Page 302

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue IV, April 2026

Consumer Preference in Multivendor E-Commerce Marketplaces:

An Exploratory Perspective

Rajitha Panthange

, Dr. Sabina Rachel Harold

Research Scholar Department of Business Management Mahatma Gandhi University, Nalgonda

Assistance professor Department of Business Management Mahatma Gandhi University, Nalgonda

DOI:

https://doi.org/10.51583/IJLTEMAS.2026.150400028

Received: 08 April 2026; Accepted: 13 April 2026; Published: 04 May 2026

ABSTRACT

E-Commerce Multivendor Marketplaces offer a variety of products to the consumer all sold on a single digital

platform; while multivendor e-commerce marketplaces enhance accessibility, variety, and convenience, they

also introduce significant complexity into the consumer decision-making process. The consumers often undergo

heightened awareness, the benefits offered, many a times become a bane to completing the purchase. Consumers

face issues such as information overload, quality validation, trust and most importantly the decision regarding

vendor selection from among the many. For the sellers unless they understand and address these issues, acquiring

and retention of customers looks grim. This paper brings to the fore an exploratory context regarding consumer

preference in vendor selection when buying on e-commerce multivendor marketplaces.

Keywords: Consumer Behaviour Process, E-Commerce, Multivendor Marketplace, Consumer Preference,

Consumer Behaviour Determinants

INTRODUCTION

Scaling Heights: The E-Commerce Sector

The internet heralded the ecommerce shopping movement, since the first online purchase in 1984 ecommerce

has grown astronomically, the present growth rate since can be pegged at 400% in the timespan of 40 years.

Figure 1 illustrates the growth of the e-commerce market; presently valued at $6.8 trillion, it is estimated to grow

to $8 trillion by the year 2027

(Oberlo, n.d.)

In comparison to some of the larger sectors such as oil and gas, and the manufacturing sector, e-commerce can

be said to be an infant sector that has been on an accelerated growth trajectory (Grand View Research, n.d.). The

global economy is undergoing a transformation. Through the use of online technologies, all businesses are being

transformed into information-based operations. The Internet has broadened the scope of businesses. E-commerce

represents a paradigm shift that affects both marketers and customers (Vyas et al., 2023).

Page 303

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue IV, April 2026

Figure. 1. E-Commerce Sales

As an industry that contributes significantly to the global GDP growth, ecommerce is a sector to reckon with.

The consumers are the driving force in this sector and their behaviour dictates all decisions; right from the

website design to the products sold on the website. Every plan made, very strategy implemented are all customer

centric. E-commerce represents a rapidly growing share of consumer spending (Dolfen et al., 2022). Therefore,

it is not surprising that all the stakeholders in the e-commerce sector are committed to understanding the

consumer behaviour process to serve them better (Vo et al., 2022).

Consumer Decision Making in Digital Environment

The consumer decision-making process consists of several stages that individuals experience when acquiring a

product or service (Giang, 2024). The steps are no different from the traditional consumer decision making

process. The stages are briefly described below:

 It starts with problem/need recognition – the consumer in this stage is faced with a problem or need that

arose, which can be solved through the purchase of a particular product or service (Mihajlovic et al.,

2025).

 The next stage is the consideration/information search – this is the stage where the consumers start their

quest on search engines, they become information resources. The initial search is regarding availability

products (what kind of products will satiate their needs), the consumers then at this stage become aware

of brands that can satisfy their need (Goodman, 2024).

 The following stage is the alternatives evaluation – this is the stage where comparative analysis takes

place, which market places offer better choice in terms of product quality, price and services et al. All

the alternatives are evaluated and usually the consumer zeroes in on a few items that have passed the

evaluation criteria (Mishra, 2018).

 The next stage is a crucial stage where they decide on the purchase – which brand to buy, when to buy,

and from whom to buy. This is the stage where many external factors play a role in validating the

consumers’ final choice. The external factors that influence the consumers’ decision are many and a few

are listed: trust on the e-merchant, e-word of mouth (e-wom), online reviews, influencer ratings etc.,

(Chevalier & Mayzlin, 2006); Loop, n.d.).

Page 304

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue IV, April 2026

 The next two stages are post purchase behaviour, the consumer having bought the product next evaluates

the purchases’ worth– is it’s a purchase that adds value then the customer is satisfied as the product meets

the customers’ expectations, dissatisfaction results when the product purchased does not meet the

customer expectations i.e., the product does not perform as expected (Graff et al., 2012; Li, 2022).

Rise of Multivendor Marketplaces

A digital platform business can be defined as a two-sided market, which is an environment with supplier and

consumer groups that engage in exchanges and transactions (Kim, 2018). A multivendor marketplace can be

thought of as a digital shopping mall, a single digital storefront that offers a plethora of products. It is can be

described as an online platform where sellers can register, list and sell their products to consumers all from a

single website. Consumers prefer shopping on multivendor websites, this preference can be attributed to the

variety that these marketplaces offer along with the convenience of shopping that they offer. Inevitably all

consumers tend to compare products in the competitive set, digital marketplaces have altogether eliminated this

tedious task of visiting several stores before confirming a purchase. The ease of buying/ convenience is deemed

an important reason for the rapid growth of multivendor digital marketplaces.

Multivendor marketplaces are categorised into types based on:

 Product Offerings – product based, services based or hybrid marketplaces

 Target Audience – B2B, B2C, C2C marketplaces

 Business Model – Horizontal marketplaces that offer a variety of products across different categories and

Vertical marketplaces that sell products connected to a niche area.

The e-commerce marketplaces offer a win-win advantage to all the stakeholders; the consumers stand to gain

benefits in terms of variety and convenience; the vendors gain access to larger customer base and less operational

overheads cost meanwhile the platform administrators have the advantage of low inventory risk and scalability.

Rather than competing with fixed assets and capabilities, such as a network of stores, the power of multi-sided

marketplaces comes from their ability to tap into a large group of end-customers and providers (Gawer &

Cusumano, 2013).

LITERATURE REVIEW

Consumer decision-making in online environments:

Consumer decision-making in online environments reflects a structured yet context-influenced cognitive

process. Consumers typically adopt a two-stage approach, initially screening a broad set of alternatives and

subsequently evaluating a smaller subset in depth before making a purchase decision (Häubl & Trifts, 2000).

Similarly, while the fundamental traits of decision-making remain consistent across offline and online contexts,

differences arise due to technological influences on consumer capabilities and their interaction with digital

platforms (Punj, 2012).

Further, factors such as social identity, electronic word-of-mouth (eWOM), trust, and perceived risk significantly

shape purchase intentions, where trust and eWOM positively influence decisions, while perceived risk has a

negative impact (Takhire & Joorshari, 2015). In addition, recent research highlights the role of digital interface

design, information availability, and personalized marketing, grounded in information processing theories and

digital environmental cues (Islam et al., 2024).

Complementing this, three key stages were identified in the digital consumer decision process: information

search (perceived benefits and search effort), alternative evaluation (overall deal evaluation and perceived risk),

and purchase stage (willingness to buy) (Teo & Yeong, 2003).

Page 305

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue IV, April 2026

Seller Cues

The cue utilization theory, distinguishes between seller reputation (high-scope cue) and product presentation

(low-scope cue). Seller reputation plays a crucial role in shaping consumers’ product quality evaluations,

especially in online environments where direct product inspection is not possible (Wang et al., 2016).

Examining the role of selling cues—specifically scarcity cues (e.g., limited edition) and popularity cues (e.g.,

best seller)—in influencing consumer purchase intentions, the alignment between seller cues and product type

plays a critical role in shaping consumer perceptions and purchase decisions, with perceived uniqueness and

perceived risk acting as key psychological mechanisms (Das et al., 2018).

E-commerce / marketplace studies

A few review articles have been examined to develop a comprehensive understanding of e-marketplaces.

Notably, early research on e-marketplaces was grounded in four key conceptual areas, including benefits,

growth, and the competitive nature of marketplaces, along with the development of e-marketplace theories. This

was followed by studies emphasizing market focus, system focus, and organizational aspects. The review also

indicates a clear shift in the literature from a predominantly theoretical emphasis to a more applied and practice-

oriented approach over time (Standing et al., 2010).

A comprehensive synthesis of electronic marketplace (EM) research. identifies eight major research themes,

including EM success, adoption, impact, design, trust, EM and SMEs, intelligent agents, and general overviews,

with success, adoption, impact, and design emerging as the most dominant areas. EM research relied heavily on

qualitative approaches, making it less scientific in nature; however, there has been a gradual shift toward more

empirical investigations. Finally, an integrative framework suggests that EM research can be understood through

three key perspectives—information systems, interorganizational/social structure, and strategic management—

which together offer a comprehensive explanation of electronic marketplace phenomena (Wang et al., 2008)

Yet another study identifies eleven key success factors for e-marketplaces. These include trust, technical aspects,

platform characteristics, platform owner, product, service operation, seller, marketing and sales, payment

channel, buyer, and environmental factors. The study highlights that e-marketplace success is multidimensional,

requiring the integration of technological, organizational, and market-oriented elements (Prihastomo et al.,

2018).

Choice overload and information asymmetry

The impact of choice overload on consumer decision paralysis shows that when consumers are presented with a

large number of options, they often experience analysis paralysis, leading to the abandonment of purchase

decisions. Key antecedents of choice overload include decision task difficulty, choice set complexity, preference

uncertainty, decision goals, and asymmetric information. Among these, decision task difficulty and asymmetric

information significantly contribute to choice overload, which in turn increases the likelihood of decision

paralysis, making it harder for consumers to make decisions in complex environments (Kamuangu, 2021).

Choice overload in the U.S. beer market indicates that, although it exists for some consumers, its negative effects

can be mitigated through seller interventions. Mechanisms such as reducing search costs via product quality

scores and prominently displayed specials (private nudges) help simplify decision-making. Overall, effective

market interactions by sellers can significantly reduce or even eliminate the adverse effects of choice overload

(Malone & Lusk, 2018).

Challenges in Multivendor Marketplaces

Multivendor marketplaces present a dual-edged ecosystem wherein consumers benefit from variety and

competitive pricing, while simultaneously facing risks related to trust and quality inconsistency, and sellers

encounter challenges such as intense competition, platform dependency, and constrained brand differentiation

(Gupta et al., 2023).

Page 306

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue IV, April 2026

Seller Challenges

The accessibility to multiple sellers, combined with the convenience of online shopping, represents one of the

most significant advantages of multivendor marketplaces. However, this very characteristic—where numerous

vendors offer similar or diverse product varieties—intensifies competition among sellers (Cui, 2025). The online

buying process is often marked by increased consumer awareness, with buyers comparing multiple vendors and

even identifying alternative products to satisfy their needs.

At the same time, sellers become highly dependent on the platform, as algorithms and policies largely determine

product visibility and reach. This dependency makes it difficult for sellers to build a distinct brand identity,

especially since marketplaces tend to promote the platform rather than individual brands. Additionally, the

requirement to pay commissions and invest in advertising further reduces profit margins. Operational challenges

such as logistics and inventory management add to the complexity of selling in such environments.

Reviews, which serve as a critical trust-building cue for consumers, also present challenges, as their authenticity

and impact can significantly influence seller performance. Unless these issues are effectively addressed, they

may hinder both seller success and the overall buying process within multivendor marketplaces.

The literarture review puts together insights from consumer decision-making theories, seller cues, e-marketplace

studies, and choice overload literature to develop a comprehensive understanding of consumer behavior in

multivendor marketplaces. It highlights that while digital platforms offer extensive choice and convenience, they

also introduce complexities such as information asymmetry, trust deficits, and decision paralysis. The review

underscores the critical role of seller cues, platform design, and information structuring in influencing consumer

preferences and reducing uncertainty.

Consumer Challenges

While multivendor marketplaces offer convenience and variety, they also present challenges that can hinder the

completion of the buying process. While online shopping offers convenience, it removes the opportunity for

tangible product evaluation, thereby shifting consumer reliance to seller cues for trust formation and variety may

increase the likelihood of finding products that meet consumer needs, excessive options can lead to information

overload and make decision-making more difficult. The absence of physical inspection in online marketplaces

makes it difficult for consumers to accurately assess product quality, thereby acting as a significant constraint in

the buying process. A commonly cited reason for product returns is the mismatch between the received product

and its online representation, as descriptions and images may sometimes be misleading. This challenge is further

intensified in multivendor environments where multiple sellers offer similar products, making quality validation

even more complex. Although return policies partially mitigate this issue, they are not always consumer-friendly

and may vary across sellers (Waqas et al., 2023).

In addition, consumers must possess adequate digital literacy to effectively navigate the marketplace. They often

experience choice overload due to the abundance of options, as well as the fear of missing out on better

alternatives. For products requiring post-purchase services, the terms and conditions are often unclear or not

readily accessible, adding to consumer uncertainty. Under such circumstances, selecting a reliable vendor

becomes a significant dilemma, complicating the overall purchase decision.

Purpose and Focus of the Paper

This paper seeks to highlight the complexity of consumer decision-making in multivendor e-commerce

marketplaces, where multiple sellers offer identical or closely comparable products. While such platforms

enhance convenience, accessibility, and choice, they simultaneously create an environment characterized by

information overload, uncertainty, and difficulty in differentiating between vendors. In this context, the

traditional product-centric basis of decision-making is significantly altered.

The paper emphasizes that, in the absence of physical product evaluation and clear differentiation, consumers

increasingly rely on a range of marketplace cues—such as seller ratings, reviews, pricing signals, product

Page 307

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue IV, April 2026

representation, and platform-mediated indicators—to make purchase decisions. It proposes that these cues act

as substitutes for direct validation and play a critical role in shaping consumer preference.

Further, the paper aims to draw attention to the dynamic interplay between consumer behavior and seller

strategies within such marketplaces. It highlights how consumers actively engage in comparison and search for

alternatives, while sellers attempt to signal credibility and build trust in a highly competitive and algorithm-

driven environment.

Overall, the paper proposes to underscore the need to identify and understand the key determinants that influence

consumer choice of vendors in multivendor settings. By bringing these factors into focus, the study contributes

to a better understanding of how purchase decisions are formed in digital marketplaces and how both sellers and

platforms can respond to reduce consumer uncertainty and improve decision outcomes.

METHODOLOGY

This study adopts a conceptual and exploratory approach to highlight an underexplored problem, examining

consumer decision-making in multivendor e-commerce marketplaces in the vendor selection context. The

primary objective of the paper is not to empirically test relationships or develop a validated model, but to

highlight and articulate the complexity of the problem faced by consumers when selecting among multiple

vendors offering similar or identical products.

Conceptual research plays an important role in theory building and problem identification, particularly in

emerging domains where empirical evidence is still evolving (Jaakkola, 2020). In this context, the present study

focuses on problem structuring and analytical insight generation rather than hypothesis testing. The study is

based on a qualitative and analytical examination of the phenomenon, drawing from observed marketplace

practices and established understanding of digital consumer behavior. Prior research has highlighted that online

environments are characterized by information asymmetry and reliance on signals such as reviews and ratings

(Akerlof, 1970; Spence, 1973), which are particularly relevant in multivendor settings.

Given the relatively limited focused literature addressing vendor selection in multivendor marketplaces, this

paper takes an exploratory stance to identify key issues, challenges, and indicative factors influencing consumer

preference. The approach involves:

 Synthesizing insights from the evolving e-commerce environment

 Examining consumer decision-making challenges in digital contexts

 Analyzing the role of marketplace cues and seller-generated signals

The study aligns with prior work that emphasizes the increasing complexity of consumer choice in digital

environments due to information overload and expanded alternatives (Schwartz, 2004).

The intent is to provide conceptual clarity and highlight areas requiring further empirical investigation, rather

than to establish definitive conclusions. Accordingly, the findings of this study should be viewed as indicative

and directional, serving as a foundation for future research in this domain.

The paper thus contributes by framing the problem space and identifying the need for systematic investigation

into the determinants of consumer vendor selection

Towards Understanding Consumer Preference in Multivendor Marketplaces

The preceding discussion highlights that while multivendor e-commerce marketplaces enhance accessibility,

variety, and convenience, they also introduce significant complexity into the consumer decision-making process.

Unlike traditional retail environments, where product evaluation is often tangible and seller differentiation is

clearer, online marketplaces present consumers with multiple vendors offering identical or highly similar

Page 308

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue IV, April 2026

products. This intensifies the challenge of vendor selection and shifts the basis of decision-making from product

attributes to the cues available within the digital environment.

In such contexts, consumers are required to navigate through an abundance of information, evaluate competing

seller signals, and often engage in continuous comparison and search for alternatives within the platform. The

absence of physical validation, coupled with variability in seller credibility, delivery performance, and post-

purchase services, further complicates the process. As a result, decision-making becomes increasingly dependent

on indirect indicators such as ratings, reviews, pricing, and platform-mediated signals.

At the same time, sellers operate in a highly competitive environment where differentiation is difficult, and

visibility is largely governed by platform algorithms and policies. This creates a situation where both consumers

and sellers rely heavily on digital cues, yet the effectiveness and interpretation of these cues remain uncertain.

Given these dynamics, a critical issue emerges: what determines consumer preference when selecting a

vendor among many offering similar products in a multivendor marketplace? Understanding these

determinants is essential, as it not only influences purchase decisions but also affects consumer trust, satisfaction,

and overall marketplace efficiency. This underscores the need for focused inquiry into the factors that shape

consumer choice in such environments, particularly in the presence of multiple alternatives and competing seller

signals.

CONCLUSION

The rapid expansion of e-commerce and the emergence of multivendor marketplaces have fundamentally

transformed the consumer buying landscape by enhancing accessibility, convenience, and choice. However, as

highlighted in this paper, these advantages are accompanied by increased complexity in consumer decision-

making, particularly in contexts where multiple sellers offer identical or closely comparable products. The

absence of physical product evaluation, coupled with information overload and variability in seller credibility,

creates significant uncertainty for consumers.

This paper has emphasized that in such environments, consumer decision-making is increasingly cue-driven

rather than product-driven, with reliance placed on indicators such as reviews, ratings, pricing signals, and

platform-mediated information. At the same time, sellers face challenges in differentiating themselves and

establishing trust within a highly competitive and algorithm-governed marketplace.

The discussion underscores that understanding the determinants of consumer preference in selecting vendors

within multivendor marketplaces remains a critical yet underexplored area of research. By highlighting the key

issues and complexities involved, this study contributes to framing the problem and drawing attention to the

need for systematic investigation into the factors influencing such decisions.

Future research can build upon this foundation by empirically examining the relative importance of various

marketplace cues, exploring the role of consumer characteristics and contextual factors, and developing models

to better understand vendor selection behavior. Such efforts would not only enhance theoretical understanding

but also offer practical insights for sellers and platforms aiming to reduce consumer uncertainty and improve

decision outcomes.

Ethical Approval

This study does not involve human participants or animals and therefore did not require formal ethical approval.

Conflict of Interest

The authors declare no conflict of interest related to this study.

Page 309

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue IV, April 2026

Data Availability

The data supporting the findings of this study are not publicly available as it is based on a review of existing

literature. However, all sources used are properly cited and can be accessed through the respective publishers.

REFERENCES

1. Oberlo. (n.d.). Global ecommerce sales growth (2022–2028) [Updated Oct 2024].

https://www.oberlo.com/statistics/global-ecommerce-sales-growth

2. Grand View Research. (n.d.). E-commerce market size and share | Industry report, 2033.

https://www.grandviewresearch.com/industry-analysis/e-commerce-market

3. Vyas, S. K., Vyas, L., Singh, S., & Joshi, M. (2023). Future of e-commerce: A robust review. Lecture

Notes in Networks and Systems, 697–710. https://doi.org/10.1007/978-981-19-7663-6_66

4. Dolfen, P., Einav, L., Klenow, P. J., Klopack, B., Levin, J. D., Levin, L., & Best, W. (2022). Assessing

the gains from e-commerce. American Economic Journal: Macroeconomics, 15(1), 342–370.

https://doi.org/10.1257/mac.20210049

5. Vo, T. H. G., Cho, J., Le, K. H., & Luong, D. B. (2022). Establishing customer behavior through e-

commerce websites in newly emerging markets. Marketing and Management of Innovations, 13(4), 85–

93. https://doi.org/10.21272/mmi.2022.4-09

6. Giang, J. (2024, October 22). The importance of consumer decision-making process for businesses.

Trustify Review.

https://trustifyreview.app/consumer-decision-making-process/

7. Mihajlovic, M., Savic, A., & Sarcevic, V. (2025). Stages in the consumer buying decision-making

process. MEST Journal, 13(2), 166–176. https://doi.org/10.12709/mest.13.13.02.14

8. Goodman, M. (2024, September 12). Consumer decision-making process: The 5 key stages. Okendo.

https://okendo.io/resources/blog/consumer-decision-making-process/

9. Mishra, O. (2018). Criteria for evaluation of alternatives in online consumer decision-making process.

ELK Asia Pacific Journal of Marketing and Retail Management, 9(4).

https://doi.org/10.31511/eapjmrm.2018v09i04005

10. Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews.

Journal of Marketing Research, 43(3), 345–354.

https://doi.org/10.1509/jmkr.43.3.345

11. Loop. (n.d.). Post-purchase evaluation in buyer’s journey.

https://www.loopreturns.com/blog/post-

purchase-evaluation-in-buyers-journey/

12. Graff, J., Sophonthummapharn, K., & Parida, V. (2012). Post-purchase cognitive dissonance: Evidence

from the mobile phone market. International Journal of Technology Marketing, 7(1), 32.

https://doi.org/10.1504/ijtmkt.2012.046433

13. Li, Z. (2022). Research on post-purchase behaviour tendency of product quality to customers in fast-

selling markets. Applied Mathematics and Nonlinear Sciences, 8(1), 2639–2652.

https://doi.org/10.2478/amns.2021.2.00244

14. Kim, J. (2018). Market entry strategy for a digital platform provider. Baltic Journal of Management,

13(3), 390–406. https://doi.org/10.1108/bjm-07-2017-0228

15. Gawer, A., & Cusumano, M. A. (2013). Industry platforms and ecosystem innovation. Journal of

Product Innovation Management, 31(3), 417–433.

https://doi.org/10.1111/jpim.12105

16. Häubl, G., & Trifts, V. (2000). Consumer decision making in online shopping environments: The

effects of interactive decision aids. Marketing Science, 19(1), 4–21.

https://doi.org/10.1287/mksc.19.1.4.15178

17. Punj, G. (2012). Consumer decision making on the web: A theoretical analysis and research guidelines.

Psychology & Marketing, 29(10), 791–803. https://doi.org/10.1002/mar.20564

18. Takhire, M., & Joorshari, M. T. (2015). Evaluation of effective factors on customer decision-making

process in the online environment. International Journal of Managing Public Sector Information and

Communication Technologies, 6(3), 1–11.

19. Islam, M. S., Ali, M., & Azizzadeh, F. (2024). Consumer decision-making processes in digital

environments—A psychological perspective. Applied Psychology Research, 3(1), 1362.

https://doi.org/10.59400/apr.v3i1.1362

Page 310

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue IV, April 2026

20. Teo, T. S. H., & Yeong, Y. D. (2003). Assessing the consumer decision process in the digital

marketplace. Omega, 31(5), 349–363. https://doi.org/10.1016/S0305-0483(03)00055-0

21. Wang, Q., Cui, X., Huang, L., & Dai, Y. (2016). Seller reputation or product presentation? An empirical

investigation from cue utilization perspective. International Journal of Information Management, 36(3),

271–283.

https://doi.org/10.1016/j.ijinfomgt.2015.12.006

22. Das, G., Mukherjee, A., & Smith, R. J. (2018). The perfect fit: The moderating role of selling cues on

hedonic and utilitarian product types. Journal of Retailing, 94(2), 203–216.

https://doi.org/10.1016/j.jretai.2017.12.002

23. Standing, S., Standing, C., & Love, P. E. D. (2010). A review of research on e-marketplaces 1997–

2008. Decision Support Systems, 49(1), 41–51. https://doi.org/10.1016/j.dss.2009.12.008

24. Wang, S., Zheng, S., Xu, L., Li, D., & Meng, H. (2008). A literature review of electronic marketplace

research: Themes, theories, and an integrative framework. Information Systems Frontiers, 10(5), 555–

571. https://doi.org/10.1007/s10796-008-9115-2

25. Prihastomo, Y., Meyliana, Hidayanto, A. N., & Prabowo, H. (2018). The key success factors in e-

marketplace implementation: A systematic literature review. In Proceedings of the International

Conference on Information Management and Technology (pp. 443–448).

https://doi.org/10.1109/ICIMTech.2018.8528189

26. Kamuangu, P. (2021). Journal of Economics, Finance and Accounting Studies.

https://doi.org/10.32996/jefas

27. Malone, T., & Lusk, J. L. (2018). Mitigating choice overload: An experiment in the U.S. beer market.

Journal of Wine Economics, 14(1), 48–70.

https://doi.org/10.1017/jwe.2018.34

28. Gupta, S., Kushwaha, P., Badhera, U., Chatterjee, P., & Gonzalez, E. D. S. (2023). Identification of

benefits, challenges, and pathways in e-commerce industries: An integrated two-phase decision-making

model. Sustainable Operations and Computers, 4, 200–218.

https://doi.org/10.1016/j.susoc.2023.08.005

29. Cui, S. (2025). Increased (platform) competition reduces (seller) competition. Journal of Industrial

Economics, 73(2), 285–315. https://doi.org/10.1111/joie.12409

30. Waqas, M., Rafiq, S., & Wu, J. (2023). Online shopping: A systematic review of customers’ perceived

benefits and challenges during COVID-19 pandemic. Global Knowledge, Memory and

Communication, 74(7–8), 2655–2679.

https://doi.org/10.1108/GKMC-04-2023-0129

31. Jaakkola, E. (2020). Designing conceptual articles: Four approaches. AMS Review, 10(1–2), 18–26.

32. Akerlof, G. A. (1970). The market for “lemons”: Quality uncertainty and the market mechanism.

Quarterly Journal of Economics, 84(3), 488–500.

33. Spence, M. (1973). Job market signaling. Quarterly Journal of Economics, 87(3), 355–374.

34. Schwartz, B. (2004). The paradox of choice: Why more is less. HarperCollins.