Readiness to Reduce Plastic Waste in Food Delivery and E-Commerce in Bangkok,Thailand

Abstract

The rise of online Food delivery and E-commerce has significantly increased plastic waste. This study aims to examine plastic waste generation and explore pro-environmental behaviors of consumers in Bangkok. Data collection involved questionnaires and in-depth interviews. In 2024, plastic waste from Food delivery in Bangkok is projected to range from 0.3 to 4.6 million kilograms, while E-commerce could generate 3.7–12 million kilograms million kilograms annually. Consumers in the Food delivery sector generally express readiness to reduce plastic usage but often expect leadership from government agencies or stores. E-commerce readiness to reduce plastic waste is significantly lower due to concerns about product protection. Key factors influencing PEB are Subjective norms (SN), Perceived behavioral controls (PBC), and Behavioral intentions (BIT), which collectively account for 87.2% of pro-environmental actions. To address plastic waste in Food delivery and E-commerce, collaborative efforts among government agencies, platform providers, packaging manufacturers, and consumers are critical.

Keywords

food delivery e-commerce pro-environment behavior single-use plastic plastic waste

Introduction

The online food delivery industry in Thailand has reached an estimated value of 4.14 trillion THB. According to the Kasikorn Research Center (2019), the market value of online food delivery in 2018 was approximately 35 billion THB, representing a 14% growth from the previous year. The COVID-19 pandemic further accelerated this trend as consumers increasingly shifted from dining out to ordering food online. Consequently, a massive volume of packaging waste, primarily single-use plastics (SUPs) such as plastic bags, cups, cutlery, and straws, has been generated. Additionally, condiment sachets—often unused by consumers—are frequently discarded. More concerningly, waste segregation at the source remains minimal, and urban waste collection systems in Thailand lack proper segregation mechanisms, resulting in a substantial increase in plastic waste mixed with general municipal solid waste.

In the e-commerce sector, the market value in 2020 was approximately 3.78 trillion THB, with B2C transactions accounting for the largest share at 2.17 trillion THB, followed by B2B (0.84 trillion THB) and B2G (0.77 trillion THB). The Electronic Transactions Development Agency (ETDA, 2021) projected that the Thai e-commerce market would grow to 4.01 trillion THB in 2021. Packaging and logistics in this sector require significant material inputs—including cardboard boxes, adhesive tapes, and bubble wrap—all of which have increased dramatically with the rise of online shopping.

Despite the rapid expansion of these industries, empirical studies quantifying plastic waste from food delivery and e-commerce remain limited at both local and national scales. Existing research in Thailand has predominantly concentrated on the food delivery sector, with comparatively little focus on plastic waste associated with e-commerce activities. The few existing studies are preliminary in nature. For instance, Prince of Songkla University, Phuket Campus (2019) estimated that online food delivery services generate approximately 37 million plastic items annually, while Food Passion Co. projected as many as 560 million pieces per year (Jitpleecheep, 2019). Simachaya (2020) reported that during the COVID-19 pandemic, although total waste decreased in major cities such as Bangkok and other tourism hubs, the proportion of plastic waste increased by more than 60% in Bangkok and by 30% in Nakhon Ratchasima Municipality, mainly due to food delivery packaging.

Using secondary data, Wongprapinukul and Wasnadamrongdee (2021a) estimated that plastic waste from food delivery in 2020 ranged between 1.12–3.08 billion pieces, and could rise to 2.33–6.40 billion pieces by 2025, equivalent to 34,883–95,928 tons, assuming an average weight of 15 g per item. The upper-bound estimate represents approximately 4.8% of the total national plastic waste generation of 2 million tons forecasted by the Pollution Control Department (2020). These figures highlight a critical need for further empirical investigation to develop robust estimation models and inform sustainable plastic waste management planning in Thailand.

Previous Thai studies have mostly focused on specific behaviors, such as plastic bag refusal or household recycling (Arunnual, 2019; Pranitham, 2019), while a few addressed consumer perceptions in food delivery services (Wongprapinkul & Wasanadamrongdee, 2021b). Nevertheless, these studies did not integrate behavioral determinants with quantitative waste data or apply comprehensive frameworks to explain readiness to reduce plastic waste within the rapidly expanding food delivery and e-commerce sectors.

There is a lack of integrated studies linking behavioral intention models (e.g., TPB) with empirical estimation of plastic waste to assess consumers’ readiness for waste reduction in Thailand’s digital consumption economy. Addressing this gap is essential to develop evidence-based behavioral interventions and policy strategies for sustainable plastic waste management. To fill these gaps, this study aims to (1) quantify plastic waste from food delivery and e-commerce in Bangkok, (2) examine factors influencing pro-environmental behavior, and (3) propose policy recommendations for sustainable plastic waste management.

The results of this research are beneficial to policymakers, as well as public and private agencies involved in online food delivery and e-commerce businesses. Specifically, the study provides quantitative estimates of plastic waste generated from food delivery and online shopping activities. Without such estimations, it would be difficult to understand the actual situation and to formulate effective policy measures. Furthermore, examining the readiness of both businesses and consumers is a crucial factor in designing and implementing plastic waste management policies. These insights can support the development of efficient and practical strategies for achieving successful and sustainable plastic waste management.

Literature Review

Current Situation in Plastic Waste Management from Food Delivery and E-Commerce in Thailand

In 2020, the Pollution Control Department, through the Waste and Hazardous Substance Management Division, collaborated with relevant public and private sector organizations to establish measures for managing plastic waste from Food delivery services. The objective was to cultivate a “New Normal” in behavior among businesses and consumers, aligning with the strategic goals outlined in the Plastic Waste Management Roadmap 2018–2030 (Pollution Control Department, 2020).

In practice, some food delivery services now offer reusable container options. For example, Indy Dish (which temporarily suspended operations during the COVID-19 pandemic due to employee safety concerns) operates similarly to Deliver Zero by partnering with restaurants to provide reusable food containers. Consumers pay a deposit of 100 baht per container and are required to return the cleaned containers to Indy Dish within 7 days. The service then sanitizes the containers according to industry standards before making them available for reuse (Thamphanichwong et al., 2021).

Currently, the “Send Plastic Home” project accepts two types of clean plastic waste from the public: stretch plastics and rigid plastics. There are 10 Drop-off Points on Sukhumvit Road in Bangkok, such as Singha Complex, The Emporium, and Tesco Lotus. The project incentivizes public participation through the ECOLIFE app, which allows users to accumulate points for rewards (Thamphanichwong et al., 2021).

Additionally, there is a use for clean plastic waste from Food delivery services: converting it into alternative fuel for cement kilns. For example, N15 Technology in Amata Nakorn Industrial Estate is engaged in this process. This option can handle various types of plastic waste, including those that cannot be recycled, making it a viable solution for managing plastic waste (Thampanichwong & Thailand Development Research Institute (TDRI), 2020).

The Situation of Waste Management Arising from Food Delivery and E-Commerce in Foreign Countries

Measures to address plastic waste from Food delivery used in other countries are summarized in Table 1. These measures encompass a variety of strategies and approaches.

Table 1.

The situation of waste management from Food delivery and E-commerce in foreign countries

	Country	Detail	Reference
1	The United States	In the United States, some startups are offering zero-waste food delivery services. For examples	Thamphanichwong et al. (2021)
		1) DeliverZero: This startup provides a zero-waste food delivery service by using reusable containers. Customers pay a deposit for the containers, which are collected, cleaned, and reused for future orders
		2) Indy Dish: Similar to DeliverZero, Indy Dish offers reusable food containers for delivery orders. Customers return the containers within a specified period for cleaning and reuse
		3) EcoCasi: EcoCasi focuses on providing sustainable packaging solutions and waste reduction strategies for food delivery services
		4) Zero Waste Daniel: This company offers eco-friendly packaging options for food delivery and emphasizes reducing waste through creative reuse of materials
2	European union	The European Union’s new regulation, the Single Use Plastics Directive (2019), focuses on a comprehensive ban on certain single-use plastics. The key points of the directive are as follows	European Commission (2024)
		Ban on single-use plastics: EU member states are required to pass national laws to ban the production and use of eight specific types of single-use plastics. These include cutlery (forks, knives, spoons, and chopsticks), plates, straws, cotton bud sticks, drink stirrers, balloon sticks, foam food containers, and products containing oxo-degradable plastics
		Reduction of plastic Cups and food containers: Member states must implement measures to reduce the use of plastic cups and lids, as well as containers for ready-to-eat foods
		Increased recycling targets: Governments are required to set higher targets for the collection of plastic bottles. By 2025, at least 25% of PET bottles must be made from recycled plastic, and by 2030, at least 30% of all plastic bottles should contain recycled material
3	China	China implemented a comprehensive plastic waste management law in September 2020, significantly increasing penalties for non-compliance, with fines rising up to tenfold. The key components of China’s approach to reducing single-use plastic waste include	Manopavit (2021)
		Mandatory reporting by retailers: Retailers across the country are required to report their use of single-use plastics, ensuring transparency and accountability
		Five-year Roadmap for waste elimination: The National Development and Reform Commission (NDRC) of China introduced a 5-year roadmap aimed at eradicating plastic waste. The policy mandates a nationwide ban on certain plastics and sets specific targets
		- By the end of 2020: China banned the use of non-degradable plastic bags plastic bags in supermarkets and shopping malls in major cities, including in food delivery services
		- By 2022: The country aimed to reduce the use of single-use plastic bags in both E-commerce and food delivery services by 30%. Additionally, delivery services in major cities like Beijing and Shanghai were prohibited from using non-degradable plastics, with a nationwide ban planned for 2025
		- Ban on difficult-to-degrade plastics: Starting in 2022, delivery services in major Chinese cities were prohibited from using plastics that are difficult to degrade, with a goal to extend this ban nationwide by 2025
4	Japan	One of the key actions plans that the Japanese government has been implementing to drive the country towards a circular economy, as part of its environmental strategy, is the reduction of plastic use to decrease the volume of plastic waste. The specific actions taken include	Buffet (2021)
		- Single-use plastic fee: In 2020, the Japanese government mandated that retail stores, convenience stores, department stores, and restaurants stop providing single-use plastic (SUP) bags for free. Customers who want a plastic bag must pay a fee of around 3 to 5 yen per bag. This measure aims to reduce plastic waste and encourage Japanese citizens to cut down on the use of single-use plastic bags
		- Ban on single-use plastic utensils: In early 2021, the Japanese government proposed a bill to ban businesses from providing single-use plastic items such as spoons, forks, straws, and plastic containers to customers. The law was enacted and began enforcement in April 2022, with violators facing fines of up to 500,000 yen (approximately 140,000 Thai baht). However, the law exempts small businesses from this requirement
		The main objectives of Japan’s new legislation are as follows
		Reduce plastic waste: The primary goal is to decrease the volume of plastic waste generated within the country, addressing environmental concerns and promoting sustainability
		Encourage businesses to adopt biodegradable materials: The legislation aims to push businesses subject to the law to switch to biodegradable materials for eating utensils and food containers. This shift is intended to lessen the environmental impact of single-use plastics
		Change consumer behavior: The law seeks to modify consumer habits by reducing the use of single-use plastics. This is evident from the mandate requiring retail stores, convenience stores, department stores, and restaurants to stop providing single-use plastic bags for free. As a result, plastic bag usage dropped significantly—by 70% in convenience stores and 80% in supermarkets

Current Situation of Plastic Waste Generated from E-Commerce and Food Delivery in Thailand

Currently, research forecasting the volume of plastic waste generated by Food delivery at both local and national levels is quite limited. The studies found mainly provide preliminary estimates, as shown in Table 2. Wongprapinkul et al., (2021a) estimated the amount of plastic waste generated by the Food delivery industry. Researchers have forecasted the volume of plastic waste based on the market value of the online Food delivery business, and based on three key assumptions: (1) the growth rate of the online Food delivery business, (2) the number of orders, and (3) the amount of plastic waste (pieces) per order. Based on these assumptions, the volume of plastic waste generated by the online Food delivery business in 2020 was estimated to be between 1.12 and 3.08 billion pieces. This volume is expected to rise to between 2.325 and 6.395 billion pieces by 2025, which is equivalent to a weight of 34,883 to 95,928 tons.

Table 2.

Preliminary report on the forecasted volume of plastic waste generated by the Food delivery business

Results	Reference
In 2019 (before the COVID-19 pandemic), the food delivery business had 20 million orders, generating up to 140 million pieces of plastic waste	Kasikorn Research Center (2019) cited via Thamphanichwong et al. (2021)
During the COVID-19 pandemic, the volume of plastic waste from food delivery is estimated to have doubled to 280 million pieces. Each food delivery order typically generates 7 pieces of waste: a Food container, a condiment bag, a plastic spoon, a plastic fork, a cutlery bag, a soup bag, and a plastic carrier bag for the entire order
Prince of Songkhla University, Phuket Campus, has estimated that plastic waste from the online food delivery business could reach up to 37 million pieces per year	Prince of Songkla university, Phuket campus. (2019)
Food Passion Company has estimated that the volume of waste from food delivery services amounts to 560 million pieces per year	Jitpleecheep (2019)
The proportion of plastic waste has increased in almost every city, particularly from online food orders delivered to homes or workplaces. In Bangkok, plastic waste has risen by more than 60%	Office of Natural Resources and Environmental Policy and Planning (2020)

The Plastic Institute estimated the amount of plastic waste from domestic producers in 2018-2020 (Plastic Institute, 2020). The Plastics Institute conducted a study on the amount of plastic waste from domestic producers by analyzing the material flow of plastic waste from production, users, waste management phase, and recycling. It was found that in 2020, Thailand generated approximately 2,763.0 kilotons of plastic waste from all activities within the country.

Factors Affecting Pro-Environmental Behavior

“Pro-environmental behavior” refers to “behavior that minimizes environmental damage or exploitation” (Steg & Vlek, 2009 cited via Arunnual, 2019). Factors affecting Pro-environmental behavior, such as Attitude (Arunnual, 2019; Pranitham, 2019; Siripokanon, 2013), Ethical Intention (Arunnual, 2019), and Personal norm (Thanathornchat. 2021), For demographic factors, in terms of gender, most research indicates that women tend to care more about the environment than men, for example, women express more concern about environmental degradation than men and are more likely to live environmentally friendly lives than men (Blocker et al., 2015 cited via Arunnual, 2019). Women express statistically significant more environmental protection than men (Goldberg et al., 2018). In terms of age, some studies have found that older people are more concerned about the environment, while in some studies younger people are more environmentally responsible (Bronfman et al., 2015). In terms of education, those with higher education are more concerned about the environment. People with higher education are more concerned about the environment and are more willing to exhibit environmentally friendly behaviors because they have been educated about environmental hazards (Bronfman et al., 2015).

On the contrary, Pranitham (2019) found that gender, age, and occupation factors were not related to environmental conservation behavior in households and hotels. In addition, the types of hotels stayed and different levels of education were not related to environmental conservation behavior in hotels. Problems and obstacles in environmental conservation include the extravagant use of natural resources and the environment, a lack of awareness and knowledge about proper waste management (Pranitham, 2019), insufficient and unclear waste separation bins, the high cost of environmentally friendly products, and a lack of cooperation from various stores (Siripokanon, 2013).

Methodology

Research Framework

The scope of this research is outlined in Figure 1, focusing on assessing the readiness to reduce plastic waste generated by Food delivery and E-commerce activities in Bangkok.

Study Area and Data Collection

This research applied quantitative methodologies. Primary data plays a crucial role in examining consumer attitudes, behaviors, and opinions, providing valuable insights for the study (Chrysochou, 2017). Primary data for this study is collected using a structured questionnaire administered through Google Forms. The questionnaire was prepared in Thai. Upon completion by participants, the responses are automatically recorded and stored in an Excel database. The survey targets approximately 250 responses from consumers in Bangkok. Secondary data is derived from existing study reports and literature reviews, including information sourced from websites and news outlets.

Questionnaire Design and Sampling

The development of measurement questions in each section of the questionnaire was guided by the framework illustrated in Figure 1. The survey design and the customization of its questions underwent expert review to ensure validity and relevance. It comprises four sections: Basic Information: Captures demographic and general information about the respondents. Plastic Waste Generation: Assesses the amount of plastic waste resulting from the use of Food delivery and E-commerce services. Pro-Environmental Behavior: Evaluates respondents’ environmentally conscious behaviors and practices. Readiness to Reduce Plastic Waste: Examines the respondents’ willingness and preparedness to reduce plastic waste associated with Food delivery and E-commerce activities.

The questionnaire sampling was distributed using a combination of online and on-site sampling methods. For the online distribution, the Snowball Sampling technique was employed, whereby initial respondents were invited to complete the survey and then encouraged to share it with others within their social networks. This approach was conducted through multiple online channels, including email, Line, and Facebook, to ensure broader reach and participation among active social media users. In addition, on-site sampling was carried out in selected public areas in Bangkok to capture responses from individuals who might not be actively engaged online. A total of 250 consumers residing in Bangkok participated in the survey. This sample size was considered sufficient for preliminary statistical analysis and for capturing diverse perspectives regarding consumer experiences and behavioral intentions toward Food delivery and E-commerce.

Model Analysis

Reliability and Validity

Factors (variables) influencing pro-environmental behavior were examined reliability and validity on the data to ensure the validity of the data before running the structural equation model (Bolarinwa, 2015; Kimberlin & Winterstein, 2008). Composite reliability (CR) and Cronbach’s alpha coefficient were used to test the reliability of all variables in this study (Bian, 2023; Fornell & Larcker, 1981). The validity of the variables in this study used the construct validity check by calculating from the multitrait-multimethod matrix, which is the calculation from the test consisting of two or more traits and two or more measurement methods, and then calculating the two types of validity, namely, convergent validity and discriminant validity (Saiyot & Saiyot, 2000).

Hypothesis Test

In this study, AMOS 24.0 was used to construct a structural equation model for hypothesis testing. Hypothesis of the relationship between various variables and pro-environmental behavior. SEM Path estimates summary, Model fit indices, and R-squared were conducted.

Estimated Plastic Waste Generation

The estimation of plastic waste generated by Food delivery and E-commerce businesses utilizes multiple data sources to project waste levels in Bangkok. These sources include statistical data, prior research on plastic waste from online Food delivery services, and findings from the questionnaire survey conducted in this study. The projection of plastic waste generation in the food delivery sector is based on a combination of methodologies, including extrapolation from existing research to extend insights from prior studies, population data analysis to estimate the number of Bangkok residents using food delivery services, market value analysis to assess the economic scale of food delivery operations, and the incorporation of historical waste data. The methodologies and assumption are detailed in Table 3.

Table 3.

Plastic waste estimation from Food delivery in Bangkok in 2024 from four methods

Methods	Assumption detail	Key assumptions	Uncertainty	Results in 2024
Methods	Assumption detail	Key assumptions	Uncertainty	Million pcs	Million kg
1) Revised analysis based on the study by Boonchanit Wongprapinkul (2021b)	1. Food delivery market value — Kasikorn Research Center estimates the market value of the food delivery business in 2019 to be 33,000 – 35,000 million baht (Kasikorn Research Center, 2019)	33,000 million baht	29,500–36,000 million baht	14.7 – 63.1	7.7 – 31.2
	2. Food delivery growth rate — the researchers used the food delivery business growth rate from 2019 as a baseline to determine the growth rate in 2018 and 2020–2024, which was set at 15% per year	15%	10–20%
	3. Order value per time — data from Food Passion that pegged the average order value per time at 250 baht (referenced via Wongprapinkul et al., 2021a)	250 baht/time	225–275 baht/time
	4. Amount of plastic waste—this section defines a minimum and a maximum assessment. The minimum is based on Food Passion’s calculations, which set the amount of plastic waste at 4 pieces per order. The maximum is based on the results of a survey by the Pollution Control Department (2020), in which consumers estimated that an average of 11 pieces per order. The researchers used the average between the minimum and the maximum as 7.5 pieces per order	7.5 pcs./order	4–11 pcs./order
	5. Proportion of people ordering food delivery in Bangkok—LINE MAN (2022) reports the provinces with the most food delivery orders. Bangkok has the most orders (3,126,074 people), accounting for 52.10%. The researcher has set the proportion of food delivery orders in the Bangkok area to be 50%	50%	45–55%
	6. Weight of plastic waste — calculated based on the assumption that 1 piece of plastic waste weighs an average of 15 g, as predicted by the pollution control department (referenced via Wongprapinkul et al., 2021b)	0.015 kg./pcs	0.0135–0.0165 kg./pcs
2) The population in Bangkok utilizing food delivery services	1. Number of people in Bangkok who ordered food delivery—LINE MAN (2022) report on the provinces with the most people ordering food delivery in 2022. The top 5 provinces are Bangkok with 3,126,074 people, Samut Prakan with 745,706 people, Chonburi with 672,210 people, Pathum Thani with 572,169 people, and Nonthaburi with 496,225 people	3,126,074 people	-	22–332	0.3–4.6
	2. Growth rate of people in Bangkok who order food delivery—the researchers set the growth rate of people in Bangkok who order food delivery at 15% per year	15%	10–20 %
	3. Based on the questionnaire survey, the average frequency of food delivery orders among residents of Bangkok is three times per week	3 times	1–7 times
	4. Amount of plastic waste—from the questionnaire survey, the average amount of plastic waste generated is equal to 6 pieces per order	6 pcs./order	4–13 pcs./order
	5. Weight of plastic waste—calculated based on the assumption that 1 piece of plastic waste weighs an average of 15 g, as predicted by the Pollution Control Department (referenced via Wongprapinkul, 2021a)	0.015 kg./pcs	0.0135–0.0165 kg./pcs
3) Data of food delivery market value	1. Food delivery market value — food delivery market value 2016–2022 (Kasikorn Research Center, 2019).	82,000 million baht in 2022	-	353 – 8,568	5.4 – 121.4
	2. Food delivery growth rate — Kasikorn research center forecasts a growth rate of 14% in 2019 compared to the previous year (Kasikorn Research Center, 2019). For 2020-2024, the researcher has set the growth rate of the food delivery business at 15%	15%	10 – 20%
	3. Average order value per time — according to the questionnaire survey, the average order value per food delivery among residents of Bangkok is 209 baht per order	209 baht/time	50 – 800 baht/time
	4. Amount of plastic waste — from the questionnaire survey, the average amount of plastic waste generated is equal to 6 pieces per order	6 pcs./order	4 – 13 pcs./order
	5. Proportion of people ordering food delivery in Bangkok — LINE MAN (2022) reports the provinces with the most food delivery orders. Bangkok has the most orders (3,126,074 people), accounting for 52.10%. The researcher has set the proportion of food delivery orders in the Bangkok area to be 50%	50%	45–55%
	6. Weight of plastic waste — calculated based on the assumption that 1 piece of plastic waste weighs an average of 15 g, as predicted by the Pollution Control Department (referenced via Wongprapinkul et al., 2021b)	0.015 kg./pcs	0.0135–0.0165 kg./pcs
4) The amount of plastic waste generated in 2020 by the Plastics Institute	1. Plastic packaging waste in 2020 — use data on the volume of food plastic packaging waste in 2020 (78,750 tons or 78,750,000 kg.), which is plastic packaging waste from the food delivery business	78,750 ton	-	-	2.6
	2. Nationwide population — nationwide population in 2021-2023 uses the data from the National Statistical Office. For 2024, the population decline rate in 2023 compared to 2022 is 0.057%	0.057%	-
	3. Population in Bangkok — population in Bangkok in 2021-2023 uses the data from the National Statistical Office. For 2024, the data from the Thailand Board of Investment (2024) was used	5,470,000 in 2024	-
	4. Number of people in Bangkok who ordered food delivery — the researchers determined that the number of people in Bangkok who ordered food delivery was 40% of the total population in Bangkok	40%	-
	5. Amount of plastic waste per person — use the plastic waste volume data (78,750 tons) divided by the total population in the country in 2022 (66,090,475 people). The amount of plastic waste is 1.19 kg/person/year	1.19 kg./person/year	-
	6. Weight of plastic waste — calculated based on the assumption that 1 piece of plastic waste weighs an average of 15 g, as predicted by the pollution control department (referenced via Wongprapinkul et al., 2021a)	0.015 kg./pcs	-

Similarly, the estimation of plastic waste in the E-commerce sector employs two primary approaches: analyzing the market value of E-commerce to project waste generation and estimating consumer participation to gauge the scale of online purchases by Thai consumers. Together, these methodologies provide a comprehensive framework for understanding the magnitude of plastic waste challenges posed by the rapid growth of the food delivery and E-commerce industries, thereby offering essential insights for developing effective and targeted waste management strategies. Two estimation methods are employed, with detailed methodologies and underlying assumptions outlined in Table 4.

Table 4.

Plastic waste estimation from E-commerce in Bangkok in 2024

Methods	Assumption detail	Key assumptions	Uncertainty	Results in 2024
Methods	Assumption detail	Key assumptions	Uncertainty	Million pcs	Million kg
1) E-commerce market value	1. E-commerce market value—E-commerce market value 2017–2021, data from electronic Transactions Development Agency or ETDA (ETDA, 2021)	4,013,399 million baht in 2021	-	909–2,573	13.3–37.7
	2. Growth rate of E-commerce business — ETDA forecasts the Compound Annual Growth Rate (CAGR) for 2017-2021 at 9.79% (ETDA, 2021). For 2022–2024, the researchers set the CAGR at 10% per year	10%	8 – 15%
	3. Order value per time—according to the questionnaire survey, the average purchase value per transaction in the e-commerce market among residents of Bangkok is 689 baht	689 baht/time	620 – 758 baht/time
	4. Amount of plastic waste—from the questionnaire survey, a minimum and maximum assessment was set, referring to the average number of purchase orders per time (2.3 orders/time) and the average amount of plastic waste per time (2-5 pieces/time: minimum is 2 pieces and maximum is 5 pieces)	2.25 pcs./order	2–5 pcs./order
	5. Proportion of E-commerce buyers in Bangkok — MarketingOops.com (2021) reported the proportion of buyers of products from Lazada in 2021, found that buyers from Bangkok and its vicinity accounted for 34% (6 provinces in Bangkok and its vicinity: Bangkok, Nakhon Pathom, Nonthaburi, Pathum Thani, Samut Prakan, and Samut Sakhon). From this information, the researcher determined the proportion of E-commerce buyers in Bangkok to be 5.67%	5.67%	5.1–6.2%
	6. Weight of plastic waste—calculated based on the assumption that 1 piece of plastic waste weighs an average of 15 g, as predicted by the Pollution Control Department (referenced via Wongprapinkul et al., 2021b)	0.015 kg/pcs	0.0135–0.0165 pcs
2) Number of Thai consumers participating in E-commerce market	1. Number of Thais who buy E-commerce products—Thai News Network or TNN predicts that the number of Thais who are familiar with buying products online in the E-commerce market in 2023 will be 40 million people (TNN, 2023)	40 million people	-	252–802	3.7–12
	2. Growth rate of Thais who purchase E-commerce products—the researchers used the number of Thais who purchased products in the E-commerce market in 2023 as the baseline for projecting the number of Thais who purchased products for 2024, assuming a growth rate of 10% per year	10%	8 – 15%
	3. Number of product orders per year—according to the questionnaire survey, the average number of product orders per year among residents of Bangkok is 58.8 times	58.8 time/year	50–70 time/year
	4. Amount of plastic waste—from the questionnaire survey, a minimum and maximum assessment was set, referring to the average number of purchase orders per time (2.3 orders/time) and the average amount of plastic waste per time (2–5 pieces/time: minimum is 2 pieces and maximum is 5 pieces)	2.25 pcs./order	2–5 pcs./order
	5. Proportion of E-commerce buyers in Bangkok—MarketingOops.com (2021) reported the proportion of buyers of products from Lazada in 2021, found that buyers from Bangkok and its vicinity accounted for 34% (6 provinces in Bangkok and its vicinity: Bangkok, Nakhon Pathom, Nonthaburi, Pathum Thani, Samut Prakan, and Samut Sakhon). From this information, the researcher determined the proportion of E-commerce buyers in Bangkok to be 5.67%	5.67%	5.1–6.2%
	6. Weight of plastic waste—calculated based on the assumption that 1 piece of plastic waste weighs an average of 15 g, as predicted by the Pollution Control Department (referenced via Wongprapinkul, 2021a)	0.015 kg/pcs	0.0135–0.0165 kg./pcs

Results and Discussions

Estimated Plastic Waste from Food Delivery and E-Commerce in Bangkok

Based on estimates derived from four calculation methods (Table 3), the amount of plastic waste generated by the food delivery sector in Bangkok in 2024 is projected to range between 22 and 8,568 million pieces per year, equivalent to approximately 0.3–121.4 million kilograms annually. Among these methods, the population-based estimation (Method (2) is considered the most plausible, yielding a range of 0.3–4.6 million kilograms. This approach combines the most recent user data from LINE MAN (2022) with behavioral insights obtained from the 2023 survey, thereby capturing current consumption patterns and providing a realistic reflection of plastic packaging waste generation in Bangkok’s food delivery industry. Unlike previous studies that relied on outdated baselines or market-value-based extrapolations—which often led to overestimations—this method offers a more balanced, evidence-based projection for 2024. For comparison, Jang et al. (2023) estimated that plastic packaging waste from food delivery services in South Korea in 2020 reached approximately 72.93 kilotons (±10.14 kt at a 95% confidence level), equivalent to 72.9 million kilograms, underscoring the scale of plastic waste associated with online food delivery systems in urban contexts.

For the e-commerce sector, the estimation of plastic waste generated in Bangkok is derived from multiple data sources, including statistical datasets and findings from the questionnaire survey conducted in this study (Table 4). The results indicate that the projected amount of plastic waste from e-commerce activities in Bangkok in 2024 ranges from 252 to 802 million pieces per year, equivalent to approximately 3.7–12 million kilograms annually. Among the four estimation methods, Method 2—the consumer number–based approach—is regarded as the most plausible for estimating e-commerce–related plastic waste in 2024. This method utilizes the most recent data on the number of online shoppers in Thailand (TNN, 2023) and integrates behavioral parameters obtained from the 2023 survey, such as purchase frequency and average packaging per order. In contrast to the market-value method, which relies on outdated economic indicators and assumes a constant proportionality between transaction value and waste generation, the consumer-based approach more accurately reflects current consumption patterns. Consequently, this method provides a realistic and behaviorally grounded estimate of packaging waste in Bangkok’s e-commerce sector. The resulting projections (3.7–12 million kilograms) correspond closely with observed consumption trends and are consistent with national estimates of plastic waste generation.

Consumer Readiness to Reduce Plastic Waste from Food Delivery and E-Commerce

An analysis of data collected from 250 consumer respondents through a questionnaire survey revealed key demographic trends and insights. The gender distribution showed that a majority of the respondents were female (52.4%), followed by males (37.2%). Regarding age groups, the largest segment (52.4%) belonged to Generation Z, comprising individuals born in 1997 or later, while Generation Y accounted for 43.6%, representing individuals aged 26–43 years (born between 1980 and 1997). The majority of consumers are university students, followed by employees in the private sector and government officials or state enterprise staff, accounting for 40.8%, 38.0%, and 11.6%, respectively. Among working-age consumers, most hold a bachelor’s degree (76.0%), followed by those with postgraduate education (13.6%). Regarding income levels, the average monthly income of most working respondents fell within the range of 15,000–25,000 Baht (20.4%), followed by 25,000–35,000 Baht (18.0%) and 35,000–45,000 Baht (16.4%). These demographic findings provide critical insights into consumer readiness to adopt sustainable practices and reduce plastic waste, particularly in the context of the food delivery and E-commerce sectors.

Readiness to reduce plastic from online Food delivery businesses in part of demand (customers), they are ready (92.4%) and can take action to reduce plastic waste by themselves. While some consumers are ready to change, they expect government agencies or stores to take the lead in driving the process. And a small number are not ready (2.4%) or are not sure (5.2%). In part of supply (entrepreneurs or food delivery platform), there is a feature to refuse plastic in the application, but only plastic cutlery. Which can be added as an option to refuse, such as plastic straws. However, in terms of reducing plastic use, most stores are not aware of waste reduction or the use of alternative packaging and reusable food containers.

For E-commerce, both the consumer and E-commerce platform perspectives, there is still a lack of readiness to reduce plastic due to concerns about product damage. This causes prefer the stores to wrap products tightly in plastic (such as plastic shockproof waste or bubble wrap) to prevent product damage and to gain consumer. The proposed solution for reducing plastic bubble wrap waste is to use alternative cushioning materials that are biodegradable and can be reused or repurposed. Natural waste materials can also be used. Platforms can add a feature in the app to allow customers to choose the type of cushioning material for their items, especially for those at risk of damage. However, it is important to communicate with the store that selling products on the platform to create a corporate culture for merchants to providing alternative cushioning materials for eco–actives, eco–considerers, and eco–dismissers.

Digimusketeers (2022) reported that 74% of Thai eco-friendly consumers choose environmentally friendly products. Mahidol University, Thailand, conducted market research on Voice of Green, focusing on 1,252 Thai eco-friendly people. It was found that 74% of consumers have the opportunity to choose products and are ready to adjust their daily behavior to be good for the environment, and 37.6% only look for Eco products and are ready to pay for such products or services.

Factors Influencing Pro-Environmental Behavior

To ensure that the factors or variables in the questionnaire, Part 3 “Pro-environmental behavior,” are reliable and valid, the reliability and validity test and the hypothesis test of the factors or variables were conducted. The factors consisted of Attitude (BH), Subjective norms (SN), Perceived behavioral controls (PBC), External factors (EF), Behavioral Intentions (BIT), and Pro-environmental behavior (PEB).

BH, SN, and PBC interact with each other and collectively shape behavioral intentions (Ajzen, 1991). Attitude refers to how favorably or unfavorably an individual evaluates a behavior. Subjective norms involve the perceived social pressure to engage in or avoid a particular behavior (Finlay et al., 2002). PBC reflects an individual’s perceived ease or difficulty in performing a behavior, often influenced by prior experiences and future expectations (Liu et al., 2007). According to TPB, behavior is influenced by both behavioral intention and PBC. While behavioral intention is the primary factor leading to behavior (Ajzen, 2002), PBC also accounts for non-volitional factors that may impact behavior (Bamberg, 2003). Therefore, intentions fully mediate the effects of attitude and subjective norms on behavior, while partially mediating the relationship between PBC and behavior (De Cannière et al., 2009).

The TPB has been widely applied across various fields, with numerous empirical studies confirming its effectiveness in predicting environmental behavior (Park & Ha, 2014; Paul et al., 2016).

Reliability and Validity

Reliability

The results of the reliability test in this study are shown in Table 5. It was found that the Cronbach’s alpha coefficient of all variables was between 0.933–0.960, which was higher than the acceptable criterion (acceptance criterion is 0.7), and the total reliability (CR) of all variables was between 0.871–0.945, which was higher than the acceptable criterion (recommended acceptance criterion is 0.7). Therefore, it was proven that the variables of the questionnaire in this study had good reliability.

Table 5.

Reliability test

Construct	Cronbach’s alpha	CR
Attitude (BH)	0.960	0.919
Subjective norms (SN)	0.942	0.871
Perceived behavioral controls (PBC)	0.940	0.917
Behavioral intentions (BIT)	0.933	0.934
Pro-environment behavior (PEB)	0.957	0.945

Validity

The convergent validity of confirmatory factor analysis (CFA) refers to the measured variables in the model effectively measuring the possible related factors. In CFA, convergent validity is an important concept used to assess the degree of relationship between the observed variables and the underlying factors used to ensure that the measured model is valid. Convergent validity is measured using factor loadings (the weight of each variable’s components to that component). The acceptable factor loading value is > 0.5 (Cheung & Wang, 2017). The results of the convergent validity test of each variable are shown in Table 6. It was found that the factor loadings of each variable were greater than 0.6, indicating the validity of the questionnaire.

Table 6.

Convergent Validity of each factor

Variables	Items	Factor Loading	AVE
Attitude (BH)	BH2	0.753	0.694
	BH4	0.850
	BH6	0.862
	BH8	0.855
	BH10	0.841
Subjective norms (SN)	SN1	0.854	0.692
	SN3	0.796
	SN5	0.844
Perceived behavioral controls (PBC)	PBC1	0.753	0.689
	PBC2	0.866
	PBC4	0.823
	PBC6	0.850
	PBC7	0.852
External factors (EF)	EF1	0.878	0.725
	EF2	0.830
	EF3	0.881
	EF4	0.816
Behavioral intentions (BIT)	BIT1	0.926	0.824
	BIT2	0.905
	BIT3	0.892
Pro-environment behavior (PEB)	PEB1	0.831	0.712
	PEB3	0.832
	PEB4	0.782
	PEB5	0.868
	PEB6	0.821
	PEB8	0.884
	PEB9	0.884

In this study, the discriminant validity was tested by calculating the square root of the average variance extracted (AVE) of the variables. If the result of the studied variable has a higher correlation coefficient than all other variables, it indicates that the variable in the questionnaire has good discriminant validity. The results of the discriminant validity test in this study are shown in Table 7. It was found that the square root of the AVE of all variables is higher than the correlation coefficient with other variables. Therefore, each variable in this study has good discriminant validity.

Table 7.

Correlations and Average Variance Extracted (AVE)

	BH	SN	PBC	EF	BIT	PEB
BH	0.833	-	-	-	-	-
SN	.699***	0.832	-	-	-	-
PBC	.746***	.752***	0.830	-	-	-
EF	.642***	.658***	.642***	0.852	-
BIT	.653***	.707***	.798***	.651***	0.908	-
PEB	.711***	.741***	.838***	.714***	.836***	0.844

Note. Attitude (BH), Subjective norms (SN), Perceived behavioral controls (PBC), External factors (EF), Behavioral Intentions (BIT), and Pro-environmental behavior (PEB), ***p<0.000.

Model Fit

We calculated seven fit indices to determine how the model fitted our data (Table 8). The x2/df values less than 5 indicate a good fit. For the Goodness of Fit Index (GFI) and Adjusted Goodness of Fit Index (AGFI), values greater than 0.8 represent a good model fit. For the Tucker–Lewis’s index (TLI) and comparative fit index (CFI), values greater than 0.9 represent a good model fit, and for the root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR), values less than 0.08 indicate a good model fit.

Table 8.

Model Fit Indices

	χ2/df	GFI	AGFI	TLI	CFI	RMR	RMSEA
Value	3.171	0.843	0.803	0.926	0.935	0.035	0.075
Standard	<5	>0.8	>0.8	>0.9	>0.9	<0.08	<0.08

Control Variables

The results from the model that included control variables indicated no significant effects. Therefore, these control variables were excluded from the final hypothesis testing (Table 9).

Table 9.

Control Variables

	Estimate	S.E.	C.R.	P-value
PEB <-- gender	−0.086	0.039	−2.201	0.028
PEB <-- age	−0.063	0.059	−1.056	0.291
PEB <-- Status	−0.072	0.047	−1.54	0.124
PEB <-- education	0.004	0.04	0.102	0.919
PEB <-- Salary	0.026	0.022	1.164	0.244

R-Squared

R-squared is a statistical measure that quantifies the proportion of variance in the dependent variable that is explained by the independent variables. In this study, the R-squared value for behavioral intention is 0.758, indicating that 75.8% of the variance in behavioral intention is explained by the three variables: personal attitude, subjective norm, and perceived behavioral control. Similarly, the R-squared value for pro-environmental behavior is 0.872, signifying that 87.2% of the variance in pro-environmental behavior can be explained by the combined effects of personal attitude, subjective norm, perceived behavioral control, and behavioral intention.

The variables (factors) of the questionnaire in this study had good reliability and validity. In addition, the factors are affecting Pro-Environmental Behavior for the readiness to reduce plastic waste from the Food delivery and E-commerce (Figure 2).

Hypothesis Test

The direct path analysis results as shown in Table 10. The study found that BH had no significant effect on behavioral intention (coefficient = −0.057, p = 0.428). However, SN (coefficient = 0.238, p = 0.009) and PBC (coefficient = 0.705, p = 0.000) showed significant positive influences on BIT, indicating that social pressures and confidence in control play important roles in shaping participants’ willingness to engage in specific behaviors. BIT was significantly related to PEB (coefficient = 0.428, p = 0.000), and perceived behavioral control had a similarly strong influence on PEB (coefficient = 0.539, p = 0.000), suggesting that both intention and control perceptions are key factors in actual engagement in such behaviors.

Table 10.

SEM Path Estimate Summary

Relationship	Estimate	P-value	Results
Attitude (BH) -> behavioral intentions (BIT)	−0.057	0.428	Rejected
Subjective norms (SN) -> behavioral intentions (BIT)	0.238	0.009	Supported
Perceived behavioral controls (PBC) -> behavioral intentions (BIT)	0.705	0.000	Supported
Behavioral intentions (BIT) -> pro-environment behavior (PEB)	0.428	0.000	Supported
Perceived behavioral controls (PBC) -> pro-environment behavior (PEB)	0.539	0.000	Supported

According to TPB theory, behavioral intention (BIT) is determined by BH, SN, and PBC. However, in this study, the results deviated from the general pattern of TPB, with BH being insignificant, while subjective norms and perceived behavioral control were significant predictors. There are several reasons why attitudes did not emerge as a significant predictor, while SN and PBC were more influential. (1) Attitude-Behavior Gap: Even if people have positive attitudes or support for pro-environmental behaviors, when faced with obstacles (e.g., lack of choice/inconvenience, budget, and concerns about product damage), they may not demonstrate actual intention or behavior. Several studies have discussed the “value-action gap,” such as lack of cost, time, structural/institutional, facilities, convenience, and logistic (Chung & Leung, 2007; Kaaronen, 2017; Vieira et al., 2023). (2) The Prominent Role of PBC: When individuals feel they have the “ability,” “resources,” or “opportunity” to perform a behavior (high PBC), the effect of attitude may be “overridden” by control perceptions or even SN (Barbera & Ajzen, 2020). (3) Social Context: In the Bangkok metropolitan area, People experience high social pressure or SN, or a culture that places a high value on what others expect, which may lead to SN being more influential than personal attitudes. (4) Attitude Definition or Measurement: There may be measurement issues, or individuals may have positive attitudes but do not perceive the behavior as easy or practical (which is related to PBC). Some research has found that when PBC is high, the effect of attitude on intention is greater, while when PBC is low, the effect of SN may be greater (Barbera & Ajzen, 2020).

Study Limitations

This study has a few limitations. First, the estimation model is based on a limited sample size and several assumptions representing the population of Bangkok, which may not fully capture the diversity of consumer behaviors. The majority of respondents were university students, followed by employees in the private sector and government officials or state enterprise staff, accounting for 40.8%, 38.0%, and 11.6%, respectively. Among working-age consumers, most held a bachelor’s degree (76.0%), followed by those with postgraduate education (13.6%). However, in the pro-environmental behavior model, all control variables—such as age and education—were found to be statistically insignificant. Second, some parameters were derived from secondary data, which may introduce uncertainty; nonetheless, multiple estimation methods were compared to enhance the robustness of the results. Third, as the survey was self-administered, some responses may have lacked precision. To mitigate this limitation, the findings were cross-checked with existing literature and validated through comparative reference analysis.

Conclusions

The volume of plastic waste from Food delivery businesses in Bangkok is expected to be between 22 to 8,568 million pieces per year, or 0.3 to 121.4 million kilograms per year, in 2024 (with the best estimate ranges from 0.3–4.6 million kilograms or approximately 0.05-0.84 kg/person from food delivery) population in Bangkok is 5.46 million in 2024. For E-commerce businesses, the estimated plastic waste is between 252 to 802 million pieces per year, or approximately 3.7 to 12 million kilograms per year (approximately 0.7–2.2 kg/person from E-commerce), with a trend of increasing in the future.

Consumer readiness to reduce plastic waste from food delivery indicates that most individuals are willing and able to take action independently. However, some expect leadership or guidance from government agencies and businesses, while a smaller group remains unprepared or uncertain about effective ways to reduce plastic use. From the perspective of business operators (Food delivery platform providers), there is an option in the app to refuse plastic, but it currently only applies to plastic cutlery. Overall, most businesses do not recognize the need to reduce waste or use alternative packaging and reusable food containers. Readiness to reduce plastic waste from E-commerce is seen as being much farther from the level achieved in Food delivery businesses. This is due to concerns about product damage. The proposed solution for reducing plastic bubble wrap waste is to use alternative cushioning materials that are biodegradable and can be reused or repurposed. Natural waste materials can also be used. Platforms can add a feature in the app to allow customers to choose the type of cushioning material for their items, especially for those at risk of damage.

Policy Recommendations

To bridge the gap between Thailand’s national action plans and public behavior in plastic waste management, integrated policy actions are needed. The government should collaborate with digital platforms and packaging manufacturers to promote alternative and reusable packaging, reducing reliance on single-use plastics. Joint campaigns among government, private sectors, and academia should strengthen public awareness of environmental and health impacts, proper waste segregation, and recycling. Delivery platforms should expand options for declining single-use items (e.g., straws and condiment sachets) and improve coordination with restaurants to ensure compliance. Multi-stakeholder collaboration—engaging government, businesses, communities, and civil society—is essential to design programs that encourage reusable systems and community-based recycling. Such cooperation fosters engagement, shared responsibility, and sustainable consumption. Ultimately, bridging the behavioral gap requires structural and social innovation through technology, effective communication, and inclusive governance to advance Thailand’s transition toward a circular plastic economy and sustainable waste management.

Footnotes

ORCID iD

Aweewan Panyagometh

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is supported by Thailand Science Research and Innovation (TSRI) grant number 4695431.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Author Biography

Associate Professor Dr. Aweewan Panyagometh received a bachelor ’s in environmental science from Mahidol University; Master of Science in Hazardous Waste Management from Chulalongkorn University; Master of Science in Environmental Science and Management from Carnegie Mellon University, USA and joint PhD in Engineering and Public Policy as well as Environmental Science and Management from Carnegie Mellon University, USA. Her expertises is in quantitative policy analysis, environmental policy, life-cycle assessment, and risk communication.

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