Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia.
Vol.
, 2024, 463-478
J U R N A L
KOMUNIKASI
E-ISSN: 2503-0795
P-ISSN:
P-ISSN: 2548-8740
IKATAN SARJANA KOMUNIKASI INDONESIA
Comparison of Online Shopping Behavior Before and During Pandemic towards Generation Z https://doi.
org/10.
25008/jkiski.
Rino Febrianno Boer1*.
Reina Amerya Ayu2.
Fatima Alifha3 Postgraduate Programme.
LSPR Institute of Communication and Business Jl.
Mas Mansyur Kav.
Jakarta 10220 - Indonesia Faculty of Economics and Business.
Universitas Gadjah Mada Jl.
Sosio Humaniora No.
Bulaksumur.
Yogyakarta 55281 - Indonesia Department of Communication Studies.
LSPR Institute of Communication and Business Jl.
Mas Mansyur Kav.
Jakarta 10220 - Indonesia Corresponding author: rino.
fb@lspr.
Submitted: November 13, 2024.
Revised: November 30, 2024.
Accepted: Dec.
2, 2024
Accredited by Kemdikbudristek No.
152/E/KPT/2023
Abstract - The increasing adoption of digital platforms has significantly influenced consumer behavior, particularly among Generation Z, necessitating a deeper understanding of how external crises reshape purchasing patterns.
Grounded in consumer behavior theories, this study explores how key factors such as quality consciousness, green consumer value, materialism, and impulsive buying influence Generation Z's decision-making stylesAiextensive, limited, and habitualAibefore and during the COVID-19 pandemic.
The primary objective is to uncover the extent to which these factors evolved during the pandemic and their implications for communication strategies in digital marketing.
Using a Partial Least Squares - Multi-Group Analysis (PLS-MGA) framework, the study employs a quantitative approach with data collected from Generation Z respondents across two time periods: pre-pandemic .
8, n=.
and mid-pandemic .
2, n=.
The analysis evaluates the relationships between variables and compares changes over time to identify significant shifts in consumer priorities.
Results reveal that external global events amplify internal consumer values, with quality consciousness and green consumer value becoming more pronounced during the pandemic.
Additionally, materialism and impulsive buying gained significance across all decision-making styles, highlighting the psychological impact of the crisis.
These findings contribute to the field of communication by emphasizing the need for brands to adapt their messaging to reflect evolving consumer priorities, particularly in times of This research underscores the role of communication in fostering trust and aligning with sustainable and quality-driven values, offering actionable insights for marketers targeting Generation Keywords: Consumer behavior.
Online Shopping Behavior.
Generation Z.
Covid-19.
PLS-MGA
Introduction The rapid advancement of the internet has transform global communication and consumer behavior, ushering in an era of electronic commerce that has fundamentally reshaped how consumers purchase products and services (Tao, 2.
Since 2014, the number of online shoppers worldwide has increased significantly, rising from 1.
32 billion to 2.
14 billion in 2021 (Statista Search Department.
This growth was further catalysed by the COVID-19 pandemic, which accelerated the global Rino F Boer / Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia.
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, 2024, 463-478
adoption of e-commerce.
Online retail sales surged from approximately $2 trillion in 2019 to $2.
trillion in 2020, and further to $2.
9 trillion in 2021, driven by lockdowns and health concerns that restricted in-person shopping (United Nations Trade and Development, 2.
In Indonesia, the COVID-19 pandemic led to a 23% increase in e-commerce transactions in 2020, with 63 million new users adopting online shopping (The International Trade Administration, 2.
The Gross Merchandise Value (GMV) of Indonesia's e-commerce market reached an estimated $32 billion by 2021, reflecting robust and sustained growth despite logistical and infrastructural challenges (Negara & Soesilowati, 2.
These patterns indicate a sustained upward trajectory for e-commerce in Indonesia, aligning with global trends of increased online consumer activity during the pandemic.
This momentum is projected to persist, with forecasts predicting a 51.
03% increase in ecommerce users between 2024 and 2029, reaching approximately 99.
1 million users by 2029Aimarking the ninth consecutive year of growth (Statista Research Department, 2.
Notably.
Generation Z consumers are leading this shift, allocating a higher proportion of their income to online shopping compared to older generations.
On average, individuals aged 18-25 spend 5.
4% of their monthly income, or approximately 4.
6 million Rupiah, on e-commerce, highlighting their pivotal role in driving IndonesiaAos digital economy (Lidwina, 2.
In a broader context, strict government measures to limit public mobility and interpersonal interactions have transformed everyday activities.
Many of these transitioned to hybrid or fully online formats, reshaping consumer behaviour and emphasizing the importance of long-studied factors such as quality consciousness, the need for uniqueness, and green consumer value (Babin, 1984.
Park & Lessig, 1977.
Aaker, 1.
Digital platforms have empowered consumers with tools to evaluate product and service quality, personalize purchases to meet individual preferences, and adopt more sustainable and eco-conscious consumption habits (Kahle, 1995.
Mick, 1.
These shifts have been widely analysed in academic research, which highlights key behavioural As direct interpersonal interactions diminished, the demand for robust online customer support grew significantly (Bettencourt, 1.
Materialism has seen a resurgence in the digital age, with consumers placing increased value on acquisition and ownership (Tian et al.
, 2.
Social media platforms and targeted advertising have amplified impulsive buying tendencies and hedonic shopping behaviours (Kahle, 1995.
Mick, 1.
Additionally, peer reviews and influencer endorsements have become influential factors in online purchasing decisions, particularly among younger demographics such as Generation Z (Faber & OAoguinn, 1992.
Shim & Gehrt, 1.
The convenience of online shopping has also fuelled compulsive buying behaviours, driven by the intrinsic satisfaction derived from acquisitions (Park & Lessig, 1.
Building on this extensive body of research, the present study examines the behaviour shifts observed in Generation Z during the pandemic.
Specifically, it seeks to address two research questions:
RQ1.
What factors influenced Generation Z's consumer behaviour before the pandemic? RQ2.
How have these factors evolved or changed during the pandemic? By exploring these questions, this study aims to provide valuable insights into how Generation Z has adapted to the unique challenges and opportunities presented by the pandemic, contributing to a deeper understanding of the evolving consumer landscape Theoretical Framework Generation ZAos Digital Consumption Gen Z, typically identified as individuals born between the mid-1990s and the early 2010s, is distinguished by its immersion in the digital age from birth.
This generation has grown up with the internet, smartphones, and social media as integral components of their daily lives.
Their developmental years, characterized by rapid technological advancements and a globalized world, have profoundly influenced their perspectives and behavioral patterns.
Recognizing the unique attributes and potential of this demographic, companies are increasingly focusing on engaging with Gen Z, anticipating them as a pivotal market segment for the future (Nowak et al.
, 2.
A salient characteristic of Gen Z, as observed in various studies, is their discerning consumptive behavior, often driven by digital influences and a global perspective (Parker et al.
, 2.
In a recent study conducted by Populix Corporation during the pandemic in 2021, it was revealed that Gen Z Rino F Boer / Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia.
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, 2024, 463-478
significantly patronizes online shopping platforms.
Specifically, individuals aged between 18-21 years constituted 35% of the online shoppers, closely followed by the 22-28 age bracket at 33%.
Dominant online marketplaces in Indonesia, such as Shopee.
Tokopedia, and Lazada, emerged as the platforms of choice for this demographic during this period.
The determinants of online purchasing behavior for Gen Z were predominantly influenced by factors like price discounts, shipping costs, and habitual behaviors shaped by digital experiences.
In the contemporary consumer landscape, the process of product evaluation, brand recognition, and attitude formation has been significantly influenced by multidimensional communication channels.
Social media platforms play a pivotal role in shaping Gen Z's perceptions, offering brands the opportunity to engage consumers through exposure, attention, and interactive experiences (Kim & Ko.
These platforms disseminate diverse messages from various sources, including peers, celebrities, marketers, and digital influencers, all of which significantly impact Gen Z's purchasing decisions (Bearden & Etzel, 1982.
Logan et al.
, 2012.
Pelling & White, 2009.
Schulze et al.
, 2.
Type of Consumer Buying Decision In the realm of consumer behavior, the intricate art of decision-making has always been a focal point of study.
Solomon et al.
delved deeply into this subject, shedding light on the various facets of how consumers make choices.
They identified three primary pathways through which individuals navigate their purchasing decisions.
The first pathway is the process of extended problem-solving.
This method is a meticulous one, drawing parallels with the traditional cognitive decision-making Imagine a consumer standing at a crossroads, taking in every signpost, and analyzing each direction before taking a step.
They commence with recognizing the problem or the need, prompting them to seek more This information search might involve reading reviews, asking friends, or even sampling After gathering sufficient information, they methodically evaluate the alternatives available.
It's akin to weighing scales, measuring the pros and cons until they find the balance that suits them best.
This eventually culminates in the product choice and purchase.
But the journey doesn't end there.
the purchase, they reflect upon the outcomes, determining if their decision was right or if there's room for improvement in future choices.
However, not all decisions warrant such detailed introspection.
Enter the second pathway: limited problem-solving.
This is the streamlined, more direct route.
Here, individuals already possess a roadmap or perhaps they're following well-trodden paths.
The motivation to search for extensive information or rigorously weigh each option isn't as They might lean on a past experience, a recommendation from a friend, or a familiar brand This approach is about efficiency, utilizing cognitive shortcuts or heuristics.
It's like having a compass in hand, guiding the direction without needing to analyze every detail of the journey.
Lastly, there's the realm of habitual decision-making.
This is instinctual, almost second nature.
Think of it as a traveler who's taken the same route countless times, moving forward without a second thought.
Many of our day-to-day purchasing choices fall into this category.
The decisions are so ingrained and routine that one might not even be consciously aware of making them until perhaps revisiting their shopping list or cart.
It's like breathing, an act so natural and automatic.
Researchers aptly term this spontaneous and subconscious process "automaticity.
Generation ZAos Online Shopping Behavior Online shopping behavior encompasses the patterns and processes consumers exhibit when purchasing products or services over the internet.
This digital activity has surged in popularity, with various platforms and e-commerce sites facilitating such transactions.
A myriad of factors influence online shopping behavior, including quality consciousness, consumerAos needs for uniqueness, green consumer value, support for customer, materialism, brand equity, conformity motivation, impulsive buying, hedonic shopping value, vanity, consumer ethnocentrism, susceptibility to reference group influence, compulsive buying, and personal integrative benefit (D.
Aaker, 1991.
Alnawas & Aburub.
Babin, 1984.
Faber & OAoguinn, 1992.
Haws et al.
, 2010.
Kahle, 1995.
Mick, 1996.
Netemeyer et , 1995.
Park & Lessig, 1977.
Richins, 1987.
Shim & Gehrt, 1996.
Shimp & Sharma, 1987.
Tian et , 2.
Online shopping has become an integral part of modern consumerism, with more individuals opting for the convenience, variety, and flexibility that digital platforms offer.
As the e-commerce Rino F Boer / Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia.
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landscape continues to evolve, understanding the nuances of online shopping behavior has become paramount for businesses and marketers alike (Al-Gasawneh et al.
, 2.
This behavior, influenced by a myriad of factors, dictates how consumers navigate, select, and ultimately decide on their purchases in the vast digital marketplace.
Quality consciousness in the digital sphere pertains to an online shopper's tendency to emphasize and seek products that are viewed as superior in quality and reliability, underscoring the digital consumer's preference for excellence.
Moreover, the consumerAos need for uniqueness in the online realm is manifested as a quest to find products or services that stand out, allowing the consumer to maintain individuality (Aksoy et al.
Mohammadi et al.
, 2.
In addition, green consumer value in e-commerce points to the importance placed on eco-friendly and sustainable products, with digitally savvy consumers increasingly looking for brands that uphold environmental values (Riva et al.
, 2.
Support for the customer in online platforms emphasizes the necessity for continuous assistance and guidance, ensuring a seamless navigation experience (Cintamyr, 2023.
Sheth et al.
, 2.
Materialism, in the context of online shopping, denotes the value placed on acquiring digital material goods, often associated with personal success or societal status (Mick, 1.
Brand equity in e-commerce is perceived as the worth and trust associated with a brand, built through positive online experiences and reviews (D.
Aaker, 1991.
Aaker, 1991.
Aaker & McLoughlin, 2.
On the other hand, conformity motivation (Chaouali et al.
, 2016.
Cheung & Prendergast, 2.
relates to consumers adapting their online purchase behaviors based on digital trends or peer Impulsive buying in the digital space indicates spontaneous purchases made while scrolling through online platforms, driven by targeted advertisements or limited-time offers.
Hedonic shopping value online centers on the joy and experience derived from virtual shopping, where browsing and discovery become a source of pleasure (Atulkar & Kesari, 2017.
yNavuolu et al.
, 2.
Vanity drives the quest for products that enhance one's digital image, often shared on social media Consumer ethnocentrism, even in the digital age, leans towards a preference for locally produced or domestic online goods.
In the era of influencers, susceptibility to reference group (Park & Lessig, 1.
influence indicates the impact of peer reviews, influencers, and digital communities on a consumer's purchasing choices.
Compulsive buying online (Aksoy et al.
, 2.
reflects uncontrollable purchasing urges, often triggered by emotional needs.
Lastly, the personal integrative benefit in online shopping pertains to the internal rewards a shopper feels post-purchase, such as a sense of accomplishment or digital self-expression (Dani & Maulana, 2020.
Ren et al.
, 2.
Understanding these elements offers invaluable insights into the evolving landscape of digital consumer behavior and preferences.
Hypothesis and Framework Development The personal integrative benefit in online shopping pertains to the internal rewards a shopper feels post-purchase, such as a sense of accomplishment or digital self-expression (Wieland, 2.
It's worth noting that the landscape of these online shopping behaviors has potentially undergone significant shifts from the pre-pandemic to the pandemic era (Rushi & Pradhan, 2.
For instance, the emphasis on quality consciousness might have increased as consumers became more cautious about the products they purchased due to health and safety concerns (Hutagalung & Rachman, 2.
The need for uniqueness may have been amplified as online shopping became more ubiquitous, and individuals sought differentiation in an increasingly crowded digital space (Al Hamli & Sobaih.
Moreover, the pandemic could have intensified green consumer values, with a heightened global focus on sustainability and health (Hutagalung & Rachman, 2.
Support for customers became even more crucial as online shopping surged, requiring businesses to adapt swiftly to provide seamless digital experiences (Wieland, 2.
Materialism may have seen a dip initially due to economic uncertainties but rebounded as consumers sought comfort in online purchases (Rushi & Pradhan, 2.
Brand equity became paramount, with trust playing a significant role in purchase decisions amidst uncertain times (Al Hamli & Sobaih, 2.
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Figure 1.
Research Framework Conformity motivation may have been bolstered by the collective experience of the pandemic, leading to more unified consumer trends (Wieland, 2.
Meanwhile, the rise in impulsive buying could be attributed to the increased screen time and targeted advertising (Rushi & Pradhan, 2.
, while hedonic shopping value may have been a refuge for many seeking solace in the pleasures of online browsing (Al Hamli & Sobaih, 2.
Vanity, driven by the boom in virtual meetings and social media connectivity, became a pronounced factor (Wieland, 2.
Consumer ethnocentrism might have seen a surge, given the global disruptions in supply chains and a renewed focus on local products (Hutagalung & Rachman, 2.
Influencers and peer groups possibly played an even more significant role as people turned to trusted voices in a world filled with information overload (Al Hamli & Sobaih, 2.
Compulsive buying, driven perhaps by stress or the need for comfort, might have increased for some (Rushi & Pradhan, 2.
All these shifts underscore the dynamic nature of online shopping behavior, emphasizing the need for businesses to remain adaptive and vigilant (Wieland, 2.
Understanding these elements and their evolutions offers invaluable insights into the ever-changing landscape of digital consumer behavior and preferences (Al Hamli & Sobaih, 2.
Given these arguments, we put forth the subsequent hypotheses:
Extensive Problem-Solving H1a.
There is a significant difference in how Gen Z's quality consciousness influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H1b.
There is a significant difference in how Gen Z's consumerAos needs for uniqueness influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic H1c.
There is a significant difference in how Gen Z's green consumer value influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H1d.
There is a significant difference in how Gen Z's support for customer influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H1e.
There is a significant difference in how Gen Z's materialism influenced their extensive problemsolving buying decisions between the pre-pandemic and during-pandemic periods.
H1f.
There is a significant difference in how Gen Z's brand equity influenced their extensive problemsolving buying decisions between the pre-pandemic and during-pandemic periods.
H1g.
There is a significant difference in how Gen Z's conformity motivation influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H1h.
There is a significant difference in how Gen Z's impulsive buying influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
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H1i.
There is a significant difference in how Gen Z's hedonic shopping value influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic H1j.
There is a significant difference in how Gen Z's vanity influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H1k.
There is a significant difference in how Gen Z's consumer ethnocentrism influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic H1l.
There is a significant difference in how Gen Z's susceptibility to reference group influence influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H1m.
There is a significant difference in how Gen Z's compulsive buying influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H1n.
There is a significant difference in how Gen Z's personal integrative benefit influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic Limited Problem-Solving H2a.
There is a significant difference in how Gen Z's quality consciousness influenced their limited problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H2b.
There is a significant difference in how Gen Z's consumerAos needs for uniqueness influenced their limited problem-solving buying decisions between the pre-pandemic and during-pandemic H2c.
There is a significant difference in how Gen Z's green consumer value influenced their limited problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H2d.
There is a significant difference in how Gen Z's support for customer influenced their limited problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H2e.
There is a significant difference in how Gen Z's materialism influenced their limited problemsolving buying decisions between the pre-pandemic and during-pandemic periods.
H2f.
There is a significant difference in how Gen Z's brand equity influenced their limited problemsolving buying decisions between the pre-pandemic and during-pandemic periods.
H2g.
There is a significant difference in how Gen Z's conformity motivation influenced their limited problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H2h.
There is a significant difference in how Gen Z's impulsive buying influenced their limited problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H2i.
There is a significant difference in how Gen Z's hedonic shopping value influenced their limited problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H2j.
There is a significant difference in how Gen Z's vanity influenced their extensive problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H2k.
There is a significant difference in how Gen Z's consumer ethnocentrism influenced their limited problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H2l.
There is a significant difference in how Gen Z's susceptibility to reference group influence influenced their limited problem-solving buying decisions between the pre-pandemic and duringpandemic periods.
H2m.
There is a significant difference in how Gen Z's compulsive buying influenced their limited problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H2n.
There is a significant difference in how Gen Z's personal integrative benefit influenced their limited problem-solving buying decisions between the pre-pandemic and during-pandemic Habitual Problem-Solving H3a.
There is a significant difference in how Gen Z's quality consciousness influenced their habitual problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
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H3b.
There is a significant difference in how Gen Z's consumerAos needs for uniqueness influenced their habitual problem-solving buying decisions between the pre-pandemic and during-pandemic H3c.
There is a significant difference in how Gen Z's green consumer value influenced their habitual problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H3d.
There is a significant difference in how Gen Z's support for customer influenced their habitual problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H3e.
There is a significant difference in how Gen Z's materialism influenced their habitual problemsolving buying decisions between the pre-pandemic and during-pandemic periods.
H3f.
There is a significant difference in how Gen Z's brand equity influenced their habitual problemsolving buying decisions between the pre-pandemic and during-pandemic periods.
H3g.
There is a significant difference in how Gen Z's conformity motivation influenced habitual limited problem-solving buying decisions between the pre-pandemic and during-pandemic H3h.
There is a significant difference in how Gen Z's impulsive buying influenced their habitual problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H3i.
There is a significant difference in how Gen Z's hedonic shopping value influenced their habitual problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H3j.
There is a significant difference in how Gen Z's vanity influenced their habitual problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H3k.
There is a significant difference in how Gen Z's consumer ethnocentrism influenced their habitual problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H3l.
There is a significant difference in how Gen Z's susceptibility to reference group influence influenced their habitual problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H3m.
There is a significant difference in how Gen Z's compulsive buying influenced their habitual problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
H3n.
There is a significant difference in how Gen Z's personal integrative benefit habitual their limited problem-solving buying decisions between the pre-pandemic and during-pandemic periods.
Material and Methodology Research Design This research use the Partial Least Squares - Multi-Group Analysis (PLS-MGA) framework to analyze behavioral shifts and persistent patterns before and during the pandemic.
PLS-MGAAos ability to examine relationships across diverse groups makes it especially suitable for exploring the unique experiences of Generation Z during this transformative period.
Guided by the quantitative approach outlined by Saunders et al.
, this study collects and statistically analyzes numerical data, providing robust and empirically grounded insights.
The research also adopts a causality perspective, delving into the 'why' and 'how' of generational behavior changes, offering a comprehensive understanding of the dynamics shaping Generation ZAos perceptions and actions.
The conceptual framework employs hierarchical component models (HCM.
, also known as second-order constructs, which integrate higher-order constructs (HOC.
and their subcomponents, lower-order constructs (LOC.
(Hair et al.
, 2018.
Putra, 2022.
Sarstedt et al.
, 2.
The HOCs are online shopping behavior (X) and customer buying decision (Y).
For online shopping behavior (X).
LOCs include factors such as quality consciousness, uniqueness, green consumer value, materialism, brand equity, impulsive buying, and conformity motivation.
For customer buying decisions (Y).
LOCs focus on extensive, limited, and habitual problem-solving.
Unit Analysis and Survey Strategy This study analyzed two datasets collected at distinct time points.
The first survey in 2018 captured pre-pandemic behaviors, while a follow-up survey in 2022 examined shifts during the The 2022 survey included 250 Generation Z participants, compared to 130 in 2018, reflecting an increased willingness to engage in research during challenging times.
This dual-survey approach provides a comprehensive understanding of behavioral changes over time.
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Result and Discussion Result Measurement Model Evaluation The outer model is crucial in PLS-SEM (Partial Least Squares Structural Equation Modelin.
for assessing validity and reliability by illustrating the relationships between observed indicators and latent According to Hair et al.
, convergent validity requires loading factors exceeding 0.
while Hair et al.
suggest reflective indicator loadings above 0.
50 are sufficient for reliability.
balance these standards, a benchmark of 0.
60 is commonly adopted.
In higher-order component models (HCM), the repeated indicator approach is used to estimate relationships between higher-order constructs and their indicators (Putra, 2.
This method links lower-order construct indicators directly to the higher-order construct, repeating them to assess the strength and direction of relationships.
Ensuring these loadings are significant and align with expectations is essential to validate the hierarchical structure of the model (Andriani & Putra, 2.
Convergent validity was further assessed using the average variance extracted (AVE), with a benchmark of >0.
The findings showed all items had loading values above 0.
7 and p-values below 05, confirming indicator reliability.
The AVE values also exceeded 0.
5, indicating that latent variables explained over half the variance in their reflective indicators, thus validating the modelAos structure.
Table 1.
Construct Validity and Reliability .
AVE
Fornell Larcker Criterion
X10
X11
X12
X13
X14
X10
X11
X12
X13
X14
Note.
The numbers in bold represent the square root of AVE correlation between the variables CA indicates CronbachAos alpha.
CR indicates composite reliability.
AVE indicates average variance extracted.
X indicates online chopping behaviour.
X1 indicates quality consciousness.
indicates consumerAos needs for uniqueness.
X3 indicates green consumer value.
X4 indicates support for customer.
X5 indicates materialism.
X6 indicates brand equity.
X7 indicates conformity motivation.
X8 indicates impulsive buying.
X9 indicates hedonic shopping value.
X10 indicates vanity.
X11
indicates consumer ethnocentrism.
X12 indicates susceptibility to reference group influence.
X13
indicates compulsive buying.
X14 indicates personal integrative benefit.
Y indicates consumer buying Y1 indicates extensive problem solving.
Y2 indicates limited problem solving.
Y3 indicates habitual decision making.
The testing results confirmed that all values met the required thresholds, with the loading factor and average variance extracted (AVE) exceeding 0.
50, demonstrating that each latent variable was effectively measured.
The next step involved addressing potential discriminant validity issues, focusing on correlation values among the model components.
While no convergent validity concerns were identified (Ramayah et al.
, 2.
, discriminant validity was assessed using methods such as the Fornelarcker Criterion.
HTMT .
eterotrait-monotrait rati.
, and cross-loadings.
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Henseler et al.
highlighted the limitations of the Fornell-Larcker Criterion in detecting discriminant validity issues and recommended the HTMT approach.
To ensure discriminant validity, bootstrapping with 5,000 resamples was applied, setting confidence intervals (CI) at 95.
0% and 5.
None of the dimensions showed CI values exceeding 1.
00, confirming the absence of discriminant validity issues.
Additionally, cross-loading analysis verified that indicators exhibited higher loading factors on their respective constructs, reinforcing discriminant validity (Hair et al.
, 2.
After validating the indicators, reliability was evaluated using Cronbach's alpha and composite According to Dijkstra and Henseler .
, composite reliability should exceed 0.
7, and Cronbach's alpha should surpass 0.
6 to confirm construct reliability.
All constructs in this study met these benchmarks, establishing their reliability and ensuring the robustness of the measurement model.
Structural Model Evaluation With the validity and reliability of the measurement model confirmed, the next step was testing the structural model to examine the relationships between latent variables.
Following Ramayah et al.
, the structural model was assessed using inner VIF values, the coefficient of determination (RA), model fit, and predictive relevance (QA).
To detect multicollinearity, inner VIF values were analyzed, revealing no strong or perfect correlations between independent variables.
As per Hair et al.
, all VIF values were below 5.
00, confirming the absence of multicollinearity.
The coefficient of determination provided further insights into the model's explanatory power.
Online shopping behaviour explained its endogenous variable with a variance of 100% (RA = 1.
indicating the model fully captured this construct without external influences.
In contrast, the buying decision variable showed an RA value of 55.
1%, suggesting that 44.
9% of its variance was influenced by factors not included in the model.
Further analysis revealed that extensive problem solving explained 4% of its variance, limited problem solving 91.
9%, and habitual decision making 91.
2%, with the remaining percentages indicating external influences.
Predictive relevance was evaluated using the QA metric, with values above zero confirming the model's ability to predict endogenous latent variables, as highlighted by Putra and Ardianto .
Model fit was assessed using the standardized root mean square residual (SRMR) and the normed fit index (NFI).
According to Ramayah et al.
and Hair et al.
, the SRMR value below 0.
indicated a good fit for the model .
ee Table .
Construct R-square Table 2.
Structural Model Assesment
RModel Fit
Saturated QApredict
Index
SRMR
d_ULS Chi-square Infinite NFI Estimated Infinite Note.
X indicates online chopping behaviour.
Y indicates consumer buying decision.
Y1 indicates extensive problem solving.
Y2 indicates limited problem solving.
Y3 indicates habitual decision SRMR indicates standardized root mean square residual.
Findings After evaluating the structural model, hypothesis testing was conducted to confirm or refute the studyAos proposed hypotheses.
This assessment relied on the path coefficient and T-Statistic values obtained via the bootstrapping method.
Of the 42 hypotheses tested, 16 were accepted, as detailed in Table 3.
Among the factors examined, quality consciousness emerged as a significant determinant of purchasing decisions, particularly for Generation Z.
This factor reflects the importance consumers place on the quality of products or services.
Before the pandemic.
Gen Z's quality consciousness did not significantly influence extensive problem-solving behaviours in online shopping, as indicated by a pvalue below 0.
However, the pandemic introduced uncertainties in supply chains, product Rino F Boer / Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia.
Vol.
, 2024, 463-478
availability, and quality assurance, prompting a shift in behaviour.
During this period, quality consciousness became a notable factor in extensive problem-solving, with a path coefficient of 0.
and a highly significant p-value of 0.
The pandemic also altered Gen Z's approach to limited problem-solving.
Previously, quality consciousness had no significant effect in this context .
-value < 0.
However, during the pandemic, its influence became apparent, with a path coefficient of 0.
=0.
, highlighting an increased emphasis on quality even in simpler purchasing scenarios.
Similarly, habitual decision-making, often regarded as automatic, showed no significant relationship with quality consciousness before the Yet, during the pandemic, quality considerations played a role, with a path coefficient of 065 .
=0.
These findings led to the acceptance of hypotheses H1a.
H2a, and H3a.
They underscore the profound impact of global events on consumer values and demonstrate Gen Z's adaptability and evolving online shopping behaviours during periods of uncertainty.
Table 3.
Hypothesis Testing H1a H1b H1c H1d H1e H1f H1g H1h H1i H1j H1k H1l H1m H1n H2a H2b H2c H2d H2e H2f H2g H2h H2i H2j H2k H2l H2m H2n H3a H3b H3c H3d H3e H3f H3g H3h H3i H3j H3k H3l H3m H3n Path X1 Ie Y1 X2 Ie Y1 X3 Ie Y1 X4 Ie Y1 X5 Ie Y1 X6 Ie Y1 X7 Ie Y1 X8 Ie Y1 X9 Ie Y1 X10 Ie Y1 X11 Ie Y1 X12 Ie Y1 X13 Ie Y1 X14 Ie Y1 X1 Ie Y2 X2 Ie Y2 X3 Ie Y2 X4 Ie Y2 X5 Ie Y2 X6 Ie Y2 X7 Ie Y2 X8 Ie Y2 X9 Ie Y2 X10 Ie Y2 X11 Ie Y2 X12 Ie Y2 X13 Ie Y2 X14 Ie Y2 X1 Ie Y3 X2 Ie Y3 X3 Ie Y3 X4 Ie Y3 X5 Ie Y3 X6 Ie Y3 X7 Ie Y3 X8 Ie Y3 X9 Ie Y3 X10 Ie Y3 X11 Ie Y3 X12 Ie Y3 X13 Ie Y3 X14 Ie Y3 Main Model (All Groups Include.
O/STDEV O (Pr.
Each Groups (Pre Vs.
During Pandemic Settin.
O/STDEV O/STDEV O (Du.
(Pr.
(Du.
(Pr.
(Du.
Significant Different Between Group O (Pre P (Pre Vs.
Du.
Vs.
Du.
Rino F Boer / Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia.
Vol.
, 2024, 463-478
Note.
H indicates hypothesis.
O indicates original sample.
M indicates sample mean.
O/STDEV
indicates t-statistics.
P indicates p values.
O (Pr.
indicates original sample of pre-pandemic setting O/STDEV (Pr.
indicates t-statistics of pre-pandemic setting group.
P (Pr.
indicates p values of pre-pandemic setting group.
O (Du.
indicates original sample of during-pandemic setting group.
O/STDEV (Du.
indicates t-statistics of during-pandemic setting group.
P (Du.
indicates p values of during-pandemic setting group.
O (Pre Vs.
Du.
indicates original sample of differentiation between pre and during-pandemic setting group.
P (Pre Vs.
Du.
indicates p values of differentiation between pre and during-pandemic setting group.
X1 indicates quality consciousness.
X2 indicates consumerAos needs for uniqueness.
X3 indicates green consumer value.
X4 indicates support for customer.
indicates materialism.
X6 indicates brand equity.
X7 indicates conformity motivation.
X8 indicates impulsive buying.
X9 indicates hedonic shopping value.
X10 indicates vanity.
X11 indicates consumer X12 indicates susceptibility to reference group influence.
X13 indicates compulsive X14 indicates personal integrative benefit.
Y indicates consumer buying decision.
Y1 indicates extensive problem solving.
Y2 indicates limited problem solving.
Y3 indicates habitual decision In terms of green consumer value, it was found that during pre-pandemic, this had no significant impact on Gen Z's extensive problem-solving behaviors .
< 0.
However, during the pandemic, this changed, with green consumer values significantly influencing extensive problem-solving, reflected by a path coefficient of 0.
= 0.
Similar transformations were observed in limited problemsolving and habitual decision-making, where green consumer values previously had no significant During the pandemic, path coefficients of 0.
069 and 0.
070, respectively .
oth p = 0.
indicated a newfound alignment of Gen Z's decisions with their green values.
These findings supported hypotheses H1c.
H2c, and H3c, demonstrating how external events can intensify internal consumer values and reshape behaviors.
The role of customer support also evolved during the pandemic.
Pre-pandemic, customer support had minimal influence on Gen Z's extensive problem-solving behaviors .
< 0.
However, the pandemic highlighted its importance, with a path coefficient of 0.
= 0.
during this period.
This trend extended to limited problem-solving .
049, p = 0.
and habitual decision-making .
p = 0.
, indicating that Gen Z increasingly valued customer support in straightforward and routine purchasing decisions.
These findings led to the acceptance of hypotheses H1d.
H2d, and H3d, emphasizing the growing importance of customer support in shaping purchasing behaviors during uncertain times.
The role of customer support also evolved during the pandemic.
Pre-pandemic, customer support had minimal influence on Gen Z's extensive problem-solving behaviors .
< 0.
However, the pandemic highlighted its importance, with a path coefficient of 0.
= 0.
during this period.
This trend extended to limited problem-solving .
049, p = 0.
and habitual decision-making .
p = 0.
, indicating that Gen Z increasingly valued customer support in straightforward and routine purchasing decisions.
These findings led to the acceptance of hypotheses H1d.
H2d, and H3d, emphasizing the growing importance of customer support in shaping purchasing behaviors during uncertain times.
Furthermore, in terms of materialism, defined as the importance placed on acquiring and possessing material goods, played a notable role in Gen ZAos online shopping behaviors during the Pre-pandemic, materialistic tendencies had no significant influence on extensive problemsolving behaviors, as evidenced by a p-value below 0.
However, during the pandemic, materialism began to influence extensive problem-solving, with a path coefficient of 0.
= 0.
This trend also extended to limited problem-solving and habitual decision-making, where pre-pandemic data showed no significant effect.
During the pandemic, both decision-making processes were influenced by materialism, with path coefficients of 0.
= 0.
for each.
These findings supported hypotheses H1e.
H2e, and H3e, highlighting the increasing importance of materialistic values in Gen ZAos purchasing behaviors during uncertain times.
Rino F Boer / Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia.
Vol.
, 2024, 463-478
Figure 2.
Bootstrapping Results of Main Model When it comes to impulsive buying, characterized by spontaneous and unplanned purchases, also saw a shift in influence during the pandemic.
Before the pandemic, impulsive buying tendencies did not significantly impact extensive problem-solving behaviors, as indicated by a p-value below 0.
However, the pandemic introduced uncertainties that made impulsive tendencies more influential, with a path coefficient of 0.
= 0.
during this period.
Similarly, limited problem-solving and habitual decision-making, previously unaffected by impulsive buying, showed path coefficients of 049 .
= 0.
for both during the pandemic.
These findings validated hypotheses H1h.
H2h, and H3h, emphasizing the growing influence of impulsive buying on Gen ZAos shopping behaviors amid global challenges.
The concept of brand equity, representing the value and strength a brand contributes to a product or service, emerged as another significant factor during the pandemic.
Pre-pandemic.
Gen ZAos perception of brand equity had no notable impact on limited problem-solving behaviors .
< 0.
However, during the pandemic, brand equity began influencing limited problem-solving decisions, with a path coefficient of 0.
= 0.
This finding led to the acceptance of hypothesis H2f, underscoring the increased role of brand equity in shaping Gen ZAos decision-making processes during the pandemic.
Conclusion This research aimed to answer two core questions: (RQ.
What factors influenced Generation Z's online shopping behaviour before the pandemic? and (RQ.
How have these factors evolved during the pandemic? By employing a Partial Least Squares - Multi-Group Analysis (PLS-MGA) framework and analysing the responses of Generation Z participants from two distinct time periods .
8 and 2.
, this study identified significant shifts in decision-making stylesAiextensive, limited, and habitualAiduring the pandemic.
The findings demonstrated that external global events, such as the COVID-19 pandemic, significantly influenced internal consumer values, leading to behaviour transformations.
Key factors like quality consciousness, green consumer value, and materialism, which had minimal influence on decision-making pre-pandemic, became prominent during the pandemic.
For example, quality Rino F Boer / Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia.
Vol.
, 2024, 463-478
consciousness emerged as a critical determinant across all decision-making styles, with statistically significant path coefficients .
, 0.
063 for extensive problem-solving, p=0.
Similarly, green consumer values became more impactful, aligning with heightened awareness of sustainability during Additionally, materialism and impulsive buying tendencies gained prominence, reflecting shifts in emotional and practical priorities.
The study also highlighted the rising importance of customer support and brand equity in Gen ZAos decision-making processes during the pandemic.
Customer support gained significant influence in both routine and complex purchasing decisions, while brand equity underscored the growing reliance on trust and familiarity during uncertain times.
These findings emphasize the role of communication in shaping consumer behaviour.
Businesses and marketers must effectively communicate quality, sustainability, and brand trustworthiness to resonate with the evolving values of Generation Z.
The study contributes to communication scholarship by highlighting how global crises amplify the importance of strategic messaging in digital contexts, fostering a deeper understanding of how external factors reshape consumer priorities.
Ultimately, this research underscores the adaptability of Generation Z and their pivotal role in driving the digital economy, offering actionable insights for businesses aiming to engage this influential demographic during and beyond periods of crisis.
References