Navigating algorithmic markets in Singapore: A practitioner reflection on the backstage realities of algorithmic path dependence and sustainable online retailing

Abstract

This practitioner reflection examines the often unseen ‘backstage’ realities of small retailers operating within AI-mediated e-commerce platforms such as Shopee, Lazada, TikTok Shop, and Carousell in Singapore. While research has extensively analysed how algorithms influence consumers and workers, less attention has been paid to how platforms’ sellers experience and interpret algorithmically governed marketplaces. Drawing on sustained industry engagement and relevant academic literature, I explore how early platform-driven decisions – such as discounting, paid promotion, and campaign participation – may generate algorithmic path dependence that intensifies imitation, reinforces price competition, and amplifies structural asymmetries. Focusing on Singapore's dense, high-cost, digitally advanced retail environment, I reflect on how small sellers attempt to sustain margins, protect creative labour, and cultivate what I describe as a ‘trust dividend’. By surfacing these backstage dynamics, the article contributes to discussions of small-enterprise sustainability and platform governance in tropical and Global South digital economies where platform penetration is high and competitive asymmetries are pronounced.

Context and background

Front stage efficiency and backstage complexity

E-commerce platforms have become foundational infrastructures of retail across Southeast Asia. In Singapore's highly connected environment, online retailing platforms such as Shopee, Lazada, TikTok Shop, and Carousell provide integrated logistics, embedded payment systems, promotional campaigns, and cross-border market access. For small retailers, these systems significantly lower barriers to entry and provide immediate exposure to regional demand.

From the consumer-facing front stage, platforms appear frictionless. Listings are algorithmically ranked, recommendations are personalised, and transaction processes are streamlined. To consumers, the interface conveys an impression of neutral optimisation and data-driven precision.

From the seller's perspective, however, participation entails what I describe as the backstage realities of online retailing. By ‘backstage’, I refer to dimensions of platform engagement that remain largely invisible to consumers and underrepresented in mainstream research. These include the ongoing effort required to interpret platform-provided seller dashboard metrics such as impressions and conversion rates, and to make sense of fluctuating product search rankings whose underlying logic is rarely transparent. They also encompass the economic and margin pressures experienced under recurring promotional cycles, the gradual normalisation of discount-based competition that erodes pricing autonomy over time, the vulnerability of carefully developed listing content to rapid imitation by competitors, and the persistent psychological pressure of maintaining algorithmic visibility while simultaneously sustaining a viable business.

Backstage participation is interpretive and anticipatory. Sellers attempt to infer how ranking systems respond to price changes, advertising intensity, and campaign participation. Algorithmic logics are opaque; sellers therefore rely on trial-and-error adjustments shaped by expectations of how the system might react.

In this sense, the platform functions not merely as a marketplace but as a behavioural environment that conditions seller strategy, an observation consistent with research on algorithmic coordination and control in digital work environments (Kellogg et al., 2020).

Algorithmic path dependence: Constraining flexibility

I use the term ‘algorithmic path dependence’ to describe a condition in which early platform-driven decisions become embedded within ranking and visibility systems, thereby narrowing future strategic flexibility. The concept draws on economic theories of path dependence, which suggest that early decisions, even if initially contingent or suboptimal, can become self-reinforcing over time through positive feedback, increasing returns, and cumulative adoption effects (Arthur, 1994; David, 1985). In the context of platform commerce, these feedback mechanisms manifest not through technological standards or network effects in the conventional sense, but through algorithmic visibility rewards that lock sellers into established behaviour patterns, making strategic deviation costly and risky.

In practical terms, sellers often begin by offering aggressive discounting or paid promotion to gain initial visibility in crowded product categories. For example, Lazada encourages sellers to offer a 50% discount in exchange for better visibility when listing new products. If these measures generate sales momentum, ranking systems amplify exposure. However, when sellers later attempt to restore profit margins by raising prices or cutting down on participating in platforms’ promotional campaigns, product listing visibility declines sharply.

This experiential effect is constraining. Even if platform rules do not explicitly mandate discount continuation, sellers perceive that deviations risk algorithmic penalties, such as reduced visibility. Decision-making is thus shaped by anticipated consequences rather than purely by business cost-benefit calculations.

This phenomenon aligns with broader observations about algorithmic systems that shape behaviour through performance metrics and visibility mechanisms rather than direct instruction (Kellogg et al., 2020). Algorithms do not merely measure activity; they structure incentives.

Imitation loops and competitive convergence

Algorithmic path dependence does not operate in isolation. Visibility signals also function as market cues for other sellers. Listings displaying high order volumes are interpreted as evidence of market demand. This results in more sellers sourcing and offering similar products and at lower prices to gain sales, usually with identical or very similar visual formats and listing descriptions.

This creates what I described as an imitation loop. Reinforced visibility attracts replication, which intensifies competition, which further amplifies price discounting and advertising intensity. Research on algorithm-mediated environments suggests that systems optimised for engagement can unintentionally promote convergence and social learning effects (Brady et al., 2023). Empirical studies of algorithmic ranking systems further show that popularity signals can distort perceived quality, amplifying items that already receive attention while suppressing alternatives, regardless of actual product quality (Ciampaglia et al., 2018).

From the backstage perspective, what appears externally as consumer-driven demand may reflect algorithmic reinforcement dynamics

In addition, larger-scale or lower-cost cross-border sellers can sustain thinner margins for longer periods, thereby amplifying asymmetries. Sellers’ competitive vulnerability, therefore, appears to emerge not solely from consumer preferences but from the interaction between algorithmic visibility dynamics and underlying structural asymmetries in cost positions within this context.

Singapore as a tropical digital marketplace

Singapore provides a distinctive tropical urban context for examining these dynamics. Singapore is characterised by high digital penetration and smartphone usage, dense logistics networks that enable same-day or next-day delivery, elevated consumer expectations for responsiveness and warranty support, and strong cross-border integration with regional supply chains.

In tropical urban markets, rapid response and fulfilment speed strongly influence commercial outcomes. Buyers expect rapid query response and swift fulfilment. Platforms also impose algorithmic visibility penalties for slow responses to potential buyers’ queries. Lazada expects sellers to respond within 10 min (Lazada, 2024). At the same time, local sellers (many of whom are one-man operations working multiple jobs) operate in higher labour and rental cost structures than overseas sellers. The combination of dense logistics, cross-border competition, and algorithmic ranking creates a competitive environment in which prices fall quickly, margins narrow, and drops in product listings’ visibility affect sales and profitability. Singapore's position as the most digitally penetrated market in Southeast Asia, with nearly universal internet adoption and the region's highest digital spending intensity, intensifies these dynamics for small sellers operating in a market that is simultaneously mature and highly competitive (Google, Temasek, & Bain & Company, 2023).

While similar dynamics may appear elsewhere, in Singapore they unfold under the specific pressures of a high-cost, digitally mature tropical economy. In many tropical digital economies, where small enterprises play a significant role in livelihoods, innovation, and regional development, the sustainability of platform-mediated retail is therefore not merely a firm-level concern but also a matter of broader developmental significance. Research on platform-dependent entrepreneurship highlights how algorithmic dependency and platform-imposed incentive structures can undermine the long-term viability of enterprises operating within platform ecosystems, particularly where structural power imbalances are pronounced (Cutolo and Kenney, 2021; Kenney et al., 2021). In Singapore's context of dense cross-border competition, these asymmetries are further amplified for local small-scale sellers facing overseas entrants with lower cost structures. These dynamics also resonate with broader scholarship that conceptualises digital platforms as contested relational structures marked by tensions between autonomy and domination, particularly where participants become dependent on opaque governance systems and asymmetric performance metrics (Curchod et al., 2020; Schüßler et al., 2021). The way algorithmic systems shape opportunity, competition, and viability may influence how economic participation evolves in these emerging digital futures.

More broadly, in many tropical and Global South markets, rapid mobile technology adoption has enabled developing economies to bypass earlier stages of digital infrastructure and engage directly in platform-mediated commerce (UNCTAD, 2018; UNCTAD, 2019). Consequently, small retailers in these environments may experience algorithmic visibility pressures and competitive convergence more immediately and intensely. From a backstage perspective, this compressed digital transition appears to heighten the practical consequences of algorithmic dependence for small-scale sellers.

Approach/practice description

This article adopts a pracademic stance, combining sustained practitioner engagement with scholarly interpretation. My reflections draw on over 10 years of active retail operations in Singapore across Shopee, Lazada, TikTok Shop, and Carousell.

I directly managed product sourcing, pricing strategy, advertising allocation, listing creation, fulfilment coordination, and customer communication. My business operates in highly competitive consumer product categories with many sellers and requires specific product domain knowledge, sourcing experience and competency, and significant after-sales customer support.

The backstage insights emerged through iterative cycles of experimentation and observation. These included systematically adjusting price discount levels and monitoring the resulting ranking volatility; participating in platforms’ frequent sales events such as the 11.11 campaign https://www.channelnewsasia.com/singapore/online-shopping-1111-ecommerce-shopee-lazada-ninja-van-fedex-5467451 and periodic flash campaigns while continuously assessing margin sustainability; testing new product categories intensively to evaluate their competitive dynamics; responding to customer queries and managing warranty disputes; observing and documenting patterns of content imitation; and evaluating advertising return-on-investment thresholds across different campaign structures and platform environments.

These experiences are complemented by my academic research on artificial intelligence (AI) and digitally mediated decision-making

The analysis presented here is interpretive rather than empirical. It is not based on systematic sampling or formal data collection, and it does not claim statistical generalisability. Instead, it offers a bounded reflection on patterns observed through sustained engagement with AI-mediated market infrastructures.

Observations and lessons learned

Observation 1: Algorithmic visibility may obscure margin risk

Platform dashboards prominently display trending categories and high-volume listings. These metrics appear to indicate demand. In practice, they often reflect cumulative promotional intensity rather than inherent profitability.

Sellers venturing into such categories frequently encountered rapid price competition and margin compression. When discounts were reduced, visibility often declined sharply. The backstage perspective is that algorithmic popularity and economic viability are not synonymous. This observation aligns with findings that algorithmic popularity signals may amplify attention independently of underlying quality or sustainability (Ciampaglia et al., 2018).

Sustainable participation required establishing internal guardrails – clear thresholds for acceptable margins and advertising ratios – even when platform incentives encouraged continued discounting.

Observation 2: Imitation loops undermine differentiation

Visible success invites replication. Listings with strong order volumes attracted competitors offering similar entries within short timeframes. Product descriptions and pricing converged, too.

Algorithmic amplification may therefore reward conformity over differentiation (Brady et al., 2023). Without deliberate positioning strategies, sellers risk falling into imitation traps, selling top-selling products with little margin and paying platforms to bid for keyword search visibility.

Observation 3: Creative labour is structurally vulnerable

High-quality, accurate product listing content requires domain knowledge and a considerable time investment. For instance, I spent significant time, money and effort sourcing and buying samples to test product compatibility. When I identified a compatible remote control for a popular TV model in Singapore, I typically enjoyed a brief surge in sales, only for competitors to quickly notice and replicate my listing content and undercut my pricing.

Although platforms provide reporting mechanisms, it is challenging to protect such knowledge. From the backstage perspective, creative labour becomes both essential for differentiation and challenging to prevent others from copying your creative effort.

Protective measures – watermarking, embedded branding, trademark registration, and providing only partial information in product listings (which also means spending more effort on responding to buyers’ queries) – became integral to sustaining market positioning. Creative effort, while invisible in ranking metrics, proved foundational to long-term viability.

Observation 4: Trust generates a ‘Trust Dividend’

On platforms that permit direct face-to-face communication – particularly Carousell – buyers frequently ask detailed questions about compatibility, authenticity, and warranty. I priced my products relatively higher on Carousell to reflect the additional effort required. These interactions revealed that perceived reliability influenced willingness to pay.

Research on AI in service contexts suggests that human responsiveness and accountability remain critical sources of value even in technologically mediated environments (Huang and Rust, 2018). In Singapore's dense tropical market, rapid responsiveness and position as a local seller carried weight. By emphasising transparent warranty policies, fast communication, physical interaction with buyers, and consistent, speedy fulfilment (many of my sales were completed in person within hours), I was able to cultivate what I call a trust dividend – a premium consumers are willing to pay for perceived risk reduction. Many become my repeat buyers, bypassing platforms thereafter.

Observation 5: Bounded rationality and pricing assumptions

Consumers rarely conduct exhaustive comparisons across all listings. Even when identical-looking products appear at different price points, buyers do not always select the cheapest option.

This pattern aligns with the longstanding view of bounded rationality, in which decision-making relies on heuristics rather than perfect optimisation (Simon, 1955). Trust signals, perceived credibility, and responsiveness can therefore meaningfully influence outcomes even within algorithmically ranked marketplaces.

Integrative reflection

Across these observations, a consistent pattern emerges: backstage decision-making involves negotiating the tension between algorithmic incentives and sustainable viability.

Platform systems coordinate large-scale marketplaces efficiently, yet their optimisation logic may privilege platform sales volume over long-term resilience for small enterprises.

Backstage awareness – recognising both the coordinating and constraining aspects of algorithmic systems – becomes a form of strategic literacy for small retailers operating in tropical digital economies.

Future outlook and recommendations

For small retailers

Small retailers operating within AI-mediated platforms would benefit from developing clear internal pricing and advertising spending thresholds before entering new product categories, rather than allowing platform incentive structures to drive margin erosion over time. It is advisable to resist the temptation of immediate large-scale entry into algorithmically trending categories, as high visibility often reflects cumulative promotional intensity rather than sustainable demand. Consistent investment in trust-building practices – including transparent warranty communication, rapid responsiveness, and reliable fulfilment – can cultivate the kind of trust dividend that sustains customer retention beyond the platform interface itself. Intellectual assets such as original listing content, product knowledge, and curated imagery should be protected proactively through watermarking, branding, and where relevant, trademark registration. Finally, rather than reacting constantly to algorithmic fluctuations, sellers benefit from scheduling periodic strategic reviews that allow for deliberate recalibration of pricing, product mix, and advertising ratios. Direct, in-person interactions with buyers, particularly through platforms like Carousell, also offer valuable qualitative insight into consumer needs and concerns that dashboard metrics alone cannot capture.

For platform designers

Incorporating sellers’ service-quality and originality into ranking systems, rather than relying heavily on sales velocity, may support healthier ecosystem dynamics.

For policymakers

Strengthening intellectual property enforcement, enhancing cross-border accountability, and supporting local sellers’ digital capability development may enhance resilience among small enterprises. Policymakers may also consider how platform governance frameworks can maintain a degree of competitive neutrality, particularly where cross-border scale advantages risk reinforcing structural asymmetries for local small retailers.

Conclusion

This article offers a practitioner reflection on the backstage realities of selling in AI-mediated marketplaces in Singapore. While platforms expand access and operational efficiency, they may also generate conditions that reinforce convergence, imitation, and margin pressure.

From the consumer-facing front stage, platforms appear frictionless. From the seller's backstage perspective, participation involves ongoing negotiation amid ranking volatility, price discounts, heavy advertising and promotion (A&P) spending, imitation pressures, and structural asymmetries between large- and small-scale sellers.

Sustainable online retailing – understood here as maintaining long-term economic viability and protecting creative effort – depends less on optimising endlessly for algorithmic momentum and more on disciplined judgement and trust-based differentiation.

In many tropical digital economies, where small retailers remain closely tied to livelihoods and local economic participation, the sustainability of platform-mediated retail is therefore not only a question of firm-level viability but also one of broader developmental significance. By making these backstage dynamics visible, this reflection contributes to grounded discussions of digital retail futures in tropical platform economies.