1 Introduction

Based on a global consensus, the United Nations’s 2015 declaration of 17 sustainable development goals (SDGs) (targeted for achievement by 2030) led to more directed and systematic studies on several associated disciplines. The achievement of SDGs heavily depends on directing and aligning almost all the activities in academia and industry toward the SDGs and their specific target points. Assessment of the progress of activities related to the pursuit of SDGs is crucial at both individual SDG levels and considering the interdependencies or interlinkages of the individual SDGs with other SDGs. Therefore, investigating the progress of scientific research related to various SDGs and investigating the interdependencies among various SDGs or the possible influence of one over another can be useful for informing various stakeholders and for providing directions for future research.

SDG 12, i.e., ‘Responsible Production and Consumption’, encourages the striving to reduce or possibly eliminate the usage of unsustainable resources for economic or developmental activities. Therefore, these SDGs have direct and indirect linkages to many other SDGs, and their progress can influence many other SDGs directly or indirectly. Investigating the relationships between SDG 12 and other SDGs can be vital for those working directly on SDG 12 as well as related SDGs or both. In addition, several stakeholders, such as urban and rural administrators, national policymakers, and industry, can benefit immensely from a systematic analysis of the body of knowledge related to the literature on SDG 12. Thus, attempts of both of these kinds in the literature related to SDG 12 are discussed. First, we discuss the case of research on the interlinkage of SDG 12 with other SDGs.

Pradhan et al. [1] identified a synergetic relationship between SDG 1 (no poverty) and most of the other goals, while SDG 12 (responsible consumption and production) exhibited a trade-off relationship with most of the other goals. SDG 12 is found to have a trade-off between SDG 3 (in some countries, SDG 3 and SDG 12 are associated synergistically), SDG 1, SDG 6, SDG 4, SDG 17, and SDG 9. SDG 13 'Climate action' is also positively associated with SDG12 through multiple target points in the case of the country 'Nepal' [2]. SDG 12 reflects a trade-off relationship between economic development, environmental protection, and resource utilization, whereas other air pollution-related SDGs exhibit substantial synergy [3]. Most of these studies focused on identifying the relationships between SDGs, emphasizing whether one SDG enhances another, i.e., exhibiting a positive (synergetic) or one SDG inhibits another, i.e., exhibiting a negative (trade-off) relationship via the analysis of multiple data sources. An attempt to identify the linkage between other SDGs and SDG 12 and among themselves through the literature related to SDG 12 was not found. This gap needs to be addressed; therefore, this topic is addressed in this work as our first point of investigation.

In regard to attempts related to systematic analysis of the progress of research related to individual SDGs without considering interdependencies, several studies rely on scientometric approaches and systematic literature reviews. The scientometric analysis effectively determines current developments in a field, reveals insights about possible future developments, and informs policymaking exercises. Some works on scientometric research related to SDGs (either attempting to study all the SDGs together or one or more SDGs) are discussed next.

The emergence of prolific authors, schools of knowledge, key topics (such as climate change, health, and the burden of diseases), and the governance of issues related to these topics globally were discussed by Sianes et al. [4]. These authors also identified important existing and widening research gaps. Benton and Shaffer [5] conducted a scientometric analysis of published literature indexed in CINAHL, identified the underlying themes addressed by nurses and midwives, and identified the profession's potential to contribute to all 17 SDGs. A bibliometric study by Sweileh [6] identified the most researched and least researched targets related to SDG 3. A scientometric study on SDG 2 suggested that social policies, poverty lines, and living standards should be the paramount focus of future studies [7]. A scientometric analysis of SDG 13 associated with major aquatic species production revealed ocean acidification as a vital topic [8]. Roy et al. [9] revealed a lack of collaboration between countries in the Global North and South in SDG 6 research and proposed a conceptual framework for water and sanitation. An interesting scientometric study on SDG 5 'Gender Equality' analyzed gender equality among the first authors in SDG 5 research, identified the dominance of female first authors, and observed that publications with first authors received more interest [10]. A bibliometric mapping study emphasized the need for transformation in the role and function of education at the university level to properly address sustainable development, especially for SDG 4 [11]. A bibliometric study (related to SDG 4) on the role of STEM education in improving the quality of education identified the topics that formed the main hotspots [12]. Raman et al. [13] identified 'hydrogen storage', 'production', 'electrolysis', and 'hydrogen economy' as four major thematic areas from a bibliometric analysis of green hydrogen research (related to SDG 7). The bibliometric analysis of 1433 reviews by Raman et al. [14] highlights the expanding research focus on SDGs, with SDG 12 being particularly prominent in key journals. It is clear that while some of the SDGs are more enthusiastically studied through scientometric approaches, some remain underexplored. Let us examine whether SDG 12 is underexplored in this regard by analyzing the attempts thus far to review/assess SDG 12 via the scientometric approach and other approaches.

A study by Kumar et al. [15] focused on one of the targets of SDG 12 (12.3: Food waste) and identified 'Anaerobic digestion' and 'LCA' as important terms other than general sustainability-related terms. Through a bibliometric analysis of 'responsible production', Liu et al. [16] reported that the link between responsible production and financial performance has received increasing interest. Through bibliometric analysis, Rita and Ramos [17] revealed different research approaches and transversal themes related to e-commerce consumer behavior (related to SDG 12). A bibliometric study by Alzate Buitrago [18] suggested that economic decline is the only factor for sustainable consumption and development. One of the attempts to review research needs in SDG 12 from the literature (although not through a scientometric approach) and exploratory expert workshops was by Chan et al. [19]. They discussed several issues in five identified key themes. Some attempts to analyze specialized themes vital to SDG 12, such as green supply chains, are discussed next. Ahi et al. [20] conducted a bibliometric study on the energy-related performance measures of green supply chains and provided several inputs for recommendations on measuring energy-related issues of supply chains. An analysis of green supply chain performance measures through a bibliometric approach was conducted by Mishra et al. [21] to provide thorough insight into the theme and future directions, especially by identifying the most influential publications and key research areas. Gupta and Chauhan [22] attempted to analyze the intellectual structure of the literature related to the sharing economy and observed that recent studies failed to provide conclusive evidence to corroborate major sustainability claims of the sharing economy.

Although SDG 12 is not necessarily underexplored, the above-discussed studies were useful in providing either a broad overview related to SDG 12 or some themes related to it or attempted in-depth analysis (to some extent) of specific topics related to SDG 12. A comprehensive study related to SDG 12 to identify prominent topics and to provide insights from systematic in-depth analysis on each of these topics was not found. This served as our motivation to attempt the same process as our second investigation point.

Thus, to carry out both the first and second investigations, a systematic framework is needed. Therefore, the objectives of this research can be stated as follows:

The development and demonstration of a framework that:

  • This study maps SDG linkages in the literature related to SDG 12 and provides useful insights.

  • Determines topic prominence in the literature related to SDG 12 and provides prominent topics for further analysis.

  • Determines key publications in each prominent topic that helps identify key specific contributions within such topics.

The first functionality of the framework (i.e., mapping of linkages of SDG 12 to other SDGs) helps our first investigation point, and the other two functionalities are directed toward our second investigation point. Prominent topics related to SDG 12 are identified using the methodology introduced by Klavans and Boyack [23]. The indicator for prominence reflects the visibility and momentum of topics, which can predict whether a topic will grow or decline quickly, regardless of whether the topic is emergent. According to the authors, this indicator could be useful for stakeholders in their portfolio analysis and planning efforts. While this approach provides prominent topics within SDG 12, for more in-depth analysis of each topic by identifying key contributing papers and analysis of their specific contributions that may provide focused and clear insights that may inform stakeholders, including policymakers, the methodology of detection and prediction of paradigm shifts pivots by Prabhakaran et al. [24] is utilized.

2 Methodology

To carry out this study, publication data that are mapped to 17 SDGs are needed. SciVal (based on Scopus), which has substantial coverage and relatively good mapping of publications to SDGs (possibly in a better way than the Dimensions database), is used in this study. Some previous works, such as those by Cardoso et al. [25], Raman et al. [26], and Sreenivasan et al. [27], demonstrated the effective use of SciVal for data collection as well as topic prominence detection for bibliometric analysis. The data collection details are discussed next.

2.1 Data collection

A schematic diagram of the methodology used in this study is shown in Fig. 1. For this study, data collection was carried out in two phases—(i) at the beginning and (ii) after determining prominent topics. For phase 1, data on publications related to SDG 12 were collected from the preconfigured SDG 12 query from the SciVal database for six years from 2017 to 2022, as this enables users to create SDG interlinkage maps as well as to determine prominent topics.

Fig. 1
figure 1

Schematic diagram of the methodology

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During phase 2, publications belonging to each topic (identified through topic prominence, which will be briefly discussed) were collected from the Scopus database.

2.2 SDG linkage map creation and analysis

As the first objective is to create an SDG linkage map from the SDG 12 literature, an SDG coaffiliation network is created from the collected data. The SDG coaffiliation network represents the linkages between different SDGs mapped to the literature related to SDG 12 through a co-occurrence relationship. The weight of the co-occurrence link determines the strength of the co-occurrence relationship. The greater the link weight between a pair of SDGs is, the greater the number of documents in which the two SDGs are mapped together. This network analysis provides interesting information that may help researchers relate to SDG 12 and other SDGs.

Cluster analysis and centrality analyses are carried out in this work. As SDGs within the same cluster are more strongly related to each other than to SDGs outside the cluster, cluster analysis provides clusters or groups of SDGs that are more strongly linked. For cluster analysis, a fast community detection algorithm is used.

Centrality analyses are intended to determine the SDGs that play a key influential role in the network according to different attributes, such as the strength of linkage to others, relative importance in the network according to the quality of connections, and presence in the shortest paths between pairs of SDGs, for which centrality measures such as weighted degree, eigenvector centrality, and betweenness centrality are used.

The weighted degree is the sum of the weights of links associated with a node (SDG). The greater the weighted indegree is, the greater the strength of its linkage to other SDGs.

Eigenvector centrality reflects the quality of connections of a node (SDG), where quality is indicated according to whether the neighbors of that node (SDGs to which a particular SDG is directly linked) are also highly connected (linked to more SDGs). This is also a representation of relative importance.

The betweenness centrality of a node reflects the frequency with which that node (SDG) can be found between the shortest path between pairs of SDGs. The greater the betweenness centrality is, the greater the presence of that node in the shortest paths in the network.

2.3 Determination of topic prominence

Identifying topic prominence requires the creation of a citation network among the documents related to the SDG 12 literature. Prominently, it is implied that the topic is visible, has momentum, and receives attention from researchers. This does not indicate that the topic is hot, innovative, etc. [28]. In the citation network, the smart local moving (SLM) algorithm [29], an efficient clustering approach [30], is used to determine clusters. Each cluster (collection of documents) is supposed to represent a topic (that is likely to be addressed in most of the documents associated with that cluster). For each topic, the prominence score is assigned as a linear combination of citations, views (in Scopus), and journal impact factors (using CiteScore) according to the following formula given by Klavans and Boyack [23].

$${P}_{j}= 0.495 \left(\frac{{C}_{j}- mean({C}_{j})}{stdev({C}_{j})}\right)+0.391 \left(\frac{{V}_{j}- mean({V}_{j})}{stdev({V}_{j})}\right)+ 0.114 \left(\frac{{CS}_{j}- mean({CS}_{j})}{stdev({CS}_{j})}\right)$$
(1)

where \({C}_{j}= ln({c}_{j}+1)\) is the log-transformed value of the number of raw citations \({c}_{j}\) obtained from articles in cluster \(j\) in years n and n-1. Similarly, \({V}_{j}= ln({v}_{j}+1)\) is the log-transformed value of Scopus views \({v}_{j}\) obtained from articles in cluster \(j\) in years n and n − 1. \({CS}_{j}= ln({cs}_{j}+1)\) is the log-transformed value of the average CiteScore \({cs}_{j}\) for articles in cluster j in year n.

While the topic prominence metric provides prominent topics related to SDG 12, FV gradient-based analysis is utilized for in-depth analysis of each topic, especially for identifying key contributions. Topic selection for in-depth analysis is performed in the following way:

Topics of high prominence percentile (99 and above) are selected among the determined topics. After that, the topics can be grouped into four categories (quadrants that can be visualized) based on the prominence percentile and total publications (size of the topic). From the four quadrants, topics of substantial size and therefore requiring a mining approach for in-depth analysis were finally selected.

2.4 In-depth mining of prominent topics

A citation (sub)network is required for each topic for FV gradient-based detection and prediction of paradigm shift pivots. A citation network is briefly defined as follows:

A citation network is a structure with papers as vertices and citation links among such vertices as arcs (directed edges).

For network mining, the network has to have enough arcs or links. Network mining is impossible without links or arcs, i.e., if all the papers are isolated.

After citation (sub)network creation for each topic, the FV gradient weights of each arc (link) in the citation (sub)network need to be computed. A brief explanation of the flow vergence model and FV gradient weights is discussed next.

2.4.1 FV gradient computation: a brief revisit

As a citation network of publications is an information network, it is supposed to have a knowledge/information flow from cited papers to citing papers. Due to this flow, each work is assumed to have a flow vergence (i.e., convergence or divergence) potential. A work can be treated as being in flow divergence mode if its flow vergence potential is high (> 0) and as being in flow convergence mode if its flow vergence potential is less than 0. A high flow divergence potential signifies that work is either already having a greater outflux of knowledge than influx and will continue to be so or might soon have a greater outflux. Thus, the flow vergence potential of a work I can be expressed as given by Prabhakaran et al. [31]:

$${W}_{{FV}_{i}}= \frac{{indeg}_{i}-{outdeg}_{i}}{{indeg}_{i}+{outdeg}_{i}} +{eig}_{i},$$
(2)

where indeg is the total number of incoming links to (citations to) i, outdeg is the total number of outgoing links (citations from) from i, and eig is the eigenvector centrality of i. These are centrality measures of vertices; indeg (indegree) and outdeg (outdegree) are local measures that reflect knowledge outflux and knowledge influx, respectively; eig (eigenvector centrality) is the global measure; and the FV index (which incorporates both) is a hybrid centrality measure.

A work with high flow vergence potential (i.e., work in flow divergence mode) can contribute more to the growth of the network or the cluster to which it belongs, as it may be cited by other works, or the works that are cited may receive citations. Such a possibility may be less for work in flow convergence mode unless it attains flow divergence mode [31]. The theoretical and rational aspects of the FV model are discussed in detail by Prabhakaran et al. [24, 31, 32] and Lathabai et al. [33, 34].

As each work has a flow vergence potential, a potential difference exists between works connected by citation links (i.e., a flow vergence potential difference is possible for every citing-cited pair). This potential difference is termed the flow vergence gradient or FV gradient [33]. This potential difference between an u-v pair where v cites u can be expressed as given by Lathabai et al. [33] as:

$${FV}_{vu} = {W}_{{FV}_{u}}-{W}_{{FV}_{v}},$$
(3)

where \({W}_{{FV}_{u}}\) and \({W}_{{FV}_{v}}\) are the FV indices of works u and v, respectively. Arc or links corresponding to a citing-cited pair can be assigned weights using the FV gradient, making the network a weighted (signed) network.

As v is supposed to be relatively more recent than you, the FV index will usually be greater than v, and the FV gradient values will be positive. However, for some citing-cited pairs, due to the intellectual innovativeness or soundness of the citing work, its FV potential will be greater than that of the cited work, making the value of the FV gradient between the pair negative. Such occurrences are not frequent in a network and signal an unusual phenomenon, termed the FV effect or flow vergence effect in a citation network, and this phenomenon may reflect a paradigm shift. A citing paper in such a citing-cited pair can be treated as a pivotal paper of a paradigm shift; thus, the FV gradient is capable of detecting pivot papers of paradigm shifts [33] if the network represents a discipline or field of research. When the network represents a particular topic within a discipline or field, FV gradient analysis might pick pivot papers related to a shift that can somehow be associated with a major shift within the discipline. This ability to detect pivot papers is used here to determine key contributing papers subjected to content analysis to determine their specific contributions. The ability of the FV gradient to predict paradigm shift pivots was established by Prabhakaran et al. [24]. In that work, links (between citing-cited pairs) with FV gradient weights close to 'zero' that may 'zero-cross' to exhibit flow vergence effects in the future were used to predict possible paradigm shifts related to 'Nanotechnology for Engineering'. In this work, for each substantially developed and connected theme associated with SDG 12, the same approach is used for predicting potential pivots associated with a major shift within SDG 12.

As the citing-cited pair associated with the FV effect is denoted by a double chromatic representation by Prabhakaran et al. [32], where citing work (pivot) is represented by a red-colored vertex and cited work is represented by a blue-colored vertex, in this work, it is also maintained as such. However, to represent the citing-cited pair that might exhibit the FV effect, the potential pivot is represented using an orange-colored vertex, and the cited paper is represented using an indigo-colored vertex.

Now, we discuss the results obtained by implementing the above framework in the SDG 12 literature.

3 Results and analysis

3.1 SDG linkage map analysis

The SDG linkage map created as a coaffiliation network of SDG mappings to publications related to SDG 12 is shown in Fig. 2. According to the figure, SDG 12 is found to be mostly coaffiliated with SDGs 13, 7, 11, 2, and 15, as indicated by the thickness of the links. While the co-occurrence of SDGs 12 and 13 is found to be very strong (1847 publications related to SDG 12 are also mapped to SGD 13), the weight of the link between SDGs 12 and 7 is the next greatest, with a value of 1474 (i.e., 1474 publications related to SDG 12 are also mapped to SGD 7). SDGs 11 and 2 are also strongly mapped to SDG 12 via shared publications, as indicated by link weights of 1255 and 862, respectively. Although this result supports the findings of several previous studies, such as Thapa et al. [2], which revealed a strong positive relationship between SDGs 12 and 13, this result points to the existing gap in diligent and focused studies on the relationship between SDG 12 and other SDGs, especially 7, 11, 2 and 15. Additionally, upon cluster analysis of the SDG linkage network, SDGs (for which cluster formation is performed using a fast community detection algorithm, 12, 7, 13, 11, 2, 15, 3, 5, 6, and 14) were found in the same cluster. Thus, the relationships between SDG 12 and other SDGs, such as 3, 5, 6, and 14, are also worth investigating.

Fig. 2
figure 2

SDG linkage map associated with SDG 12 literature

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To understand the relationships among other SDGs and to determine the importance or influence of each SDG in the network structure formed by the literature related to SDG 12, centrality analyses such as weighted degree analysis, eigenvector centrality analysis, and betweenness centrality analysis are performed (Table 1). According to all these centrality measures, SDG 12 is found to have the top rank. According to all three centrality measures, SDG 13 ranks second. SDG 7 ranks third in terms of the weighted degree, and SDG 11 ranks third in terms of the eigenvector and betweenness. According to weighted degrees, the fifth position is occupied by SDG 2, and for eigenvector and betweenness, SDGs 8 and 15 rank fifth, respectively. Except for SDG 8, all the other SDGs ranked among the top 5 concerning three centrality measures belong to cluster 1 (SDG 12). As SDG 8 occupies a key position in the network related to the SDG 12 literature, more careful, comprehensive, and systematic analysis is required to identify the kind of relationship between SDG 12 and SDG 8, which may strengthen or bring more clarity to the findings of Zhu et al. [3].

Table 1 Top 5 SDGs according to centrality analyses
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3.2 Determination of prominent topics

Identifying prominent topics is performed using the steps described in Sect. 2 with the help of the SciVal tool. The prominent topics (prominence percentile > 99.3) are classified according to the scatter plot of the prominence percentile scores with the total number of publications on each topic. There are 4 possible quadrants representing 4 possible categories, as shown in Fig. 3.

Fig. 3
figure 3

Classification of the most prominent topics (with prominence percentiles > 99.3)

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More information about topics falling into the four quadrants is shown in Table 2.

  1. 1.

    Quadrant 1 (having high total publications (> 248) and high prominence percentile scores (> 99.68)) represents motor topics, which are fast-growing topics that are receiving enough visibility attention from the scientific community, etc.

  2. 2.

    Quadrant 2 (characterized by low total publications, i.e., < 248, and high prominence percentile, i.e., > 99.68) represents niche topics, which means that topics with high prominence and showing growth prospects and, if substantial growth occurs, can drift toward Quadrant 1.

  3. 3.

    Quadrant 3 (characterized by low total publications, i.e., < 248, and low prominence percentile, i.e., < 99.68) represents emerging or declining topics. These topics have not been researched much and have not received visibility or enough scientific attention. Dynamic analysis is required to determine whether the topic is emerging or declining.

  4. 4.

    Quadrant 4 (characterized by a high total number of publications, i.e., > 248, and a low prominence percentile, i.e., < 99.68) represents basic topics. These topics are relatively older or well-researched but lack sufficient visibility and scientific attention.

Table 2 Classified prominent topics and their details
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Six of the 12 prominent topics are well developed, with over 100 publications. These include (1) Industrial Symbiosis; Sustainable Development; Circular Economy; (2) E-Waste; Electronic Waste; Electronic Equipment; (3) Structural Decomposition Analysis; Carbon Emissions; Material Flow Analysis; (4) Solid Waste Management; Life Cycle Assessment; Municipal Solid Waste; (5) Community Participation; Green Product; Environmental Attitudes; and 6) Food Loss; Waste Prevention; Community Participation. These six topics need to be analyzed in depth to identify key contributing papers and their contributions.

3.3 In-depth mining of prominent topics

The networks must be substantially connected for in-depth mining using network analysis techniques. A lack of substantial connectivity, as in a highly sparse network, is the reason for avoiding less developed topics (fewer than 100 publications). Networks related to six selected topics are created, and it is found that for topic 6 (food loss, waste prevention, and community participation), all the papers are isolated, and there is not even a single link between these publications. Thus, topic six is unsuitable for network analysis, and the other five topics for which network creation is possible are selected for in-depth analysis using the FV gradient methodology discussed in Sect. 2. These details are discussed next.

3.3.1 Topic 1: industrial symbiosis; sustainable development; circular economy

The network related to topic 1 highlighting detected and predicted pivot papers is shown in Fig. 4, wherein the three red-colored nodes (papers) are the detected pivots and the orange-colored node is the predicted pivot, as also given in Table 3. The blue nodes [24] are the cited papers in the citing-cited pairs that exhibit flow vergence effects, and the indigo-colored nodes are the cited papers in the citing-cited pairs that have the potential to exhibit flow vergence effects. This color protocol is also used for the visualization of other topics. Although it is useful to analyze the content of blue and indigo nodes, we restricted the content analysis to detecting and predicting pivots because the contributions of these nodes are more important.

Fig. 4
figure 4

Network related to topic 1 highlighting detected (red) and predicted (orange) pivot papers

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Table 3 Details of the detected and predicted pivots in Topic 1
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From the network (Fig. 5), it can be seen that the first pivot, [35] specified in Table 3, is related to two blue papers, which is indicative of the importance of the theme addressed by it. The specific contributions of the detected and predicted pivots to this topic are discussed below.

Fig. 5
figure 5

Network related to topic 2 highlighting detected (red) and predicted (orange) pivot papers

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The first pivot in the table, [35], attempted to expand the targets for a transition toward a circular economy by proposing a set of brand-new targets. The second pivot, i.e., [36], identified restoration as a core principle of the circular economy; other concepts should augment restoration to realize the circular economy effectively. The third pivot, i.e., [37], identified economic, social, and environmental dimensions as the most appealing dimensions of the circular economy, and water and energy were the main resources associated with the circular economy. The predicted pivot, i.e., [38], dealt with a participation strategy for resource recovery from the waste program, which also appealed for a change in mentality, industrial practices, regulations, and regulations in the United Kingdom's waste and resource management.

3.3.2 Topic 2: e-waste: electronic waste; electronic equipment

The network related to topic 2 highlighting detected and predicted pivot papers is shown in Fig. 5. It can be seen that some of the detected pivots are directly connected and indirectly connected via blue nodes. The connection between the predicted pivots and detected pivots is also apparent from the visualization. All these points point toward the level of scientific attention and rigor of explorations on this topic. The existence of these detected and predicted pivots also shows that the scientific community has already made substantial contributions to SDG 12 via this topic, and more contributions can be expected in this regard. The specific contributions of the detected and predicted pivots to this topic are discussed below, as shown in Table 4.

Table 4 Details of the detected and predicted pivots in Topic 2
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The first paper in Table 4, [39], studied the health hazards of E-waste processing in China. Pb processing has been shown to have adverse effects, including genetic effects, and early intervention is needed for the growth and development of children in Guiyu. The second work in Table 2, i.e., [40], found that the informal sector's E-waste burning was responsible for high levels of air pollution and contributed to heavy metal exposure by residents. The third work, [41], proposed a framework for identifying the locations of sustainable collection centers for E-waste. The ranking of alternatives for waste management was evaluated using three primary criteria: economic, social, and environmental considerations. Among these, transportation costs emerged as the most influential factor in determining the location of the collection center.

The fourth study, [42], was an exploratory investigation into sustainable E-waste management practices, focusing on young consumers' knowledge, awareness, and participation levels. Despite a notable level of environmental consciousness among respondents, awareness regarding E-waste regulations, formal and informal recycling sectors, and recycling programs was found to be low. The fifth research effort, [43], aimed to quantify the levels of lead (Pb) and cadmium (Cd), as well as blood DNA methylation of specific genes (Rb1, CASP8, and MeCP2), and assess hearing abilities in 116 preschool children aged 3–7 years from an e-waste region and a reference region. The findings indicated elevated levels of Pb, altered promoter DNA methylation, and compromised hearing abilities among children in e-waste areas, suggesting that early exposure to environmental toxins could induce epigenetic modifications affecting the auditory system. The sixth study, [44], employed life cycle impact assessment (LCIA) methods and regulatory total threshold limit concentrations to explore the potential human health impacts and ecotoxicity of waste mobile phones. An analysis of a sample of basic phone and smartphone waste manufactured between 2001 and 2015 revealed no significant changes in the toxic components of basic phones. However, the use of smartphones significantly increased the use of toxic materials from 2006 to 2015. These results underscore the necessity of monitoring material components in electronics and the advancement of safe E-waste management practices.

The seventh work, [45], reviewed environmental pollution from printed circuit boards (PCBs) and examined methods for recovering valuable and hazardous metals from e-waste. Traditional methods, although effective, are burdened by high operational costs and generate secondary waste. Thus, this study highlighted advanced recycling methods such as hydrometallurgical, biometallurgical, and bioleaching processes. In particular, bioleaching was identified as a priority for further research and application due to its superior metal recovery efficiency from PCBs. The eighth study, [46], sought to enrich the knowledge base for initiating E-waste recovery experiments. Fax machine PCBs (FPCBs) and copy machine PCBs (COPCBs) were identified as high-value E-wastes for metal recovery. Cu, Ag, and Sn have emerged as economically important metals that can be recovered from most PCBs. The ninth study, [47], reviewed current trends in formal and informal E-waste management practices, highlighted emerging threats and proposed appropriate interventions. A significant recommendation included independent E-waste trading and processing surveillance to ensure compliance with the Basel Ban Amendment. The tenth study, [48], examined the life cycle environmental impacts of the mechanical plastic recycling practices of a company in China. This work concluded that centralized mechanical recycling is environmentally superior to the production of virgin plastics and composites in most aspects. The eleventh paper, i.e., [49], conducted a systematic review to address the prevalence of inadequate recycling protocols for e-waste and their toxicity. This study proposed an approach based on end-of-life electronic products as an effective strategy for e-waste management in both developed and developing countries.

The twelfth research work, [50], evaluated the state-of-the-art physical, chemical, and biological technologies for recycling and recovering secondary resource materials. A hybrid approach involving initial mechanical treatment followed by leaching with biodegradable reagents or organic acids produced by microbes is recommended. The thirteenth paper, [51], used a literature review and expert judgments to identify key enablers for effective e-waste management (e-WM) in circular economies. This study identified the 'Environmental Management System' (EMS) as the most significant enabler influencing other existing enablers. The fourteenth work, i.e., [52], presented a cost‒benefit analysis for e-waste recycling workers in Pakistan. The paper concluded that the government and business owners largely ignore the visible and hidden costs of the industry. This finding stressed the need for a systematic assessment based on identified impact factors to mitigate adverse effects. The fifteenth study, i.e., [53], employed the USEtox life cycle impact assessment (LCIA) model to assess the health-related implications of toxic elements in plastics, specifically focusing on human health. Mercury (Hg) and lead (Pb) were flagged as key health risk contributors, while chromium (Cr) was highlighted for its ecotoxicity potential. Importantly, the detected toxicity levels were below the thresholds specified by the RoHS Directive in China and Europe. A novel database was also introduced that is promising for informing ecodesign strategies in electrical and electronic equipment (EEE) manufacturing and plastic recycling within the e-waste sector.

The sixteenth investigation, [54], characterized spent automotive catalytic converters (SACCs) across various dimensions, including structural, thermal, physicochemical, morphological, and surface properties. The waste extraction test has emerged as the most effective method for mobility evaluation. Consequent analyses of contamination indices prompted the categorization of SACCs as hazardous waste. In the seventeenth paper, a circular supply chain (CSC) framework was delineated, particularly spotlighting the increasing role of the reverse supply chain (RSC) in end-of-life (EoL) management, enabled by the Internet of Things (IoT) [55]. This paper advocated for advancements in information infrastructure and proposed a qualitative evaluation for a heterogeneous IoT network tailored to meet CSC requirements. The eighteenth paper, [56], was a review centered on the need for a comprehensive strategy for efficient e-waste recycling that minimizes health risks. Various constraints, opportunities, and strategic directions for improved e-waste management were scrutinized. The nineteenth study, [57], explored the complexities surrounding electronic waste urban mining (EWUM) in India using multicriteria decision-making methods (MCDMs). Key solutions included enhancing public awareness regarding e-waste and training staff for eco-friendly electronics production and waste disposal.

The twentieth paper, [58], focused on the development of a sustainable process for recovering copper (Cu) and zinc (Zn) from end-of-life printed circuit boards (PCBs). The research confirmed, through a carbon footprint assessment, that an effective recirculation system could move toward a 'zero waste' paradigm. A twenty-first study, i.e., [59], investigated barriers and opportunities for formalizing e-waste management systems in Ghana using a triphasic methodology. Economic and financial limitations were found to be major impediments. The establishment of regional government agencies for oversight was suggested as a viable pathway for improving e-waste management. A twenty-second review, i.e., [60], evaluated the application of multicriteria decision-making methods in managing waste electrical and electronic equipment. The study highlighted the multidimensionality of decision-making criteria, emphasizing the need to augment the relevance of the environmental dimension. The third article, [61], examined recent technological advances in recovering precious metals from e-waste and spent catalysts. The transition from acid-leaching methods to less-polluting agents was noted, suggesting an increased focus on environmentally responsible technologies. The twenty-fourth paper, [62], introduced a revenue-expenditure analytical model based on five categories of small waste household appliances (SWHAs). The results indicated that, irrespective of the entity responsible for e-waste collection, recycling enterprises operated at a continual deficit, thus highlighting the significance of economic policies in e-waste management.

The first predictive pivot paper, [63], conducted 30 semistructured interviews within the electrical and electronic equipment (EEE) value chain to scrutinize the ramifications of the UK's waste electrical and electronic equipment (WEEE) directive. This study emphasized the critical role of the waste hierarchy in the European Union's waste strategy. It advocated for increasing the levels of the waste hierarchy to effectuate sustainable waste management and transition to a circular economy. Subsequently, a compendium of actionable measures was proposed to facilitate the adoption of the waste hierarchy under the purview of a resource efficiency framework.

The second predictive pivot paper, i.e., [64], executed a dual-method analysis, entailing quantitative scrutiny of state-level programs and qualitative evaluation of stakeholder insights. This study proposed a comprehensive framework that included legislative components targeting four key areas: (i) the stimulation of increased e-waste collection rates, (ii) the enforcement of socially and environmentally responsible treatment standards across the vendor network, (iii) the transfer of e-waste management expenses from public to private entities, and (iv) a flexible regulatory authority structure capable of adapting to industrial evolution.

3.3.3 Topic 3: structural decomposition; carbon emissions; material flow analysis

A network related to topic 3 highlighting detected and predicted pivot papers is shown in Fig. 6. As there are no connections among various detected pivots or between detected and predicted pivots, the themes addressed by different detected pivot papers and predicted pivot papers might not be strongly related. This may be treated as an indication of the diverse contributions already made by the scientific community to SDG 12 via this topic and the potential to do so. The specific contributions of the detected and predicted pivots to this topic are discussed below in Table 5.

Fig. 6
figure 6

Network related to topic 3 highlighting detected (red) and predicted (orange) pivot papers

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Table 5 Details of the detected and predicted pivots in Topic 3
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The first study presented in Table 5, i.e., [65], employed input‒output analysis to evaluate the total material footprint (MF) across a time series spanning from 2001 to 2015 for four major Chinese cities—Beijing, Shanghai, Chongqing, and Tianjin. This study utilized the STIRPAT model and further scrutinized the variables influencing these MFs. Among the cities, Chongqing registered the lowest per capita MF and exhibited a marginal temporal increase in MF, contrasting with the steep increase observed for Beijing and Shanghai. Notably, Chongqing was unique in its greater reliance on locally extracted materials. This research is posited as an inaugural study to highlight the disparity between the resource utilization patterns of economically prosperous coastal cities and their less-developed inland counterparts. The second study in Table 5, i.e., [66], employed the material footprint as a metric, incorporating measurements from global supply chain networks to address Sustainable Development Goals (SDGs) targets 8.4 ('resource efficiency improvements') and 12.2 ('sustainable management of natural resources'). A novel collaborative research platform based on multiregional–output analysis was proposed to facilitate the regular production, updating, and reporting of comprehensive global material footprint accounts aligned with SDGs 8.4 and 12.2.

The third research effort, i.e., [67], focused on rural China, one of the fastest-growing economies with a substantial population. This study investigated the carbon footprint and inequality arising from household consumption utilizing microlevel household survey data from 2018 and environmentally extended input‒output analysis. The findings indicated that reducing carbon intensity may curtail carbon footprints but could exacerbate economic inequality. Comprehensive strategies for mitigating both the carbon footprint and inequality, including (i) a transition to clean energy, (ii) poverty alleviation, (iii) income inequality reduction, and (iv) enhanced health care coverage, were recommended. The fourth research endeavor, i.e., [68], leveraged a dataset of 60,000 Japanese households to examine consumption patterns, particularly highlighting the climatic impact of excessive consumption of restaurant food, confectionery, and alcohol. This study aims to inform potential directions for global diets, as current Japanese dietary practices align closely with other international dietary guidelines. The fifth study quantitatively assessed the spatiotemporal dynamics of global deforestation footprints over 15 years (2001–2015) using remote sensing data and a multiregional input‒output model at a 30-m resolution. Although developed nations such as China and India registered net gains in forest cover, they also intensified the deforestation embodied in their imports. The study emphasized that tropical forests remain the most endangered biome and called for a reformulation of zero-deforestation policies, encompassing (i) robust transnational collaborations, (ii) supply chain transparency enhancements, (iii) public‒private engagements, and (iv) financial backing for tropical regions.

The sixth work, i.e., [70], estimated the global key environmental footprints of the German economy (BE) in a historical analysis from 2000–2015 and laid a projection up to 2030. The need for sufficient BE monitoring was emphasized, considering both the production and consumption perspectives and the global FPs of national economies. Using a world input‒output database, the seventh work, [71], provided important insights into the environmental and socioeconomic impacts of the world's largest food-producing countries based on four sustainability metrics—energy use, carbon footprint, value added, and compensation of employees by low-, medium-, and high-skill groups. Comparisons with other global databases, such as Eora and EXIOBASE, were also performed, and the analysis revealed that the agriculture industry has the largest environmental footprint in food supply chains. The eighth work, [72], was a systematic review based on the current neglect of the GHG emissions embodied in trade by climate change mitigation policies. Consumption-based accounting (CBA), which reveals lifecycle emissions, including transboundary flows, which are gaining support as a complementary information tool, can be a solution. This review provides a concise starting point for policymakers and future research by summarizing timely policy implications. The ninth work, [73], argued that global multiregional input‒output (GMRIO) analysis is the most efficient method for providing a consistent accounting framework for calculating various footprint indicators. Additionally, the ways in which GMRIOs can be further standardized and transformed from the scientific to the official statistical domain were analyzed.

The first predicted pivot (tenth work in Table 5), i.e., [74], utilized environmental extended input‒output analysis (EEIOA) and structural path analysis (SPA) to investigate the dynamic variation in the SO2 emissions embodied in 28 economic sectors in Chinese supply chains during 2002–2012. The most radical interventions for reducing Chinese SO2 emissions identified were controlling construction activities and reducing end-of-pipe discharge during power generation. The second predicted pivot, i.e., [75], implemented methodologies for assessing city-level production- and consumption-based emissions and estimating the associated emissions trajectories for Bristol, a major UK city, from 2000 to 2035. It also developed mitigation scenarios for reducing the former, considering potential energy, carbon, and financial savings in each case. Incorporating consumption-based emission statistics into cities' accounting and decision-making processes could uncover largely unrecognized opportunities for mitigation that are likely to be essential for achieving deep decarbonization. The third pivot, i.e., [76], employed both single- and multiregional input‒output tables to visualize the table coverage to compare disparities in carbon footprint accounting in the case of Tokyo, Japan. The emissions gap driven by Tokyo's final demand between single- and multiregional input‒output tables was considerably large.

3.3.4 Topic 4: solid waste management; life cycle assessment; municipal solid waste

The network associated with topic 4 is shown in Fig. 7, wherein detected and predicted pivot papers are appropriately highlighted. From the visualization, it can be seen that two detected pivots have drawn knowledge from more than one blue node, while all others are connected to only one blue node. This indicates that the scientific community has made diverse contributions to SDG 12 via this topic, and in some cases, explorations were made with more rigor. The specific contributions of the detected and predicted pivots to this topic are discussed below, as shown in Table 6.

Fig. 7
figure 7

Network related to topic 4 highlighting detected (red) and predicted (orange) pivot papers

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Table 6 Details of the detected and predicted pivots in topic 4
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The initial study shown in Table 6, i.e., [77], investigated the environmental efficacy of potential development trajectories for the municipal solid waste (MSW) management system in Campo Grande, Brazil. The conservative development pathway demonstrated the capacity to mitigate negative environmental externalities attributed to escalating waste generation. A more ambitious development scenario involving mixed MSW treatment and technological enhancements—such as the transition from composting to anaerobic digestion—exhibited significant impact reduction and positive externalities. The second paper, [78], offered a comprehensive literature review addressing the complexities of achieving circularity in the plastics value chain. This work discussed multiple stakeholder activities and presented an overview of the challenges associated with plastic waste recycling. Particular emphasis was placed on the trade-offs involved in designing, producing, collecting, and sorting postconsumer plastic waste (PCPW). The third research endeavor, i.e., [79], introduced a hybrid framework aimed at assisting firms in (i) quantifying waste volumes and seasonal patterns, (ii) identifying viable waste valorization strategies, and (iii) selecting pertinent socioeconomic-environmental and technological performance indicators. Two key opportunities were illuminated: (i) the marketing of substandard but edible waste at substantially reduced profit margins via wholesale channels and (ii) the extraction of high-value pectin from the same waste stream via microwave-assisted processes. Based on the market prospects of pectin, the latter strategy appeared more viable for medium- to long-term implementation. The fourth academic paper, [80], explored the feasibility of integrating food waste (FW) with biological wastewater (WW) treatment. Assessments were conducted regarding WW treatment efficacy, economic feasibility, net energy gains, and carbon footprint using steady-state modeling and life cycle assessment methodologies. The study concluded that leveraging surplus capacity in Hong Kong’s existing WW treatment facilities made integrated treatment strategies highly promising for sustainable development.

The fifth investigation, [81], employed life cycle assessment (LCA) to compare the environmental impacts of chemical recycling of mixed plastic waste (MPW) via pyrolysis with those of mechanical recycling and energy recovery. The pyrolysis method had considerably greater environmental impact than its mechanical recycling and energy recovery methods. The findings have implications for researchers, practitioners, and policymakers engaged in waste management and circular economy initiatives. In the context of China's policy to ban plastic waste imports, the sixth study, [82], employed the life cycle assessment (LCA) methodology to quantify the environmental consequences of alterations in flow patterns and treatment approaches for six categories of plastic waste across 18 nations. The analysis revealed a short-term improvement in four environmental indicators attributable to the ban. However, an increase in global warming was also observed. To align with long-term global environmental sustainability objectives, the study recommends that countries transition from an export-oriented waste management strategy to a domestic focus, specifically advocating a shift from landfill utilization to recycling mechanisms.

The seventh study, [83], employed a prospective life cycle assessment (LCA) to compare mechanical recycling (MR) and thermochemical recycling (TCR) across four newly collected waste subfractions, contrasting them with incineration coupled with energy recovery. The analysis unequivocally favored recycling methods over incineration for energy recovery. The eighth investigation, i.e., [84], utilized chemical property analysis to evaluate the environmental performance of 10 distinct recycling technologies with varying technology readiness levels (TRLs). When LCA outcomes were integrated with European polymer demand data, the study indicated the potential for a 73% reduction in CO2 emissions from plastics, equivalent to 200 Mtonne CO2 eq.

The initial predicted pivot, i.e., [85], examined household waste collection practices in a developing Bolivian city, demonstrating substantial benefits from optimizing waste collection strategies. The second pivot, i.e., [86], formulated an integrated approach to municipal solid waste (MSW) management emphasizing enhanced recycling and energy recovery. This study proposed three moderately intensified scenarios and comprehensive waste collection and recycling strategies, aiming to accommodate regional variations in waste composition and suitability.

3.3.5 Topic 5: community participation; green products; environmental attitudes

The network related to topic 5 highlighting detected and predicted pivot papers is shown in Fig. 8. The visualization shows more predicted pivots than detected pivots. This indicates that the scientific community can contribute more to SDG 12 via this topic in contrast to the already made contributions. This points toward relatively less scientific attention than the level of attention deserved by this topic. The specific contributions of the detected and predicted pivots to this topic are discussed below, as shown in Table 7.

Fig. 8
figure 8

Network related to topic 5 highlighting detected and predicted pivot papers

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Table 7 Details of the detected and predicted pivots in topic 5
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The first study in Table 7, [87], probed the economic implications of sustainable recycling and waste management policies aimed at addressing the growing crisis in waste management. This paper offers a roadmap for policymakers concerned with the practical validity and societal acceptability of such strategies. The second research endeavor, i.e., [88], scrutinized the intricate web of factors comprising (i) environmental concerns, (ii) perceived consumer effectiveness, (iii) choice behavior regarding plastic consumption, (iv) connectedness to nature, and (v) love for nature. Notably, the study revealed that 'environmental concern' and 'perceived consumer effectiveness' are precursors to 'connectedness to nature' and 'love for nature', which partially mediate the relationship with 'choice behavior for plastic consumption', particularly in emerging economies.

Turning to predicted pivots, the first initiative, i.e., [89], evaluated the impact of information dissemination on residents' waste separation intentions, employing the 'norm activation model framework.' This work broadens the corpus on waste separation behaviors and underscores the influence of public information campaigns. The second pivot, i.e., [90], involved an empirical assessment of recycling actions as a countermeasure to climate change. This study isolated the salient factors influencing recycling intentions and accentuated the imperative role of green education programs. These programs are pivotal in facilitating communication, amplifying awareness, driving engagement, and embedding environmental citizenship by cultivating resource recycling intentions.

Together, these papers expand our understanding of both the economic and psychological aspects influencing waste management and recycling behaviors. The focus on information dissemination and green education reveals a nuanced view that extends beyond pure economics and regulatory frameworks. It emphasizes the importance of public engagement and education as integral components of any comprehensive waste management strategy.

The third predicted pivot, i.e., [91], involved an empirical examination to elucidate the decisive factors influencing young consumers' behaviors concerning environmentally sustainable food purchases. By utilizing a questionnaire-based approach with both descriptive and causal objectives, this study delved into applying compensatory decision rules during prepurchase evaluations. The inferential results indicated a noteworthy role for these compensatory rules in shaping young consumers' judgments of environmentally sustainable food attributes.

4 Discussion

4.1 Topic 1: industrial symbiosis; sustainable development; circular economy

All the detected pivots deal with a transition toward a circular economy. The predicted pivot is also about the strategy that should be adopted to transition to a circular economy. The multiple detected and predicted pivots dealing with the same theme reinforce the shift toward a circular economy paradigm that will revolutionize many industrial operations. While industrial symbiosis focuses mainly on symbiotic relationships between firms or industries regarding product, byproduct, and utility exchanges, the circular economy embraces many other possible symbiotic relationships for the success of industries and sustainability [92]. The implications of the contributions of the detected and predicted pivots on this topic for various stakeholders are discussed next.

Urban and rural administrative authorities: Given that the circular economy is a central paradigm across various domains, focusing on establishing recovery pathways for reusing viable products is imperative. Additionally, leveraging advanced recycling technologies to maximize the extraction of critical raw materials and instituting targeted policy mechanisms to facilitate a waste hierarchy designed around resource efficiency is essential.

National policymakers: There is a need to revamp the innovation, industrial, trade, and commerce policies of the country to foster industrial symbiosis in such a way that it aligns well with the demands of a shift toward a 'circular economy', i.e., adopting policies to encourage a symbiotic relationship that is not confined to products, byproducts and utility exchanges between industries or firms.

Industries: New business activities should be planned in congruence with the principles and norms of the circular economy. Existing business activities should be upgraded to embrace the same approach. Transformation to a circular economy demands a healthy symbiotic relationship beyond the traditional industrial symbiotic relationship between firms and industries oriented around the product, byproduct, and utility exchange.

4.2 Topic 2: e-waste: electronic waste; electronic equipment

Electronic waste (e-waste) management, closely aligned with Sustainable Development Goal (SDG) 12, especially with targets 12.4 and 12.5 [93], warrants comprehensive inquiry into hazardous materials used in electronic equipment manufacturing, along with their ensuing social and environmental repercussions. Equally pertinent are the strategic methodologies for efficacious e-waste management in residential localities and the health risks emanating from extant e-waste management systems. In this regard, the identified and predicted pivot analyses have illuminated these multidimensional aspects, suggesting imminent paradigm shifts in e-waste management. These studies also serve as a reservoir of key legislative inputs to refine and augment e-waste management policies and can provide directions for further research on e-waste legislation, possibly complementing the suggestion by [94] to integrate the geographical or territorial peculiarities of countries into the national legal framework. The implications of the contributions of the detected and predicted pivots on this topic for various stakeholders are discussed next.

Urban and rural administrative authorities: Existing E-waste management systems should be systematically evaluated for their impact on residents, and if necessary, these systems should be revamped to eradicate or minimize the hazardous impact on residents. Special care should be taken to address the ecotoxicity of waste mobile phones and other E-waste. There is a need to establish high-end laboratory facilities (public, private, or public‒private partnerships) to identify key toxic materials and components that impact residents. Legislation should be considered for several key areas: (a) Increasing collection rates while instituting and enforcing eco-friendly standards across the supply chain. (b) The financial responsibility of e-waste management should be transferred from the public sector to the private sector. (c) Allowing for flexible regulatory oversight that can adapt as the industry evolves.

National policymakers: Consider the establishment of specialized research institutions for deeply exploring crucial areas such as the ecotoxicity of materials and components, the impact of existing waste management systems, etc., and nurturing them into centers of excellence that can directly work in synergy with industries toward the achievement of key targets of SDG 12 that are crucial for the achievement of other SDGs such as 13, 11, 2, 6, etc.

Industries: As there has been a shift from 'export' to 'domestic management' in waste management, enormous opportunities (and challenges) exist. These opportunities can be grasped by systematically overcoming challenges to make the most out of them. Firms dealing with waste management systems should adopt the efficient system strategies and designs discussed in important contributing publications from topics 2 and 4.

4.3 Topic 3: structural decomposition; carbon emissions; material flow analysis

As this topic addresses structural decomposition, material flow management, and carbon emissions, most detected and predicted pivots address material footprint (MF) assessment and carbon footprint assessment, mostly using data from the world input‒output database and allied databases. One of the works directly addressed a target related to SDG 12 and a target related to SDG 8. One of the detected works revealed a shortage of policy instruments, contradictions in policy recommendations, and the right starting point and directions for policymaking. One of the predicted pivots investigated the dynamic variation in the SO2 emissions embodied in 28 economic sectors in Chinese supply chains and determined that power generation was a key source that contributed to SO2. The second step involved implementing methodologies for assessing production and consumption-based emissions and developing mitigation scenarios for reducing such emissions. The third predicted pivot identified disparities in carbon footprint accounting. All these points indicate an ongoing shift toward 'green production and consumption' and 'green supply chains', which are vital for achieving SDG 12. A recent study by Lopes dos Santos and Jacobi [95] also emphasized the importance of green supply chain management for several SDGs, such as 12, 13, and 17. The implications of the contributions of the detected and predicted pivots on this topic for various stakeholders are discussed next.

Urban and rural administrative authorities: Developing or adapting a consumption-based accounting (CBA) system is advisable for mapping lifecycle emissions, including those that cross borders, within the governance framework of competent national authorities. Special care should be taken to establish mechanisms for assessing materials and carbon footprints within cities/municipal areas to ensure a transition toward 'green production and consumption' and 'green supply chains', as indicated by major contributing publications in topic 3.

National policymakers: Establish and periodically update industrial standards and laws for minimizing production, consumption, and supply chain emissions. Additionally, it is crucial to encourage the creation and adoption of a CBA (consumption-based accounting) information tool for urban and rural areas that reveals lifecycle emissions, including transboundary flows, as consumption-based emissions are mostly overlooked in many countries or cities. Revisions are required for zero-deforestation initiatives via robust international collaboration, enhanced transparency in supply chains, synergies between the public and private sectors, and targeted financial assistance for tropical forests.

Industries: Adoption of measures to avoid or minimize the use of hazardous materials and components (those that impact and burden residents in rural and urban areas) for the development of devices and equipment through the use of less hazardous alternatives. Alternatives that can be easily recycled and reused, if available, are more desirable because the possibility of recycling and reuse might compensate for the economic cost incurred from the choice of less hazardous alternative. Measures should be adopted to ensure low emissions during production and to adhere to green supply chain practices, legal frameworks, and standards (local, national, and international) as applicable. Additionally, special care should be taken to find innovative ways to keep the industry's performance intact when more efficient 'zero-deforestation' policies are in effect, without compromising adherence to those policies and not by backing out from green supply chain practices.

4.4 Topic 4: solid waste management; life-cycle assessment; municipal solid waste

As solid waste management is a vital crosscutting issue with a direct linkage to 12 SDGs, including SDG 12 [84], key investigations (reported in detected and predicted pivots) in this topic enriched the discourse on solid waste management, each addressing pivotal aspects of the field. One notable recommendation was to transition from traditional composting to more advanced anaerobic digestion techniques for treating organic MSW. Resource recovery has emerged as a multifaceted construct critical for achieving long-term sustainability. Specific avenues for a circular economy were highlighted, such as selling still-edible but imperfect waste at reduced profits and investing in pectin extraction technologies. The surplus wastewater treatment capacity was identified as an enabler for integrating food waste management. Moreover, pyrolysis is recognized as a substantially superior option to mechanical recycling, energy recovery, or the production of virgin plastics. Concurrently, the analysis of China's plastic import ban indicated a need for a shift from export-oriented waste management to a more domestic focus, specifically from landfills to recycling. These insights collectively serve as valuable input for policy frameworks that aim to achieve improved resources, energy, and environmental benefits (REEBs) in waste management, offering various competing and complementary strategies. The implications of the contributions of the detected and predicted pivots to this topic for various stakeholders are discussed next.

Urban and rural administrative authorities: For municipal solid waste treatment, as there is an ongoing shift from 'composting' to 'anaerobic digestion of organics', special treatment centers should be established at appropriate locations considering multiple factors and feasibility or upgrading existing centers wherever applicable. Consider adopting an integrated municipal solid waste management system focusing on reinforced waste recycling and energy recovery developed in a predicted pivot (i.e., [86]) in topic 4.

National policymakers: Specialized research institutions should be established to explore crucial areas, such as the ecotoxicity of materials and components and the impact of existing waste management systems, and these institutions should nurture these institutions into centers of excellence that can directly work in synergy with industries and local authorities to achieve the key targets of SDG 12 that are crucial for the achievement of other SDGs, such as 13, 11, 2, 6, etc.

Industries: Engage in proactive R&D activities by collaborating with academia to achieve SDG 12 targets, especially related to other SDGs such as 13, 7, 11, 15, 2, etc. Along with these challenges, pressing problems such as solid waste management (residential and industrial) triggered the formation of a dedicated industry on its own [96] and offered a myriad of opportunities for innovations for new players. Existing established players in other industries can also enter into waste management businesses through diversification (whichever is applicable among vertical, horizontal, or conglomerate diversification) depending on their relationship (or lack thereof) with waste management.

4.5 Topic 5: community participation; green products; environmental attitudes

These studies significantly contribute to a multifaceted understanding of waste management, recycling, and sustainable consumption through the use of economic, psychological, and social perspectives. While the detected pivots delineated the economic frameworks that policymakers should consider for effective waste management, the predicted pivots highlighted the psychological aspects, including the importance of information publicity and green education. These psychological factors have been shown to play critical roles in the communication, promotion, activation, and internalization of environmental citizenship. The third pivot is particularly illuminating in the context of sustainable consumption, unveiling a nuanced understanding of how young consumers evaluate environmentally sustainable food options. This finding underscores the intricate interplay of compensatory decision rules in shaping consumer attitudes toward green products. By elucidating these multiple dimensions, the papers enrich the ongoing discourse on sustainable waste management and consumption, offering valuable insights for policymakers, scholars, and practitioners.

Urban and rural administrative authorities: As highlighted by Droscos et al. [97], the right mindset and perceptions are crucial for any game-changing initiative. The right mindset, beliefs, and perceptions can be nurtured through proper awareness. To cultivate a proper perspective conducive to sustainability, focused effort through efficient leadership is needed. Analogous to the importance of school principals’ leadership in teachers’ professional development, as discussed by [98], the role of local authorities should take a leadership position for the development and maintenance of a team of sustainability professionals who can handle community participation initiatives. Effective programs are recommended to ensure the efficient waste separation behavior of residents and improve awareness among residents about the importance of 'community participation' in ensuring sustainability through green education programs. Specifically, younger individuals or students from local educational institutions can be educated and motivated because they are environmentally affectionate [99] but need education beyond their regular curriculum. Sponsorship and guidance for all these can be obtained from the central government and corporations (via CSR).

National policymakers: Sufficient aid in funds and other resources may be provided to respective local governing bodies to effectively spread information to improve awareness (through green education programs) among urban and rural residents about the importance of community participation in achieving sustainable production and consumption. Additionally, it is recommended that sufficient aid be provided to urban and rural areas to establish and sustain effective waste management systems that can be supported by proactive community participation.

Industries: Firms that are directly related to SDG 12 activities, especially waste management, can help by providing guidance and supplying resource persons and even actively participate in organizing green education sessions to spread awareness about healthy community participation. Firms not directly involved in waste management or any SDG 12-related sectors can also contribute by sponsoring such drives and initiatives as part of their CSR. However, CSR should be driven by a commitment to sustainability rather than expecting that CSR can improve corporate reputation because the influence of CSR on corporate reputation is not always unmediated [100].

In addition to these recommendations, it is recommended that industries collaborate with academia to investigate the influence and impacts of SDG 12 on other SDGs, especially those identified in this work (via SDG mapping analysis), such as SDGs 7, 11, 2, 15, 3, 5, 6 and 14. National policymakers are directed to engineer such collaborations by providing a conducive ecosystem for sustainability-oriented research.

5 Conclusion

Due to the direct importance of SDG 12 at the levels of individuality and society and due to its apparent connection to other SDGs (although the form of such a relationship is still debated, as is evident from the literature), we attempted to (1) map the relationship between SDG 12 and other SDGs, as it is naturally formed in the literature related to SDG 12; (2) determine prominent topics related to SDG 12 through an efficient scientometric method; and (3) mine key specific contributions in investigation-worthy topics through another established framework based on a network approach. SDG mapping analysis (the first investigation point) revealed an important gap in the existing pertinent literature and calls for robust and focused investigations about the relationship between SDG 12 and other SDGs, such as 7, 11, 2, 15, 3, 5, 6, and 14. Upon topic prominence analysis, five topics were found to be eligible for in-depth mining and analysis, and the key contributing papers were revealed via an FV-gradient-based methodology. The specific contributions of these publications are identified through content analysis (manual) of these publications.

5.1 Major contributions of this work

Thus, with the help of SDG linkage mapping and FV gradient-based analysis, we report important insights that may be useful for various stakeholders, including policymakers. Additionally, we attempted to provide some policy recommendations for national policymakers and urban and rural administrative authorities. Key takeaways for industries to ensure their smooth progress in light of many ongoing or upcoming shifts in five prominent topics that align with the overarching 'circular economy' paradigm are also revealed. As already mentioned in the introduction, the second investigation point (addressed in this work through topic prominence and FV gradient analyses) is not addressed in such a comprehensive manner and with this level of methodical rigor in any of the existing works. Thus, a systematic framework that diligently integrates three effective approaches, demonstrated effectively in the literature about SDG 12, is the major contribution of this work in addition to the valuable and insightful implications and suggestions provided to major stakeholders of SDG 12 and possibly to other SDGs.

6 Limitations and possible future explorations

A major shortcoming of this study is that as the study is dependent on the SciVal database, the coverage of the database impacts our study. The SDG linkage map, prominent topics identified, and (sub)citation networks within each topic might be slightly different if other databases such as Dimensions were used. Additionally, the accuracy of mapping publications indexed in SciVal to 17 SDGs affects our work. It will be interesting to explore the possible variations in results (and hence the insights retrieved) if the same approach is attempted in other databases. Such a study can complement this study by revealing missed insights and with the help of which more useful recommendations can be made. Additionally, we selected a few prominent topics for analysis (with prominence values > 99.3 and 100). For the use of this framework for the analysis of any other SDG, an appropriate threshold value must be chosen for topic prominence analysis to retain a substantial number of representative topics for analysis. Although our choice of threshold for the selection of predicted pivots (i.e., FV gradient value < 0.05) can be treated as a rule of thumb, the threshold value can be chosen appropriately (lower values if there are too many cases) for analysis of other SDGs.

7 Declaration of generative AI in scientific writing

During the preparation of this work, the author(s) used ChatGPT to rephrase existing content for readability. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the publication's content.