hospitality e-commerce: how hotels can optimize cooperation with heterogeneous online travel agencies (OTAs). Moving beyond the conventional question of whether to cooperate, we investigate the interrelated decisions of which OTA type to partner with (quality-focused vs. price-focused) and which business model to adopt (merchant vs. agency). We develop a game-theoretic model that incorporates key e-commerce factors, including hotel capacity constraints, cross-channel spillover effects, and differential consumer acceptance of OTA types. Our analysis yields a contingent decision framework. We demonstrate that OTA cooperation becomes beneficial only when a hotel’s room capacity exceeds its direct-channel demand. The optimal strategy evolves with capacity: hotels with moderate capacity should partner with a single OTA type—predominantly the quality-focused one—while larger hotels should engage both types to maximize market coverage. In terms of business models, smaller hotels benefit from the risk-shifting merchant model, whereas larger hotels capture higher margins through the agency model. A key finding is the general superiority of a differentiated approach: applying the agency model to quality-focused OTAs and the merchant model to price-focused OTAs. This research provides a structured analytical framework to guide hotel managers in crafting e-commerce platform strategies and offers scholars a foundation for further inquiry into platform competition and contract design in digital marketplaces. Full article

The purpose of this research was twofold. Firstly, it aimed to indicate factors hindering and accelerating the development of organic food as a niche innovation in Poland. Secondly, to depict a phase and a pathway of sustainability transition in the Polish agri-food sector. The analysis was performed taking advantage of the multi-level perspective on socio-technical transitions, which has not been used to analyze the sustainability transition in Poland so far. Data were collected through a systemic literature review. Organic food production is a slow-growing niche in Poland, and the sustainability transition from the current dual agri-food regime consisting of small family farms and intensive food production is at a take-off phase. Organic food production struggles to become a regime with short food supply chains and agroecology, and the number of barriers it faces outweighs the number of enablers for its development. A de-alignment and re-alignment transition pathway can be observed. Which niche innovation becomes dominant depends on changes in regulations and on the development of both local marketplaces and online sales channels. The major conclusion is that in order for the transition in the Polish agri-food sector to happen, it should be better governed. Specifically, we need new policy instruments and governance mechanisms, new financing schemes, alternative and hybrid organizational and ownership structures, and institutional and transformative change approaches. Full article

The purpose of this study is to examine the impact of integrity-related considerations, such as ethics, privacy, protection, security, and trust, on online consumer shopping intention within the interactive marketing environment. To achieve this, the research uses partial least squares structural equation modelling (PLS-SEM), analysing data from a sample of 260 respondents collected through an online survey. The findings reveal that protection is the most influential factor driving consumer buying intentions, followed by trust, ethics and security. Privacy, while significant, has a more moderate influence on consumer behaviour compared to other factors. The study makes a key theoretical contribution by advancing the understanding of how these constructs interact to shape consumer behaviour in the digital marketplace, particularly highlighting the importance of data protection and ethical practices. Practically, the research offers actionable recommendations for e-commerce businesses, based on building a digital integrity model, suggesting the focus on enhancing data security and ethical transparency to build consumer trust. Furthermore, the findings highlight the need for policymakers to strengthen data privacy regulations and harmonise international security standards in e-commerce. Future research should consider longitudinal studies and explore these dynamics in different regulatory environments. Full article

As Generation Z increasingly dominates the consumer market, understanding their purchasing behaviour in online marketplaces has become crucial for businesses aiming to engage this digitally native and environmentally conscious demographic. The present study aims to explore Generation Z′s purchasing behaviour in e-commerce platforms through the lens of the Technology Acceptance Model (TAM), while incorporating additional factors such as sustainability and environmental awareness. A partial least squares structural equation modelling (PLS-SEM) analysis using WarpPLS 8.0 was conducted on a sample of 636 Generation Z respondents from Romania. The results suggest that online marketplaces can enhance consumer engagement by integrating eco-friendly practices and emphasizing sustainable product offerings. This research contributes to the e-commerce literature by extending the TAM framework and by providing valuable insights for businesses targeting environmentally conscious digital consumers. Full article