The Effect of Consumer Acquisition Process on Consumer

Satisfaction in Purchasing Fresh Food Online in the Context of

Uncertainty

Xinyi Chu

, Ruilong Li

and Zengwen Yan

3,*

Department of Economics, Yale University, U.S.A.

Department of Economics, The Chinese University of Hong Kong, China

School of Intelligent Finance and Business, Xi’an Jiaotong Liverpool University, China

Keywords: Consumer Satisfaction, Online Fresh Food Shopping, Consumer Behavior, Uncertainty, e-WOM.

Abstract: This study aims to identify the key factors influencing Chinese consumers' satisfaction when purchasing fresh

food online in the context of uncertainty. It explores how these factors impact consumer satisfaction,

electronic word-of-mouth (e-WOM), and behavioral intentions, providing insights into the unique challenges

of the online fresh food market. A conceptual framework was developed based on prior literature, identifying

seven key determinants of consumer satisfaction: information quality, website design, merchandise attributes,

security, payment, delivery, and customer service. The study employs a quantitative research approach, using

path analysis through linear regression to test hypotheses. Data were collected from 266 respondents with

prior experience in online fresh food shopping, and reliability and validity were confirmed through

Cronbach’s alpha and confirmatory factor analysis. The results confirm that all seven determinants positively

influence consumer satisfaction in the online fresh food market. Additionally, consumer satisfaction is found

to have a significant positive impact on both behavioral intentions and e-WOM. These findings highlight the

importance of addressing perishability, quality sensitivity, and uncertainty in shaping consumer satisfaction.

This research contributes to the theoretical understanding of consumer satisfaction in e-commerce by

extending existing models to the context of uncertainty. It provides a comprehensive hierarchical model that

evaluates the consumer acquisition process from pre-purchase to post-purchase stages. The findings offer

actionable insights for online retailers to enhance their strategies and meet consumer needs in a highly

competitive and volatile market.

1 INTRODUCTION

The rapid growth of online shopping has transformed

consumer behavior and the retail landscape in China,

and the China Online Shopping Market was estimated

at USD 1400 billion in 2022 and is anticipated to

reach around USD 2300 billion by 2030, growing at

a CAGR of roughly 9% between 2023 and 2030 in

Table 1 (CMI, 2024). Compared to traditional brick-

and-mortar stores, online shopping offers

unparalleled convenience, enabling consumers to

compare and evaluate goods and their alternatives

with ease (Shankar et al. 2003). Additionally, online

platforms provide a broader variety of products than

local markets, with many offering direct-to-home

Corresponding author

delivery services (Chu et al. 2010). Among the

various categories of online shopping, fresh food and

groceries have emerged as a critical segment, driven

by increasing consumer demand and the unique

characteristics of perishable goods. The online fresh

food market has experienced exponential growth and

continues to witness both success and struggle. It

estimates that the scale of the fresh food e-commerce

transactions in 2023 will reach RMB 642.76 billion,

a year-on-year increase of 14.74% (CIW, 2023).

However, the perishable nature of fresh food, coupled

with its short shelf life, makes it a unique and

challenging category for e-commerce. For Chinese

consumers, food safety remains a top priority,

particularly during periods of uncertainty (Wang et

al., 2019; Gao et al., 2020). This underscores the

Chu, X., Li, R. and Yan, Z.

The Effect of Consumer Acquisition Process on Consumer Satisfaction in Purchasing Fresh Food Online in the Context of Uncertainty.

DOI: 10.5220/0013422900003956

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 7th International Conference on Finance, Economics, Management and IT Business (FEMIB 2025), pages 68-77

ISBN: 978-989-758-748-1; ISSN: 2184-5891

importance of understanding the factors that

influence consumer satisfaction in the online fresh

food market, especially in the face of unpredictable

and volatile conditions.

Figure 1: China Online Shopping Market 2022-2030

(dollars by billion) (CMI, 2024).

Periods of uncertainty, such as economic

instability, supply chain disruptions, and shifting

consumer preferences, have introduced new

complexities to the online shopping landscape.

Especially, external shocks can act as catalysts for

behavioral changes, pushing consumers to adopt

online shopping due to health concerns and

restrictions on physical movement. Such shifts

highlight the critical role of e-commerce in

addressing consumer concerns and meeting their

needs during uncertain periods (Gao et al., 2020).

Existing studies have identified key factors

influencing consumer satisfaction, such as

information quality, delivery, and website design

(Rita et al. 2019; Komara and Fathurahman, 2024).

However, these studies primarily focus on stable

market conditions and do not account for the unique

challenges posed by uncertainty. The COVID-19

pandemic and other periods of uncertainty have

amplified the importance of fresh food e-commerce.

With the growing importance of online fresh food

shopping, the rise of uncertainty necessitates a deeper

understanding of how the consumer acquisition

process influences satisfaction in the online fresh

food market. Factors such as economic instability,

logistical challenges, and cultural differences during

uncertain times may deviate from previous research

findings and require updated models and frameworks.

Moreover, while prior research has explored

consumer satisfaction at specific stages of the

purchasing process, limited studies have examined

satisfaction across the entire consumer acquisition

process, from pre-purchase to post-purchase stages,

and its subsequent impact on future consumer

behavior, such as electronic word-of-mouth (e-

WOM) and repurchase intentions (Cheung et al.,

2021).

To conclude, fresh products represent a unique

and critical segment of e-commerce due to their

perishability, short shelf life, and heightened quality

sensitivity (Kim & Krishnan, 2015; Lee et al., 2020).

Unlike durable goods, fresh food requires robust

quality control, timely delivery, and effective

communication to meet consumer expectations.

These factors make fresh products a critical yet

underexplored area in consumer satisfaction research.

These challenges are further exacerbated during

periods of uncertainty, such as the COVID-19

pandemic, when consumers increasingly rely on

online platforms for essential goods (Zhou et al.,

2018). Understanding the determinants of satisfaction

in this context is crucial for addressing consumer

concerns and fostering loyalty, particularly in a

competitive and volatile market.

2 HYPOTHESIS DEVELOPMENT

2.1 Consumer Satisfaction in Online

Shopping: A Hierarchical Model

Consumer satisfaction is a multidimensional

construct influenced by both outcomes and

comparisons. It is achieved when the performance of

a product or service exceeds consumer expectations

(Lu et al., 2020). While extensive research has

explored the determinants of consumer satisfaction in

traditional retail and online shopping contexts, the

online fresh food market remains underexplored.

Existing studies have identified key factors

influencing satisfaction, such as service quality,

shipping, information quality/transparency, and

website design (Zhou et al., 2018; Savastano et al.,

2024; Komara and Fathurahman, 2024). However,

there is no consensus on how these factors interact or

their relative importance in driving satisfaction

(Schaupp and Bélanger, 2005). Furthermore, most

studies focus on specific stages of the purchasing

process, such as pre-purchase or purchase, neglecting

the holistic consumer acquisition process and its

impact on future behaviors (Kumar and Anjaly, 2017)

like electronic word-of-mouth (e-WOM) and

repurchase intentions (Cheung et al., 2021),

especially the updates to reflect the challenges and

dynamics of uncertain environments (Yang et al.,

2024).

Recent research highlights the importance of post-

purchase experiences in shaping consumer

satisfaction, particularly in online retail. For example,

Kumar and Anjaly (2017) developed a validated scale

for Online Post-Purchase Customer Experience,

The Effect of Consumer Acquisition Process on Consumer Satisfaction in Purchasing Fresh Food Online in the Context of Uncertainty

emphasizing dimensions such as returns/exchanges,

delivery reliability, customer support, and the "feel-

good" factor. These dimensions collectively influence

consumer satisfaction and loyalty, underscoring the

need to evaluate satisfaction across the entire

consumer acquisition process. In the context of online

fresh food shopping, product-level uncertainty is a

significant determinant of satisfaction. Unlike

traditional retail, where consumers can physically

inspect products, online shoppers face challenges in

assessing product quality, especially for perishable

goods. Higher levels of product intangibility

exacerbate this uncertainty, making it difficult for

consumers to align product features with their needs

(Kim and Krishnan, 2015). Vendors can mitigate this

uncertainty through strategies such as detailed

product descriptions, customer reviews, and flexible

return policies, which enhance trust and satisfaction.

This study categorizes the consumer acquisition

process into three stages: pre-purchase, purchase, and

post-purchase. The pre-purchase stage involves

information quality, website design, and merchandise

attributes, while the purchase stage focuses on

security and payment. The post-purchase stage

emphasizes delivery reliability and customer service.

Consumer behavioral intentions, such as repurchase

willingness and frequency, are influenced by

satisfaction across these stages (Cheung et al., 2021).

Building on prior research, this study proposes a

hierarchical model to examine the impact of the

consumer acquisition process on satisfaction and

future behavioral intentions (Lin et al., 2009; Blut,

2016; Zhou et al., 2018; Lu et al., 2020; Cheung et al.,

2021; Savastano et al., 2024).

Figure 2: Conceptual Framework.

2.2 The Role of Information Quality,

Website Design, and Merchandise

Attributes

Information quality refers to the relevance, accuracy,

and comprehensiveness of data provided to

consumers, and indicators of information quality

include clarity, accuracy, and timeliness, which

collectively influence consumer trust and satisfaction

(Holloway and Beatty 2008; Blut 2016). In the

complex and uncertain commercial environment,

information quality has become increasingly

influential during the decision-making process (Gao

et al., 2020). High-quality information enhances

consumer knowledge and reduces uncertainty,

particularly in the online fresh food market, where

accurate and detailed product descriptions and

reviews play a critical role (Ghasemaghaei and

Hassanein, 2015; Gao et al., 2020). Therefore,

extensive and high-quality information will directly

result in higher customer satisfaction (Liu et al.

2008). As such, the following hypothesis is proposed:

H1: During periods of uncertainty, high-quality

information reduces uncertainty and enhances

consumer trust, leading to higher satisfaction levels.

Website design encompasses the visual appeal,

navigability, and functionality of an online platform

(Rita et al. 2019). A well-designed website facilitates

seamless navigation and quick access to information

satisfaction (Zhou et al., 2018). Some studies have

found a relationship between website design and

consumer satisfaction; well-designed websites will

enhance customer satisfaction towards online fresh

food purchases and their perceived service quality

(Lee et al. 2020). In addition, a well-designed

website, such as layout, responsiveness, and ease of

use, facilitates an enjoyable shopping experience,

thereby enhancing consumer satisfaction (Duarte et

al., 2018). Therefore, it’s important to increase e-

commerce platforms’ adaptability in providing

relevant information and optimizing website

interfaces to cater to consumer expectations

(Savastano et al., 2024). Thus:

H2: A well-designed website improves usability

and creates a seamless shopping experience, therefore

contributing to consumer satisfaction by making the

shopping process more enjoyable and efficient.

Merchandise attributes refer to the quality,

variety, and availability of products offered on an e-

commerce platform. In the context of fresh food e-

commerce, attributes such as freshness, packaging,

and product descriptions are particularly important

and play a significant role in shaping customer

satisfaction with their online shopping experiences.

These attributes can be evaluated through various

aspects, including product variety, price, quality, and

safety (Hwang 2013; Duarte et al. 2018). Among

these, wider assortments of products have been

shown to attract customers and result in higher

satisfaction (Rita et al. 2019). Although some

FEMIB 2025 - 7th International Conference on Finance, Economics, Management and IT Business

scholars argue that customers are becoming less

price-sensitive with the growth of the online food

market (Mutum 2014), price remains one of the most

frequently cited reasons for online shopping, as noted

by respondents in earlier studies (Chen and Chang

2003). Alongside pricing, the importance of product

quality has been growing in the context of the online

food market, particularly due to the rising preference

for healthy and organic products (Lee 2020). Product

quality has been identified as a critical determinant of

customer satisfaction, with Hwang (2013)

emphasizing its significance as a core satisfaction

construct. Moreover, product safety, an essential

component of quality, is particularly important in the

agricultural food sector, where it has been shown to

significantly influence customer satisfaction and their

likelihood of continued purchasing behavior (Gwon

et al. 2015). Drawing upon these studies, the

following hypothesis can be proposed:

H3: High-quality products that meet or exceed

consumer expectations play a vital role in shaping

consumer perceptions and satisfaction.

2.3 Security and Payment Systems as

Drivers of Satisfaction

Security is referred to as protecting the customers’

personal information collected from e-transaction and

avoiding unauthorized use of disclosure (Blut 2016).

Compared with traditional shopping, online

consumers lay more emphasis on the need for security

(Wang et al. 2016). Basically, customers’ concerns

about security can be divided into several dimensions

such as user authorization, transaction security and

personal information privacy (Blut 2016). Previous

research revealed that the perception of security risk

has a negative relationship between satisfaction with

the information service of the online platform (Guo et

al. 2012). In other words, consumers will be more

satisfied with their online shopping experience when

they feel secure with the transaction process and their

personal information. Thus, the following hypothesis

is posited:

H4: Consumers are more satisfied with their

online shopping experience when they feel confident

that their data is secure and protected from

unauthorized access.

In addition to security, convenience is another

significant advantage recognized by customers in

online shopping (Seiders et al. 2000). Among the

various aspects of convenience, payment

convenience stands out as a key feature (Duarte et al.

2018). E-payment, defined as a financial exchange

facilitated by electronic means, has become a critical

component of online shopping (Roozbahani et al.

2015). When selecting a payment method, consumers

prioritize both speed and ease of use (Beauchamp and

Ponder 2010). Research has shown that customers are

more satisfied when online platforms enhance

transaction capabilities and design convenient,

flexible payment mechanisms that save operation

time (Liu et al. 2017). Moreover, the integration of e-

payment systems into online shopping platforms not

only streamlines the payment process but also raises

customer expectations through rapid responses and

seamless transactions (Roozbahani et al. 2015).

Accordingly, the following hypothesis is proposed:

H5: Consumers are more likely to feel satisfied

when the payment process is smooth, reliable, and

free from complications.

2.4 Delivery and Customer Service:

Enhancing Consumer Trust and

Satisfaction

Delivery refers to the process of transporting

commodities from the distribution center to the

customer. It is widely recognized that delivery issues

have become one of the most common challenges

faced during online shopping (Guo et al. 2012). In

online purchases, after making the payment,

customers must wait for their goods to be shipped and

delivered. This waiting period is considered a non-

monetary cost associated with online shopping

(Beauchamp and Ponder 2010). Consequently, delays

in delivery can negatively impact customer

satisfaction (Gawor and Hoberg 2019). To ensure

superior service quality and better meet customer

expectations, companies are encouraged to enhance

delivery timeliness and optimize delivery conditions

(Rita et al. 2019). Based on this, the following

hypothesis is proposed:

H6: Efficient delivery services that meet

consumer expectations significantly enhance

satisfaction and trust in the retailer.

Customer service contains service level and

returning handling within and after the purchase (Blut

2016). In traditional purchase, there is always stuff

for helping when customers meet any difficulty. On

the contrary, there are some purchases that happen

online without any assistance (McLean and Wilson

2016). There are also some online businesses that

provide online assistance in form of web-based

synchronous media such as live chat facilities (Turel

and Connelly 2013). Poor customer service is one

root for common complaints of the online transaction

(Chen and Chang 2003). There is evidence suggests

that there can be a positive correlation between

The Effect of Consumer Acquisition Process on Consumer Satisfaction in Purchasing Fresh Food Online in the Context of Uncertainty

customer service and customer satisfaction (Blut

2016). Hence:

H7: High-quality customer service is a key

determinant of consumer satisfaction, especially in

uncertain environments.

2.5 Consumer Satisfaction and

Post-Purchase Behavior

Word-of-mouth (WOM) refers to the information

about products that one individual shares with others

and is recognized as a highly effective and powerful

form of communication (Yang et al., 2024).

Behavioral intention, on the other hand, represents a

consumer’s willingness to make another purchase

from the same company based on their prior

experience (Cheung et al., 2021). Consumer

satisfaction serves as a key precursor to behavioral

intentions, influencing outcomes such as increased

repurchase rates and the spread of positive electronic

WOM (e-WOM) (Savastano et al., 2024). Satisfied

consumers are more likely to continue purchasing

fresh food online and recommend it to others,

highlighting the strong link between satisfaction and

positive behavioral intentions. This relationship has

been supported by various empirical studies (Blut,

2016; Gao et al., 2020; Savastano et al., 2024;

Komara and Fathurahman, 2024).

The integration of big data analytics and grounded

theory has further advanced our understanding of

consumer behavior in online contexts, which is

particularly relevant in the post-COVID-19 era,

where digital transformation has significantly altered

consumer expectations and behaviors (Yang et al.,

2024). In contrast with offline shopping, the role of

electronic WOM becomes even more critical as

consumers heavily rely on the experiences of others

to make informed purchasing decisions (Yang et al.,

2024). Satisfied consumers are more likely to share

positive experiences online, promoting e-commerce

adoption among others, particularly as a safer

alternative to physical stores, which highlights the

role of satisfaction in driving e-WOM during times of

uncertainty (Gao et al., 2020). Per the above review:

H8: High satisfaction levels foster trust and

confidence, encouraging consumers to continue

engaging with the retailer.

H9: A satisfying shopping experience increases

the likelihood of positive e-WOM, enhancing the

retailer’s reputation and attracting new customers.

3 METHODOLOGY

3.1 Research Design

This study adopts a quantitative research approach to

investigate the factors influencing consumer

satisfaction in purchasing fresh food online,

particularly in the context of uncertainty. A conceptual

framework was developed based on prior literature

(Liu et al., 2008; Zhou et al., 2018; Rita et al., 2019;

Komara and Fathurahman, 2024), identifying key

determinants of consumer satisfaction. These determi-

nants include information quality (IQ), website design

(WD), merchandise attributes (MA), security (SEC),

payment (PAY), delivery (DEL), and customer

service (CSE). Furthermore, the framework explores

the relationship between consumer satisfaction (CSA),

e-WOM, and behavioral intentions (BI). To

comprehensively evaluate these relationships, a

hierarchical model was proposed, offering insights

into the consumer acquisition process.

The survey instrument used in the study was

designed to measure the constructs identified in the

conceptual framework. It consisted of two main

sections: 1. Demographic Information: This section

collected basic details about respondents, including

age, gender, education level, and frequency of online

shopping for fresh food. 2. Construct Measurement:

This section utilized five-point Likert scales (ranging

from 1 = strongly disagree to 5 = strongly agree) to

assess respondents' perceptions of the factors

influencing consumer satisfaction. Each construct was

measured using multiple items adapted from validated

scales in existing literature (e.g., Zhou et al., 2018; Fu

et al., 2020; Komara and Fathurahman, 2024).

To ensure content validity, the survey items were

reviewed by academic experts and practitioners in the

e-commerce field. A pilot test was conducted with 30

respondents to refine the questionnaire and ensure

clarity and relevance.

Table 1: Sample Demographics (n=266).

n %

Gender

Male 94 35.34

Female 172 64.66

Age

Unde

16 5 1.88

16-24 74 27.82

25-34 92 34.59

35-44 56 21.05

45-60 24 9.02

Above 60 15 5.64

Education

≤High school

45 16.92

Under

raduate 181 68.05

≥Master

40 15.04

FEMIB 2025 - 7th International Conference on Finance, Economics, Management and IT Business

3.2 Data Collection

The data for this study were collected through an

online survey targeting consumers in China who had

prior experience purchasing fresh food online. The

survey was distributed via social media platforms and

e-commerce forums to reach a diverse audience. To

ensure relevance, participants were required to have

made at least one online fresh food purchase within

the past month, and made purchases during a period

of heightened uncertainty, characterized by economic

instability and supply chain disruptions (e.g. Covid

19), ensuring the relevance of the findings to the

study’s context as well. A total of 266 valid responses

were obtained, representing a sample of major

consumers aged 16 to 44. This age range captures a

significant portion of online shoppers, despite it may

not fully represent older demographics or those in

rural areas. The data comprises two sub-samples: one

from consumers who primarily shop online and

another from those who also engage in offline

shopping. This dual-sample approach provided a

more comprehensive understanding of consumer

behavior across different shopping preferences.

3.3 Data Analysis

The collected data were analyzed using path analysis

with simple linear regression, utilizing SPSS and

AMOS software to test the proposed hypotheses.

Confirmatory Factor Analysis (CFA) was conducted

with maximum likelihood estimation to evaluate the

measurement model, while regression analysis was

applied to test the hypothesized relationships within

the structural model.

3.3.1 Reliability and Validity Testing

Reliability of the constructs was assessed using

Cronbach’s alpha, with values ranging from 0.774 to

0.897, as presented in Table 2. These values exceed

the recommended threshold of 0.70, indicating a high

level of internal consistency (Nunnally, 1978). To

evaluate validity, CFA was performed, and the model

fit indices demonstrated an acceptable fit, as shown in

Tables 3 and 4 (Bentler and Bonett, 1980; Hu and

Bentler, 1999). Furthermore, all factor loadings (λ)

were statistically significant at p < 0.001, providing

evidence of strong construct correlations (Fornell and

Larcker, 1981).

Table 2: Reliability Results.

Constructs Cronbach's alpha AVE CR

IQ 0.897 0.559 0.898

WD 0.792 0.564 0.794

MA 0.823 0.538 0.822

SEC 0.792 0.569 0.797

PAY 0.845 0.646 0.845

DEL 0.774 0.542 0.778

CSE 0.797 0.57 0.798

CSA 0.808 0.596 0.814

BI 0.788 0.651 0.789

e-WOM 0.840 0.575 0.843

Table 3: Statistics of Measurement Model

Constructs Indicator

Std.

Erro

P-value

Std. Factor

Constructs Indicator

Std.

Erro

P-

value

Std. Factor

IQ1 - - 0.744

WD1 - - 0.789

IQ2 0.079 0.000 0.792 WD2 0.064 0.000 0.713

IQ3 0.08 0.000 0.785 WD3 0.063 0.000 0.741

IQ4 0.081 0.000 0.733

MA1 - - 0.798

IQ5 0.084 0.000 0.718 MA2 0.07 0.000 0.696

IQ6 0.086 0.000 0.771 MA3 0.066 0.000 0.692

IQ7 0.081 0.000 0.682 MA4 0.063 0.000 0.741

SEC

SEC1 - - 0.706

PAY

PAY1 - - 0.812

SEC2 0.095 0.000 0.729 PAY2 0.069 0.000 0.778

SEC3 0.105 0.000 0.813 PAY3 0.071 0.000 0.819

DEL

DEL1 - - 0.803

CSE

SCE1 - - 0.797

DEL2 0.069 0.000 0.742 SCE2 0.073 0.000 0.748

DEL3 0.065 0.000 0.645 SCE3 0.07 0.000 0.715

CSA

CSA1 - - 0.827

e-WOM

EW1 - - 0.771

CSA2 0.062 0.000 0.794 EW2 0.083 0.000 0.776

CSA3 0.063 0.000 0.677 EW3 0.074 0.000 0.768

BI1 - - 0.824 EW4 0.071 0.000 0.706

BI2 0.062 0.000 0.789

The Effect of Consumer Acquisition Process on Consumer Satisfaction in Purchasing Fresh Food Online in the Context of Uncertainty

Convergent validity was confirmed as the

Average Variance Extracted (AVE) values exceeded

the recommended threshold of 0.5, with values

ranging from 0.538 to 0.651. Discriminant validity

was also established by comparing the square root of

the AVEs with the inter-construct correlations, as

presented in Table 5, in accordance with the criteria

proposed by Fornell and Larcker (1981). These

findings confirm the reliability and validity of the

measurement model, ensuring the constructs are both

internally consistent and distinct from one another.

Table 4: Fit Statistics of CFA.

χ² df p χ²/df IFI

756.897 515 <0.01 1.47 0.963

RMSEA RMR CFI NNFI SRMR

0.042 0.044 0.963 0.957 0.037

3.3.2 Hypothesis Testing

Path analysis was used to explore the relationships

between the key determinants of consumer

satisfaction and their influence on e-WOM and

behavioral intentions. The significance of each path

coefficient was assessed to evaluate the strength and

direction of the hypothesized relationships, as

outlined in Table 6 (Lleras, 2005).

The results revealed that all standardized path

coefficients were statistically significant at p < 0.01,

confirming the hypothesized relationships. These

findings provide strong support for the proposed

model, demonstrating that the identified determinants

of consumer satisfaction have meaningful and

significant impacts on both e-WOM and behavioral

intentions. In summary, all proposed hypotheses were

supported by the analysis.

4 RESULTS DISCUSSION

4.1 The Role of Information Quality in

Reducing Uncertainty

Information quality emerged as the most influential

determinant of consumer satisfaction, consistent with

previous studies (Gao et al., 2020). During periods of

uncertainty, consumers rely heavily on accurate,

reliable, and relevant information to make informed

purchasing decisions (Cheung et al., 2021; Gao et al.,

2020). The findings suggest that online retailers

should prioritize providing detailed product

descriptions, real-time inventory updates, and

transparent sourcing information to alleviate

consumer concerns.

Table 5: Pearson Correlations Matrix and Square Roots of AVEs.

IQ WD MA SEC PAY DEL CSE CSA BI EW

IQ 0.747

WD 0.843 0.751

MA 0.879 0.781 0.733

SEC 0.731 0.645 0.714 0.754

PAY 0.776 0.774 0.719 0.54 0.804

DEL 0.817 0.777 0.806 0.638 0.762 0.736

CSE 0.792 0.75 0.78 0.655 0.714 0.761 0.755

CSA 0.812 0.781 0.785 0.619 0.746 0.764 0.753 0.772

BI 0.786 0.761 0.754 0.619 0.71 0.736 0.704 0.782 0.807

EW 0.826 0.708 0.771 0.703 0.63 0.735 0.705 0.724 0.76 0.758

Table 6: Hypotheses Results.

Pro

ose

Effect Std. Coefficient t-value R² Result F

IQ→CSA + 0.809 22.623 0.66 H1 Su

orte

511.793

WD→CSA + 0.76 20.322 0.61 H2 Supporte

412.979

MA→CSA + 0.79 20.594 0.616 H3 Su

orte

424.093

SEC→CSA + 0.544 12.796 0.383 H4 Supporte

163.749

PAY→CSA + 0.72 18.184 0.556 H5 Su

orte

330.641

DEL→CSA + 0.759 19.236 0.584 H6 Supporte

370.006

CSE→CSA + 0.753 18.584 0.567 H7 Su

orte

345.367

CSA→BI + 0.841 20.407 0.612 H8 Supporte

416.46

CSA→e-WOM + 0.725 17.031 0.524 H9 Su

orte

290.065

FEMIB 2025 - 7th International Conference on Finance, Economics, Management and IT Business

4.2 Website Design and Its Impact on

Consumer Experience

Website design, including navigation capability,

aesthetic appeal, and transaction efficiency, was

found to significantly influence consumer satisfaction

(Liu et al. 2008). In uncertain environments, where

consumers may feel heightened stress or urgency, a

well-designed website can enhance the shopping

experience by reducing cognitive load and facilitating

seamless transactions. This finding highlights the

need for online retailers to invest in user-friendly

interfaces and mobile-optimized platforms to cater to

the growing demand for online grocery shopping

during uncertain times.

4.3 Merchandise Attributes and

Consumer Expectations

Merchandise attributes, such as freshness, quality,

and variety, play a critical role in shaping consumer

satisfaction (Lee et al. 2020). The perishable nature

of fresh food makes it particularly sensitive to

consumer expectations, especially during periods of

uncertainty when supply chain disruptions may

impact product availability and quality. The results

suggest that online retailers should establish robust

quality control measures and communicate these

efforts to consumers to maintain satisfaction and

loyalty.

4.4 Security and Payment Systems:

Building Consumer Trust

Security and payment systems were identified as

significant determinants of consumer satisfaction

(Rita et al. 2019). In uncertain contexts, consumers

are particularly concerned about the safety of online

transactions and the protection of their personal

information (Guo et al. 2012). The findings

emphasize the importance of implementing secure

payment gateways, offering multiple payment

options, and clearly communicating privacy policies

to build consumer trust and encourage repeat

purchases.

4.5 Delivery and Customer Service:

Meeting Consumer Expectations

Delivery and customer service were also found to

have a strong impact on consumer satisfaction.

Timely and reliable delivery is especially critical for

fresh food, as delays can compromise product quality.

During uncertain times, logistical challenges such as

transportation disruptions or labor shortages may

exacerbate delivery issues. The findings suggest that

online retailers should adopt innovative solutions,

such as real-time tracking systems and flexible

delivery options, to address these challenges.

Additionally, responsive and empathetic customer

service can help resolve issues promptly and enhance

overall satisfaction (Holloway and Beatty 2008).

4.6 Behavioral Intentions and e-WOM:

The Ripple Effect of Satisfaction

The study further demonstrates that consumer

satisfaction positively influences behavioral

intentions, such as repurchase intentions and e-WOM

(Cheung et al., 2021). Satisfied consumers are more

likely to recommend the platform to others, creating

a ripple effect that can enhance the retailer's

reputation and attract new customers. This finding

underscores the strategic importance of prioritizing

consumer satisfaction as a means of fostering long-

term loyalty and growth, particularly in competitive

and uncertain markets.

5 CONCLUSION

While prior research has laid a foundation for

understanding consumer satisfaction in online

shopping, there is a growing need to incorporate

emerging perspectives on post-purchase experiences

and product-level uncertainty. In the context of online

fresh food shopping, perishability and quality

sensitivity amplify the importance of factors,

information quality, website design, merchandise

attributes, security, payment, delivery, and customer

service, and the findings confirm that they positively

influence consumer satisfaction. These results align

with prior research (Liu et al. 2008; Rita et al. 2019)

but extend the understanding of these factors by

situating them within the unique challenges posed by

uncertainty, such as economic instability and supply

chain disruptions. The hierarchical model tested in

this study provides a comprehensive framework for

evaluating consumer satisfaction across the entire

acquisition process, from pre-purchase to post-

purchase stages. These dimensions enrich our

understanding of consumer satisfaction and provide

actionable insights for businesses seeking to enhance

their e-commerce strategies in uncertain and dynamic

environments.

The Effect of Consumer Acquisition Process on Consumer Satisfaction in Purchasing Fresh Food Online in the Context of Uncertainty

5.1 Implications for Online Retailers in

the Context of Uncertainty

The results of this study provide valuable insights for

online retailers operating in uncertain environments.

By addressing the seven key determinants of

consumer satisfaction, retailers can better meet

consumer needs and differentiate themselves in a

highly competitive market. For example:

· Information Quality: Retailers should leverage

technology, such as AI and big data analytics, to

provide personalized recommendations and

real-time updates.

· Website Design: Investing in intuitive and

visually appealing interfaces can improve user

experience and reduce cart abandonment rates.

· Delivery and Customer Service: Building

resilient supply chains and training customer

service teams to handle uncertainty can enhance

consumer trust and satisfaction.

5.2 Theoretical Contributions

This study contributes to the theoretical body of

knowledge on e-commerce by extending existing

models of consumer satisfaction to the context of

uncertainty. The hierarchical model developed in this

research integrates multiple determinants across the

entire consumer acquisition process, providing a

more holistic understanding of consumer behavior in

uncertain environments. The findings also highlight

the dynamic interplay between satisfaction,

behavioral intentions, and e-WOM, offering a

foundation for future research on consumer behavior

in volatile markets.

5.3 Limitations and Future Research

Directions

While this study provides valuable insights, it has

several limitations that should be addressed in future

research. First, the sample was limited to consumers

aged 16 to 44 with prior experience purchasing fresh

food online, which may not fully represent the views

of all online shoppers in China. Future studies should

include a more diverse sample in terms of age,

location, and education level. Second, this research

focused on the direct effects of each determinant

without exploring potential interrelationships or

moderating factors. Future research could examine

the intricate correlations between these variables and

their impact on consumer satisfaction. Finally, the

study applied the model to general fresh food

products without considering specific food

categories. Future research could investigate whether

the findings are consistent across different product

segments or industries.

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