Using Community-Based Social Marketing to Promote Pro-Environmental Behavior in Municipal Solid Waste Management: Evidence from Norte de Santander, Colombia

Abstract

The sustainable management of Municipal Solid Waste (MSW) relies heavily on community participation in separating it at the source and delivering it to collection systems. These practices are crucial for reducing pollution, protecting ecosystems, and maximizing resource recovery. However, in the Global South context, with conditions of socioeconomic vulnerability, community participation in the sustainable management of MSW remains limited, highlighting the need to generate context-specific interventions. MSW includes items such as household appliances, batteries, and electronic devices, which require specialized handling due to their size, hazardous components, or material complexity. This study implemented a Community-Based Social Marketing approach during the research and design phases of an intervention focused on promoting source separation and management of hard-to-manage MSW in five municipalities within the administrative region of Norte de Santander (Colombia), which borders Venezuela. Using a mixed-methods approach, we collected data from 1775 individuals (63.83% women; M _age = 33.48 years; SD = 17.25), employing social mapping, focus groups, semi-structured interviews, participant observation, and a survey questionnaire. The results show that the source separation and delivery of hard-to-manage MSW to collection systems are limited by a set of psychosocial, structural, and institutional barriers that interact with each other, affecting communities’ willingness and capacity for action. Furthermore, a prediction model of willingness to engage in separation and delivery behaviors showed a good fit (R2 = 0.83). The strongest predictors were awareness of the negative consequences of non-participation and perceived environmental benefits, with subjective norms contributing to a lesser extent. Based on these results, we designed a context-specific intervention focused on reducing these barriers and promoting community engagement in the sustainable management of hard-to-manage MSW.

1. Introduction

“Every year across the globe more than two billion tonnes of municipal solid waste is generated” [1].

One of the most pressing environmental challenges of the 21st century is the increase in Municipal Solid Waste (MSW) generated by the lifestyles and consumption practices of contemporary societies [1,2]. MSW management is a complex, multi-stage system encompassing waste generation, source separation, collection, transportation, treatment, recovery, recycling, and final disposal. Each stage presents unique operational, logistical, and social challenges that impact the overall efficiency and sustainability of the system [3,4]. Traditional methods, such as curbside collection and landfill disposal, remain widespread but face increasing criticism due to their environmental and social drawbacks, including pollution, greenhouse gas emissions, and limited resource recovery [5,6]. Inadequate MSW management not only contributes to the pollution of air, soil, and water but also affects health, degrades ecosystems, and deepens social inequalities, especially in vulnerable communities [1,7,8].

The sustainable management of MSW is therefore essential to mitigate environmental damage and move towards a circular economy [9]. This economic model proposes replacing the linear “extract, produce, and dispose” approach with one based on reducing, reusing, recycling, and extending the life cycle of products, aiming to optimize resource use and minimize waste generation [10]. Furthermore, the sustainable management of MSW aligns with the fulfillment of the Sustainable Development Goals (SDGs), in particular SDG 11, which seeks to promote more inclusive, safer, and sustainable cities, and SDG 12, which aims to encourage responsible production and consumption patterns [11,12].

However, sustainable MSW management relies heavily on citizen participation in practices such as source separation and delivery of MSW to collection systems [12,13]. This is especially relevant for hard-to-manage MSW, such as household appliances, batteries, and electronic devices. These materials are considered hard-to-manage because of their physical size, chemical composition, or material complexity, which makes them incompatible with conventional municipal collection, transportation, and disposal systems. For example, batteries often contain hazardous substances like lithium or nickel; electronic devices combine heavy metals, plastics, and circuit boards that require specialized handling; and large appliances can be bulky and contain refrigerants or e-waste components. Instead of standard treatment, these waste streams require dedicated infrastructure and specialized processes that enable the recovery of valuable materials while minimizing environmental and public health risks and avoiding damage to the collection and waste management infrastructure [13,14,15].

The sustainable management of hard-to-manage MSW requires a greater citizen effort to separate it at the source and deliver it to collection systems. Citizen participation is essential to reduce the volume of MSW sent to landfills, increase the efficiency of management systems, and facilitate the recovery of valuable materials. Lack of citizen engagement, on the other hand, leads to the mixing and contamination of MSW, the waste of usable resources, and damage to ecosystems [13,14].

Therefore, in addition to advances in technical infrastructure, MSW management systems should integrate strategies aimed at changing behavior and promoting pro-environmental habits in communities that align with the principles of the circular economy [10].

The Community-Based Social Marketing (CBSM) approach, which integrates insights from social sciences and psychology with principles of social marketing, has demonstrated efficacy in enhancing citizen participation in pro-environmental initiatives [16]. Unlike other approaches, CBSM recognizes that pro-environmental behaviors are often conditioned by barriers [17,18,19,20] and considers communities as active agents of social transformation (and not only as recipients of interventions). Therefore, it is crucial to commence with an analysis of barriers within the context of the interventions and involving communities in their design and implementation, as this enhances the probability that they will be relevant, efficient and sustainable, because they are adapted to the specific needs and priorities of the communities [16,20,21].

The CBSM framework has five distinct stages: (1) selection of pro-environmental behaviors for promotion—in this research, source separation and delivery of hard-to-manage MSW to collection systems; (2) identification of barriers; (3) development of intervention strategies for behavioral modification; (4) pilot testing the intervention; and (5) implementation and large-scale evaluation [17,18].

We propose that in the second stage of CBSM, in addition to identifying barriers to the adoption of pro-environmental practices, it is important to analyze the key determinants of the behavior to be promoted in the context of intervention [22]. To this end, it is also relevant to identify the competing behaviors to be discouraged, the attribution of responsibility that communities have regarding who should act on the environmental problem, and the willingness toward the behaviors to be promoted. Hence, we propose calling the second stage the identification of barriers and determinants of pro-environmental behavior.

In this article we present the application of the CBSM approach in the stages of identifying key barriers and determinants and designing the intervention to promote source separation and delivery of hard-to-manage MSW to collection systems in five municipalities in the administrative region of Norte de Santander (Colombia), a region historically marked by conditions of sociopolitical violence, socioeconomic vulnerability, and sustainability challenges [23,24,25].

1.1. Barriers, Competing Behaviors, and Responsibility Attribution in Relation to Source Separation and Delivery of MSW

Designing effective interventions to encourage pro-environmental behavior requires understanding the reasons that hinder its adoption [26]. As McKenzie-Mohr [17,18] suggests, it is difficult, if not impossible, to promote behavioral changes without first identifying the barriers that hinder them. These barriers can be grouped into two main categories: psychosocial (or internal) and structural and institutional (or external). Psychosocial barriers refer to personal and social factors, such as beliefs, perceptions, emotions, norms, and group dynamics, which limit or prevent the implementation of pro-environmental behavior. In contrast, structural and institutional barriers include material limitations, such as the absence of containers for differentiated delivery, and organizational limitations, such as deficiencies in collection processes or in the implementation of regulations, which hinder pro-environmental actions even among those who intend to do so [10,17,26,27,28].

In addition to these barriers, it is important to analyze competitive behaviors, which are understood as the habits that people typically exhibit in relation to environmental issues [20,29]. Examples of these competitive behaviors in relation to MSW management include undifferentiated delivery or informal disposal. These habits, when operating automatically, can neutralize both the knowledge and the intention to act in a pro-environmental manner. Therefore, identifying them is key to designing strategies that not only encourage new behaviors but also discourage those that hinder sustainable MSW management [29].

Another factor that also influences the adoption of pro-environmental behaviors is the attribution of responsibility. Citizens’ perceptions of who should be responsible for solving environmental problems—whether governments, companies, or the community itself—determine the degree of individual involvement. Previous studies have demonstrated that attributions of responsibilities perceived as diffuse or unfair can reduce motivation to act. Conversely, when people recognize themselves as part of the problem and its solution, they tend to show greater commitment to adopting pro-environmental behaviors [16,30]. Therefore, understanding who is attributed responsibility for the environmental problem (in this case, MSW management) is relevant in designing interventions aimed at bringing about behavioral change.

1.2. Willingness to Source Separation and Delivery of MSW

Identifying the factors that determine the willingness to adopt pro-environmental behaviors is also critical for designing effective interventions to promote their adoption. Previous studies have identified several relevant predictors of pro-environmental behaviors, including awareness of the negative consequences of not acting pro-environmentally, perceived benefits, and subjective norms [9,13,14].

First, the awareness of the negative consequences of not acting pro-environmentally (in this case not separating MSW at the source or not delivering it to collection systems), refers to the degree to which people understand the environmental and public health impacts associated with inaction. This awareness can function as a moral motivator by highlighting individual responsibility for collective problems, such as pollution or landfill saturation [9,13,14].

Second, the perception of environmental or economic benefits can increase the willingness to act. Environmental benefits are linked to the protection of ecosystems, while economic benefits can include tangible incentives such as discounts, bonuses, or savings from material recovery. Perceiving that pro-environmental behaviors generate concrete, favorable outcomes strengthens the willingness to engage in them [13,14].

Finally, the subjective norm, understood as the perception that significant others (e.g., family members, neighbors, or community members) value or expect certain behaviors, increases the likelihood of engaging in that behavior. A strong subjective norm supporting pro-environmental practices can increase participation through social pressure or the desire to belong to a group with shared values [13,14,31].

Based on this background, we propose an explanatory model in which awareness of the negative consequences of not separating at the source and delivering MSW to collection systems, the perception of benefits of doing so, and the associated subjective norm act as joint predictors of the willingness to engage in these behaviors.

1.3. Research Context and Aims

Colombia generates approximately 12 million tons of MSW annually, a moderate figure compared to more densely populated or higher-income countries [2,32]. However, management systems have significant deficiencies as 96.67% of collected MSW is disposed of in landfills, of which around 40% are expected to reach maximum capacity in less than three years [32].

These limitations are further exacerbated by significant regional disparities within the country. The administrative region of Norte de Santander, located on the border with Venezuela, clearly illustrates these inequalities. This region has been historically impacted by armed conflict, presents high levels of human mobility (particularly due to migratory flows, forced displacement, and returns), and has some deficiencies in infrastructure and provision of basic services [23,24,25].

Although the region accounts for approximately 3.6% of the national population [33], it contributes only 1.52% of the total MSW managed in the country. This discrepancy suggests that the region manages substantially less waste than would be expected based on its population share. Such a gap cannot be solely attributed to lower waste generation per capita and instead likely reflects significant limitations in formal waste collection coverage, infrastructure, and data reporting. In many areas, especially those with informal settlements or limited municipal capacity, waste may be disposed of through informal means—such as open dumping, burning, or unreported self-management—rather than entering the formal collection system. This underperformance highlights the structural challenges faced by vulnerable regions like Norte de Santander in achieving equitable and effective MSW management.

The situation becomes even more critical in relation to the management of hard-to-manage MSW, such as tires, household appliances, batteries, household insecticides, computers, and peripherals, which is of particular concern. These MSW types have been identified locally as those with the lowest collection rates and those most frequently discarded in unregulated spaces.

Given this situation and considering that effective interventions require contextualized, inclusive, and community-centered approaches, we set out to investigate the factors that limit or could enhance citizen participation in source separation practices and delivery of tires, household appliances, batteries, household insecticides, computers, and peripherals (hereinafter referred to as hard-to-manage MSW) to collection systems in the administrative region of Norte de Santander.

We established two primary objectives. First, to identify barriers, existing management habits of hard-to-manage MSW (including competitive behaviors), and associated responsibility attributions. Second, to test an explanatory model wherein awareness of the negative effects of failing to separate at the source and deliver MSW to collection systems, the perceived benefits of such actions, and the associated subjective norm collectively predict the willingness to engage in these behaviors.

Based on the results obtained, we developed an intervention proposal to promote pro-environmental behaviors of source separation and delivery of hard-to-manage MSW to collection systems through low-cost strategies adapted to community dynamics in five municipalities in the administrative region of Norte de Santander, Colombia.

Our findings and proposed intervention offer a novel and potentially scalable framework for promoting pro-environmental behaviors in socioeconomically vulnerable contexts. Beyond the specific case study, this research contributes to the broader literature by extending the CBSM approach. We highlight the importance of identifying not only barriers to the adoption of target behaviors but also other key behavioral determinants. These include discouraging competing behaviors, identifying the attribution of responsibility for addressing the environmental issue, and assessing the community’s willingness to adopt pro-environmental practices. Our results provide empirical evidence supporting the relevance of integrating these factors into intervention design, offering a context-sensitive strategy that can inform similar efforts in other contexts.

2. Methodology

We conducted our study using a concurrent mixed-methods design, which allowed us to collect both qualitative and quantitative data. To collect qualitative data, we used social mapping, semi-structured interviews, focus groups, and participant observation techniques. To collect quantitative data, we used a survey-style questionnaire. The combination of these methodologies sought to strengthen the study’s validity [31]. The research was approved by the Institutional Bioethics Committee of Fundaciȯn Universitaria Konrad Lorenz.

2.1. Participants

Data collection was conducted between March and October 2023 in five municipalities within the Norte de Santander administrative region, Colombia: Cúcuta, Los Patios, Villa del Rosario, San Cayetano, and El Zulia. These municipalities account for approximately 63% of the region’s total population [34]. While Cúcuta, Los Patios, and Villa del Rosario are primarily urban, San Cayetano and El Zulia are predominantly rural.

We employed a snowball sampling strategy to contact participants due to the insecurity and difficult access to some locations in the administrative region of Norte de Santander, which made it challenging to implement a probability sampling strategy.

To contact and recruit participants, we established contact with both private and public educational institutions, as well as with local businesses, environmental leaders, community leaders, and public officials.

The participants comprised 1775 residents (63.83% women, M _age = 33.48 years, SD _age = 17.25) from the five municipalities: Cúcuta (39.27%), El Zulia (15.44%), Los Patios (17.07%), San Cayetano (9.12%), and Villa del Rosario (19.10%). For a more detailed analysis of the sample’s sociodemographic characteristics, see

Table 1. Sociodemographic characterization of the sample across municipalities.

Municipality	Participants	% Participants Municipality	Average Age (SD)	Gender
Cúcuta	697	39.27	31.42 (14.62)	Female	399
				Male	296
				Other	2
Zulia	274	15.44	37.22 (16.98)	Female	186
				Male	88
Los Patios	303	17.07	39.01 (21.14)	Female	202
				Male	101
Saint Cajetan	162	9.12	33.41 (17.91)	Female	95
				Male	67
Villa del Rosario	339	19.10	37.22 (16.98)	Female	251
				Male	88
Total	1775	100	33.48 (17.25)	Female	1133
				Male	640
				Other	2

and Appendix A in the Supplementary Material.

2.2. Data Collection Process

Before beginning data collection, participants were informed of the study’s purpose, the confidentiality and anonymity policies for their responses, and the data protection measures. To ensure their understanding and consent, they were asked to sign an informed consent form, as well as an informed assent form for minors, which also included authorization for audio recording and photography. This confirmed their voluntary participation in the study.

Once the informed consent form was signed, and in the case of minors, the informed assent, participants completed a questionnaire that included items on sociodemographic characteristics and variables related to the source separation and delivery of MSW to collection systems. To measure these latter variables, 13 five-point Likert-type items were used, with responses ranging from 1 (strongly disagree) to 5 (strongly agree). These items asked about: awareness of the negative consequences of not separating and delivering MSW; perceptions of both economic and environmental benefits of such actions; subjective norms regarding these practices within their reference groups (family, neighbors, and social organizations); and willingness toward these practices. The exact wording of the items can be found in Appendix B of the Supplementary Material.

Each participant was then assigned to one of four qualitative data collection techniques aimed at exploring perceived barriers, everyday practices, and opinions related to the management of hard-to-manage MSW. Social mapping sessions (36 sessions, involving 352 participants) consisted of group discussions and the collaborative development of maps to identify commonly used delivery sites and propose locations for infrastructure, such as designated collection points. Focus groups (90 sessions; 973 participants) facilitated collective dialog about shared experiences, practices, opinions, and perceived barriers. Semi-structured interviews (375 interviews), conducted individually, enabled an in-depth exploration of personal experiences, practices, opinions, and perceived barriers. Finally, participant observations (72 sessions) were conducted in households, schools, and small businesses, enabling researchers to directly document daily separation and delivery routines and collect opinions and perceived barriers expressed by participants. The protocol for each technique can be found in Appendix C of the Supplementary Material.

The qualitative techniques application sessions, excluding participant observations, were recorded and automatically transcribed using Amberscript Global B.V software program (2024, Online). Subsequently, we manually edited and corrected the transcripts to adjust punctuation, syntax, and to distinguish between the interventions of participants and researchers (see Appendix D in the Supplementary Material for the transcription protocol). Furthermore, we digitized the registration forms associated with the participant observation technique. Due to issues with the audio recording of one interview and the legibility of two observation registration forms, the data from three participants were excluded from the qualitative data analysis.

2.3. Data Analysis Process

Based on the transcripts from the qualitative data collection sessions and the participant observation records, we conducted a qualitative thematic analysis following the approach proposed by Braun and Clarke [35]. With the support of seven research assistants, we developed and applied a coding system. The thematic analysis was carried out using ATLAS.ti software (version 23).

During the coding process, theoretical saturation was reached in four analytical categories [36]; that is, as new data were added, no additional relevant codes or themes emerged. This saturation was verified through triangulation of results obtained from the four qualitative data collection techniques employed. The coding protocol is available in Appendix E of the Supplementary Material.

Using the questionnaire data, we applied Structural Equation Modeling (SEM) to test the proposed explanatory model. To evaluate model fit, we referred to the following cutoff values: 0.95 for the Comparative Fit Index (CFI) and Tucker–Lewis Index (TLI), 0.06 for the Root Mean Square Error of Approximation (RMSEA), and 0.08 for the Standardized Root Mean Squared Residual (SRMR) [37]. The model was estimated using version 0.6-18 of the Lavaan package in R. Prior to running the SEM, we conducted internal consistency analyses, descriptive statistics, and comparisons across municipalities and area types (urban vs. rural).

3. Results

3.1. Barriers, Competing Behaviors, and Responsibility Attribution in Relation to Source Separation and Delivery of MSW

Below, we present the results of the qualitative thematic analysis, based on four categories: (1) psychosocial barriers; (2) structural and institutional barriers; (3) hard-to-manage MSW management practices; and (4) attributions of responsibility (see

Table 2. Summary of the thematic analysis.

Category	Subcategory	Code	Frequency of Code
			Social Mapping Sessions (n = 36)	Focus Groups (n = 90)	Semi-Structured Interviews (n = 375)	Participant Observations (n = 72)	Total
Psychosocial barriers: references to personal and social factors reported by participants that hinder their engagement in or commitment to pro-environmental behaviors related to hard-to-manage MSW management.	Limited knowledge and awareness	Lack of awareness of the MSW problem	10	100	250	20	380
		Lack of knowledge of sustainable MSW management	5	57	210	58	330
		Lack of interest in the useful life cycle of products		33	150		183
		Lack of awareness about the positive impact of post-consumption MSW management		29	99	7	135
		Perceived low environmental and public health benefits of MSW		6	35	11	52
		Lack of environmental awareness related to consumer habits	1	11	35	2	49
	Negative perceptions and resistance to change	Negative perception of MSW management systems	4	81	160	2	247
		Perception of convenience of unsorted MSW disposal		30	49	6	85
		Resistance to change	2	25	42	1	70
		Abandonment of programs regarding MSW management	1	21	30	4	56
		Lack of motivation to participate in MSW management activities		9	33	7	49
Structural and institutional barriers to MSW management: references to infrastructural limitations, organizational capacity constraints, and policy or regulatory gaps that impede the effective implementation and operation of hard-to-manage MSW programs.	Institutional shortcomings	Lack of MSW management and awareness programs	4	61	113	27	205
		Poor communication of MSW initiatives	3	29	62	20	114
		Deficiencies in the implementation of environmental regulations	1	13	13	2	29
	Infrastructural limitations	Insufficient MSW collection bins	3	35	63	37	137
		Failures in MSW collection services	1	41	41	15	98
	Inequities in information and training access	Unequal access to environmental management training		4	8	1	13
		Digital divide and limited access to information channels		4	8		12
Hard-to-manage MSW management practices: references to behaviors observed or reported by participants concerning the routine handling of hard-to-manage MSW in household or community contexts.	MSW competitive behaviors	Undifferentiated delivery of hard-to-manage MSW	2	148	386	52	588
		Accumulation and temporary storage of hard-to-manage MSW	1	104	185	75	365
		Practices with a direct negative impact on the environment and public health	7	120	137	3	267
	Pro-environmental behaviors	Separation at source and delivery of hard-to-manage MSW to collection systems	3	106	214	92	415
		Separation at source of hard-to-manage MSW		19	53	5	77
	Community practices	Reuse of hard-to-manage MSW	3	196	162	29	390
		Delegation of hard-to-manage MSW management to third parties	2	41	127	37	207
		Informal disassembly behaviors for repurposing and resale	2	66	108	19	195
Attribution of responsibility in MSW management: references to participant perceptions regarding which actors should assume primary responsibility or leadership in hard-to-manage MSW management.		Institutional and governmental responsibility	21	136	315	14	486
		Personal responsibility	5	130	313	1	449
		Corporate responsibility	12	99	195	3	309

). The subcategories and codes were not pre-established; rather, they emerged inductively from participants’ opinions, perceptions, experiences, and habits related to hard-to-manage MSW. The total frequency of each code—calculated by integrating the application of the code to the transcripts and registration forms of the four qualitative techniques employed—is indicated in parentheses. Although the emphasis during data collection was on hard-to-manage MSW, participants often referred to all types of MSW when commenting on barriers, hard-to-manage MSW management practices, and attributions of responsibility.

3.1.1. Psychosocial Barriers

We identified two subcategories of psychosocial barriers: (a) lack of knowledge and/or awareness and (b) negative perception and resistance to change.

Regarding the limited knowledge and awareness, many participants expressed that they do not perceive MSW management as a relevant problem in their municipalities, or they indicated that, although they recognize associated negative consequences, they believe that the majority of the community does not share this perception (f = 380). They also reported having limited knowledge about sustainable MSW management practices in their municipalities (f = 330), little awareness about its potential benefits (f = 135), and a low perception of positive impacts on the environment and public health associated with sustainable MSW management (f = 52). Some participants expressed disinterest or indifference towards the life cycle of the products they consume (f = 183), as well as a lack of awareness about the impact of their consumption habits (f = 49).

Regarding the subcategory of negative perceptions and resistance to change, participants expressed a negative view of the MSW management systems in their municipalities (f = 247), mainly due to previous experiences of failures in implementing initiatives. Some participants acknowledged having abandoned management programs (f = 56) or claimed to have little motivation to participate in related activities (f = 49). Furthermore, some pointed out that delivering MSW without source separation is more convenient (f = 85) and that attempts to promote pro-environmental behaviors for MSW management are likely to face social resistance in their municipalities (f = 70).

3.1.2. Structural and Institutional Barriers

We identified three subcategories of structural and institutional barriers: (a) institutional shortcomings, (b) infrastructure limitations, and (c) inequalities in information and training access.

Regarding institutional shortcomings, participants mentioned the limited presence of municipal programs focused on sustainable MSW management, particularly in terms of awareness-raising strategies (f = 205). They also mentioned limited communication about the objectives, functioning, and benefits of existing initiatives (f = 114), as well as the omission or inconsistency in the effective application of environmental regulations (f = 29).

Regarding infrastructure limitations, both the lack of containers for differentiated MSW delivery (f = 137) and failures in the collection service (f = 98) were identified as conditions that hinder or discourage participation in sustainable MSW management.

Finally, regarding inequities in access to information and training, some participants highlighted a lack of training strategies tailored to specific groups, such as rural communities and older adults (f = 13), as well as poor internet connectivity and low digital literacy (f = 12).

3.1.3. MSW Management Practices

We identified three types of management practices for hard-to-manage MSW: (a) competitive behaviors, (b) pro-environmental behaviors, and (c) community practices.

Competitive behaviors—those that must be discouraged to achieve sustainable management of the hard-to-manage MSW—were the most frequently reported and observed. The most common was the undifferentiated delivery of hard-to-manage MSW (f = 588), followed by stockpiling and temporary storage in homes (f = 365). Practices with direct negative effects on the environment and public health, such as disposing of MSW near rivers, burning, or burying it, were also identified (f = 267).

Second, we also identified pro-environmental behaviors that contribute to the sustainable management of hard-to-manage MSW. Several participants reported and were observed separating at source and delivering this MSW to formal collection systems (f = 415). Some participants also perform source separation but do not necessarily complement this practice with subsequent differentiated delivery (f = 77).

Finally, we identified three community practices for managing hard-to-manage MSW. The first involves reusing salvageable materials or converting MSW into new products, such as making handicrafts from tires (f = 390). The second focuses on delegating MSW management to third parties, such as informal recyclers, scrap metal dealers, or local businesses (f = 207). The third involves disassembling or reusing some of the hard-to-manage MSW components, such as household appliances or computers, to obtain a financial return (f = 195).

3.1.4. Attribution of Responsibility

Participants attributed responsibility for managing hard-to-manage MSW to three main actors. First, they identified public institutions and local governments as responsible for leading and ensuring effective management systems (f = 486). Second, they recognized individual responsibility, emphasizing the role of each person in adopting pro-environmental behaviors that contribute to pro-environmental management (f = 449). Finally, they identified the business sector as co-responsible (f = 309), referring to both the actors involved in the direct management of MSW and the productive sectors.

3.2. Willingness to Source Separation and Delivery of MSW

Before estimating the explanatory model for willingness to engage in source separation and the delivery of MSW to collection systems, we compared the results across municipalities and by their classification as urban or rural. Except for the subjective norm variable, no statistically significant differences were found. However, the effect sizes for the differences in subjective norm between municipalities and territory types were small (see Appendix F in the Supplementary Material). Therefore, the analyses were conducted on the total sample without distinction by municipality or territory type (see

Table 3. Descriptive statistics of variables related to willingness to source separation and delivery of MSW.

Municipalities	Awareness About the Negative Consequences		Perception of Economic Benefits		Perception of Environmental Benefits		Subjective Norm		Willingness
	M	SD	M	SD	M	SD	M	SD	M	SD
Cúcuta	4.39	1.07	3.40	1.27	4.36	1.12	3.31	1.13	4.39	1.05
El Zulia	4.31	0.97	3.32	1.12	4.33	0.99	3.41	1.02	4.40	0.96
Los Patios	4.36	0.98	3.33	1.19	4.35	1.04	3.16	1.1	4.39	0.99
San Cayetano	4.45	0.93	3.48	1.11	4.45	0.93	3.44	1.06	4.46	0.94
Villa del Rosario	4.48	0.82	3.51	1.21	4.49	0.86	3.42	1.04	4.50	0.83
General	4.40	0.99	3.40	1.21	4.38	1.02	3.33	1.09	4.42	0.98

Note. A total of 1766 participants responded to the quantitative questionnaire.

).

Participants reported a high awareness of the negative consequences of not separating and delivering MSW to collection systems, both for the environment and for their health and that of their families (M = 4.40, SD = 0.99; α = 0.90, ω = 0.90), as well as a high perception of environmental benefits from performing these behaviors (M = 4.38, SD = 1.02; α = 0.90).

In contrast, the perception of associated economic benefits was moderate (M = 3.40, SD = 1.21; α = 0.58), as was the subjective norm—the perception of social support received from family members, neighbors, and organizations to carry out these practices (M = 3.33, SD = 1.09; α = 0.75, ω = 0.76). Finally, participants expressed a favorable willingness toward source separation and delivery of MSW, with high scores on usefulness, necessity, and interest (M = 4.42, SD = 0.98; α = 0.92, ω = 0.93).

For model estimation, we used the Weighted Least Squares Mean and Variance adjusted (WLSMV) estimator, which is recommended for variables measured on a 5-point Likert scale. We also employed the Maximum Likelihood estimation with Robust standard errors (MLR) estimator (see

Table 4. SEM models of willingness to separate at the source and deliver MSW.

Model	Estimator	df	χ2	CFI	TLI	RMSEA [90% CI]	SRMR	AIC	BIC	R2
Model with four predictors	WLSMV	55	1117.504	0.976	0.966	0.05 [0.04, 0.05]	0.051	-	-	0.830
Model with four predictors	MLR	55	506.710	0.963	0.947	0.08 [0.07, 0.08]	0.058	55,937.842	56,134.955	0.828
Model with three predictors	WLSMV	38	818,743	0.983	0.975	0.04 [0.04, 0.05]	0.044	-	-	0.830
Model with three predictors	MLR	38	346,953	0.970	0.957	0.08 [0.07, 0.09]	0.052	44,336.262	44,489.572	0.829

Note. df = Degrees of freedom; χ² = Chi-square; CFI = Comparative Fit Index; TLI = Tucker–Lewis Index; RMSEA [90% CI] = Root Mean Square Error of Approximation [90% confidence interval]; SRMR = Standardized Root Mean Squared Residual; AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion.

).

The initial model showed good fit. However, we found that the perception of economic benefits was not a significant predictor of the intention to perform these behaviors. Therefore, we estimated an alternative model including only three predictors, excluding this variable. This model, computed using both the WLSMV and MLR estimators, had a better fit compared to the original model. Additionally, when comparing Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values—available only for the MLR estimator—the three-predictor model yielded lower values, indicating a better fit. Consequently, Figure 1 presents the results of the three-predictor model estimated with WLSMV. For detailed SEM analysis results, see Appendix G in the Supplementary Material.

The results show that awareness of the negative consequences of not separating and delivering MSW was the strongest predictor of willingness to engage in these practices, followed by the perception of environmental benefits and, to a lesser extent, subjective norms. These three predictors were positively correlated: awareness of negative consequences showed a strong correlation with perception of environmental benefits and a moderate correlation with subjective norms; likewise, perception of environmental benefits was moderately correlated with subjective norms.

Although the perception of economic benefits was not a significant predictor in the SEM model, it showed a significant positive effect in a simple linear regression (β = 0.412, p < 0.001). However, in a multiple linear regression analysis, its effect disappeared (β = 0.002, p = 0.874) (see Appendix H in the Supplementary Material). These results suggest that while the perception of economic benefits may increase willingness toward source separation and the delivery of MSW in simple analyses, their influence is less relevant compared to environmental knowledge and social pressure variables when considered simultaneously. Nevertheless, the items used to measure this variable exhibited low internal consistency (α = 0.58), which limits the reliability of inferences based on this measure.

4. Intervention Proposal

Based on the results obtained, we designed an intervention aimed at increasing source separation and delivery of hard-to-manage MSW to collection systems in the municipalities of Cúcuta, Los Patios, Villa del Rosario, San Cayetano, and El Zulia, in the administrative region of Norte de Santander, Colombia (see Figure 2).

The main objective of this proposal is to overcome the identified psychosocial, structural, and institutional barriers, discourage competitive behaviors, and promote pro-environmental behaviors within the community that contribute to the sustainable management of hard-to-manage MSW. To this end, environmental knowledge and awareness, the perception of benefits, favorable social norms, and a sense of co-responsibility for the sustainable management of hard-to-manage MSW will be strengthened.

The intervention design is based on low-cost strategies, adapted to local dynamics and supported by recent scientific evidence [38,39,40,41,42]. Therefore, it is a multi-component intervention integrating knowledge from the social sciences, psychology, and social marketing. Evidence suggests that this type of intervention is effective in generating lasting changes in pro-environmental behavior [9,16,18,31,43].

The intervention consists of three strategic axes. The first axis seeks to strengthen infrastructure by installing containers for hard-to-manage MSW in high-traffic, easily accessible public spaces in the five municipalities. The location of these containers will be determined in coordination with key local stakeholders, prioritizing the suggestions raised by participants in the social mapping sessions, compliance with public health regulations, and the optimization of collection routes.

The second axis involves implementing a targeted public education program to reduce some of the identified psychosocial and institutional barriers. This program includes five sequential activities aimed at raising awareness, training, and providing feedback on the sustainable management of hard-to-manage MSW in municipalities. Since it is not feasible to implement this public education program on a massive scale, it will be targeted at strategic stakeholders—community leaders, educational communities, and local authorities—to enable these stakeholders to become multipliers of the acquired knowledge and practices.

The third axis corresponds to a multi-channel communication plan designed to expand the reach of the intervention and reduce barriers to accessing information. This plan will utilize a combination of direct, indirect, and digital communication channels. The direct channel will host participatory workshops with local leaders, serving as spaces for training, dialog, and feedback. The indirect channel will consist of disseminating key content through local radio stations, newspapers, and television. The digital channel will utilize social media such as Facebook and Instagram, electronic newsletters, and a dedicated website to disseminate information, facilitate interaction with key stakeholders, and showcase the intervention’s progress. The content of this communication plan will be generated from audiovisual material produced during the public education program activities, with the prior authorization of the participants. It will be adapted to the sociocultural contexts of each municipality, aiming to increase its relevance and effectiveness.

The intervention will be implemented in accordance with the last two stages proposed by CBSM. In Stage Four, the intervention will be piloted in one of the municipalities to evaluate the effectiveness of the three strategic axes and make adjustments. Subsequently, the intervention will be implemented on a large scale in the remaining municipalities based on the lessons learned from the pilot.

5. Discussion

In this study, we present the application of the CBSM approach in five municipalities of Norte de Santander (Colombia), a border region with Venezuela, to promote source separation and delivery of hard-to-manage MSW to collection systems. The prioritized MSW types—tires, household appliances, batteries, household insecticides, computers, and peripherals—were defined based on the management needs and issues identified in the municipalities.

We apply the CBSM approach because it is based on the recognition that pro-environmental behaviors are often conditioned by barriers [17,18,19,20] and considers communities as active agents of social transformation and not only as recipients of interventions [16,20,21].

One of the main contributions of this study is the expansion of the CBSM approach by incorporating the analysis of key determinants of pro-environmental behavior to be promoted during the barrier identification stage [22]. Specifically, in our study, in addition to identifying the main psychosocial, structural, and institutional barriers that hinder the behaviors of source separation and delivery of hard-to-manage MSW to collection systems, we analyze the competing behaviors to be discouraged, the attributions of responsibility for MSW management, and the community’s willingness towards the pro-environmental behaviors to be promoted.

The results obtained support the broadening of the approach. The inclusion of key determinants analysis has enabled the design of a more comprehensive intervention tailored to local dynamics. In addition to seeking to overcome barriers, it also aims to discourage habits that are counterproductive to sustainability, promote environmental awareness, and foster a stronger sense of co-responsibility [39]. We identified that source separation and delivery of hard-to-manage MSW is limited by a combination of psychosocial, structural, and institutional barriers that affect both motivation and the capacity for community action [10,26,28].

Among the psychosocial barriers identified are the low awareness of the environmental problem at the local level, limited knowledge about pro-environmental behaviors and their benefits, indifference to the impacts of their consumption, and a negative perception of existing management systems. In parallel, the identified infrastructure and institutional barriers included a shortage of bins that limits undifferentiated delivery, inefficient collection routes, a lack of visibility and communication regarding existing sustainable initiatives, and weak institutional articulation. These barriers have been previously reported in other similar studies conducted in countries of the Global South [7,12].

Identifying these barriers is essential, as adopting pro-environmental behaviors requires not only recognizing the problem and its causes but also understanding the potential positive and negative consequences of one’s actions [27,30,38]. However, even with high levels of awareness, most of these behaviors can only be implemented if the right environmental conditions exist to enable them [27,31].

Regarding hard-to-manage MSW management practices, we identified three main patterns. First, behaviors that harm the environment and public health persist, such as undifferentiated waste disposal, prolonged accumulation in households, and inappropriate disposal through burning, burial, or dumping into water sources. These practices have also been identified in other countries in the Global South [7,11]. Second, pro-environmental practices were observed, ranging from the full implementation of source separation and differentiated delivery to cases where only source separation is carried out. Third, community strategies adapted to the local context are emerging, such as the reuse of products, the delegation of management to informal recyclers or businesses, and the dismantling of waste to recover valuable materials for economic purposes.

These results underscore the need for comprehensive interventions that integrate educational, structural, and community-based approaches to address the issue. It is essential to develop communication campaigns and training programs that highlight the impacts of practices harmful on the environment and public health, while also teaching how to implement alternative practices that are perceived as easy to implement and contribute to sustainability [9,30,38]. Furthermore, it may be beneficial for individuals who already engage in pro-environmental behaviors to take on visible roles as community leaders and promoters of change. This can strengthen social norms and reinforce citizen co-responsibility in MSW management [31].

Regarding community-based practices, while they represent creative and adaptive solutions to the inefficiencies of formal systems, they also pose significant risks. Without adequate technical conditions or protection, the informal management of MSW can expose people to toxic substances and generate environmental contamination. Furthermore, informality limits the traceability of MSW and can perpetuate social inequalities. Therefore, management systems and public policies must recognize and integrate these practices within more inclusive regulatory frameworks that guarantee safe and sustainable conditions, without undermining community participation [39,41].

Regarding the attribution of responsibility for managing hard-to-manage MSW, participants pointed to public institutions and local governments, followed by themselves, and finally, the business sector. At a practical level, this result underscores the need to make MSW management visible from a co-responsibility perspective, demonstrating that the actions of all actors within the system contribute to progress toward sustainability [30,41].

The results of the proposed explanatory model on the willingness to separate and deliver MSW support its predictive validity. We identified that awareness of the negative consequences of not engaging in these practices, followed by the perception of environmental benefits and subjective norm, act as interrelated predictors of the willingness toward these behaviors. These results underscore the importance of designing comprehensive interventions that enhance awareness of consequences, reinforce perceptions of environmental benefits, and foster favorable social norms, demonstrating that pro-environmental practices are valued by the community [13,42].

In our initial explanatory model, we also included the perception of economic benefits as a predictor of willingness to engage in these pro-environmental behaviors. It was identified as a significant predictor in the bivariate analyses. However, its influence disappeared in the multivariate models, suggesting a secondary effect or one mediated by other variables. This result is consistent with previous studies, which indicate that economic incentives can encourage initial participation but tend to lose effectiveness in the long term or in the face of educational strategies, awareness-raising initiatives, or strategies to improve the physical environment [42,43]. This result is especially relevant in contexts with limited economic resources, such as the one in which we collected data, where implementing long-term economic incentives may not be feasible. Hence, allocating available resources to strengthen environmental awareness, motivate community commitment, and improve infrastructure is a more effective and sustainable approach in the long term [40].

Finally, we highlight the importance of the complementarity between the qualitative and quantitative results. The qualitative results on psychosocial barriers—such as low awareness of the problem of MSW management in their municipalities, limited knowledge of sustainable practices, and limited perception of positive impacts associated with sustainable management—may seem contradictory to the quantitative results, which report a high awareness of the negative consequences of not separating or delivering of MSW, both for the environment and for one’s own and family health, as well as the perception of environmental benefits of adopting these behaviors.

However, this apparent contradiction does not necessarily imply an inconsistency. We believe that these results suggest that, although there is general awareness of the environmental consequences of not separating or delivering MSW, a weak identification of the problem at the local level persists, possibly due to a perception of spatial or temporal distance. Furthermore, there is a lack of practical knowledge about the chain of pro-environmental behaviors to be implemented, as well as an absence of conditions that facilitate their adoption [10,26]. These findings underscore the importance of distinguishing between distinct levels of environmental knowledge, including cognitive, practical, and contextual [27].

In this regard, we emphasize the importance of using mixed methodologies. Qualitative data can offer insights into barriers to pro-environmental behavior that may not be readily apparent using quantitative data collection techniques [28]. In addition, combining individual and group participation techniques—conversational and observational—enriches the analysis by integrating different types of information, from personal experiences to social dynamics.

Study Limitations and Future Directions

This study presents at least three limitations that could be addressed in future studies.

First, the snowball sampling strategy, selected as the most feasible given the security and accessibility restrictions of the context, may have affected the representativeness of the sample. This technique likely favored the inclusion of individuals with stronger ties to social networks, community leaders, or local organizations, excluding those who were less integrated or had low participation in community activities. Additionally, the gender imbalance observed in the sample can also be attributed to the use of this sampling strategy. This distribution does not reflect a deliberate selection criterion but rather the demographic profile of individuals who were more willing or available to participate in the study. This trend is consistent with previous research, which has shown that women tend to exhibit greater environmental concern and are more likely to engage in pro-environmental behaviors [44,45]. The imbalance may partly reflect a greater interest among women in participating in environmental research. While this limits the generalizability of the findings to the broader population, it provides valuable insights into the perspectives of those more actively engaged with environmental management issues. Future studies could complement this strategy with alternative methods, such as quota sampling or mixed approaches that combine targeted recruitment through key stakeholders with open sampling techniques in public spaces or digital platforms, to enhance the representativeness of the sample.

Second, the proposed explanatory model focused exclusively on psychosocial variables, omitting relevant structural factors such as accessibility to MSW drop-off points. However, the qualitative results suggest that including contextual variables would allow for a more complete understanding of the factors that facilitate or inhibit the implementation of pro-environmental behavior. Furthermore, the items administered did not differentiate between specific types of MSW, which may have limited the accuracy of responses, as willingness can vary by type of MSW. Future research should incorporate structural variables and employ items that distinguish between different types of MSW or focus on a specific category.

Third, using self-reported data from the questionnaire may have introduced social desirability biases, which could affect the validity of the responses. Also, the economic benefits variable showed low internal consistency, which calls into question its reliability and underscores the need to test a new measure in future research. Furthermore, the relationships identified in the model should be interpreted as predictive, not causal, associations. Therefore, it is recommended that the proposed pathways be validated using experimental or longitudinal designs.

Finally, although this study focused on five municipalities to design a contextualized intervention, the results cannot be generalized to other municipalities. However, the protocols used and the intervention proposal are transferable and adaptable to other territories, representing an opportunity to conduct comparative studies across regions.