Exploring antecedents of built environment for walkability of older adults: A systematic literature review

Defining research questions

To gain insight into the current state of research on the BEW of older adults, specifically in terms of its antecedents and outcomes, the following four research questions have been identified:

These four research questions emerged through the initial literature survey that was undertaken to study the antecedents of BEW in older adults. The finding of the answer to RQ1 would enable the identification of the theories that influence the BEW of older adults. The answer to RQ2 would enable the identification of publications in terms of research contribution, research focus, and research type in BEW. The answer to RQ3 would open the scope for an understanding of whether there is a need to develop the model, test the existing model, work on the advancement of the model, or further compare the existing models to find their convergence or divergence in terms of the ECS of agribusiness. Finally, the answer to RQ4 will shed light on the future direction of research on the BEW of older adults considering the role of the associated theories.

Identifying keywords and the search strategy

The initial literature survey was performed to uncover theories that affect the antecedents of BEW in older adults and, accordingly, five prominent theories: 1. Community-Engaged Urban Design Theory (CEUDT). 2. Ecological Model of Ageing (EMA), 3. Social-Ecological Model of Health Promotion (SEMHP), 4. Active Aging Framework (AAF), and 5. Neighbourhood social environment theory (NSET) was identified. The research studies available on BEW using these five theories were searched thoroughly in standard databases. The electronic databases that had publications on BEW in the urban context were identified, and as a result, 15 such indexing agencies were scrutinized, which contained peer-reviewed journals, a high volume of BEW literature, and content-specific topics in that field. The indexing agencies of the databases considered were as follows: 1. Google Scholar 2. Scopus, 3. Web of Science, 4. ProQuest, 5. SAGE, 6. Science Direct, 7. JSTOR, 8. Wiley Online, 9. Springer Link, 10. Taylor & Francis Online, 11. EBSCO, 12. SSRN, 13. ERIC, 14. Emerald Insight, and 15. Elsevier’s Science Direct. The databases from which the papers were selected were as follows: 1. SCOPUS, 2. Clarivate Analytics, 3. ProQuest, 4. SAGE, 5. JSTOR, 6. Wiley Online Library, 7. SpringerLink, 8. Taylor & Francis Online, 9. EBSCO, 10. ERIC, and 11. Emerald Insight.

Fixing the years of starting and ending the search of publications in the database is very important, as it provides data for trend analysis. While there are no very well-established hard and fast rules, they are left to the discretion of the researchers to arrive at the period so that the major trends are covered. In this SLR, five theories have a dominant influence on the research construct. Each of these theories has different origins and developmental phases. CEUDT has had an impact on publications during the last 10–15 years (2010–2024), with the rationale that urban design theories, including community engagement, have evolved with a focus on inclusivity and participation. Recent publications are likely to capture the contemporary understanding and applications of community engagement in the context of urban design for walkability. The EMA has had an ideal period of development since the past 20–30 years (1994–2024), the rationale being that researchers have applied this theory since the last 20–30 years to provide a comprehensive understanding of its development and application in relation to the built environment for older adults. The SEMHP has had an ideal period of impact during the last 15–20 years (2004–2024), with the rationale being that the last 15–20 years have witnessed the development and understanding of the relationship between the social environment and health outcomes. The AAF has had a related impact during the last 10–15 years (2009–2024), the rationale being that the last 10–15 years will capture the contemporary literature on how the AAF has been applied to the built environment, especially in promoting physical activity among older adults. Finally, the NSET has had an ideal period during the last 10–20 years (2004–2024), the rationale for the choice being – during this time, the theory has been explored to provide insights into how this theory has been incorporated into research on the built environment and walkability.

Importantly, the primary objective of this research is to explore the antecedents and outcomes of BEW for older adults. Therefore, even though theories have been active in the generic sense of the wellbeing of older adults, the specific context of the BEW of older adults dates back to the early 2000s. One of the earliest references in the search results dates back to 2003, with a study by Saelens, Sallis and Frank discussing the environmental correlates of walking and cycling (Van Dyck et al., 2013; Winters et al., 2015). Another study by Takahashi, Baker, Cha, and Targonski was published in 2012, providing insights into the relationships among walking, biking, and the built environment for adults aged over 70 years (Takahashi et al., 2012). These findings indicate that the field has been actively studied for more than two decades, with ongoing research contributing to our understanding of how the built environment can affect physical activity and quality of life among older adults. Therefore, this SLR considers the period of publication selection from 2000–2023.

Having fixed the period of review of the articles, the search strategy included three sets of search items: (1) a list of theories available in the BEW of older adults in the context of urban design (e.g., “Community-Engaged Urban Design Theory”); (2) theories and their relevance in BEW, which targeted associated concepts (e.g., ‘safety’, “security”, “comfort”, “convenience”, and “aesthetics”; and (3) discipline-specific terms combined with the BEW of older adults (e.g., “policy frameworks” and ‘governance”).”

With respect to the search approach and search queries, diverse search strings were employed for each database. This is due to the distinct nature of each database, making a singular search string insufficient for obtaining the desired results. Consequently, numerous comprehensive searches were executed via various combinations of words and search strings. Table 1 provides details of the list of search strings and their combinations.

Selecting and assessing the quality of primary studies

Search strings were used for all selected theories, and 622 studies were retrieved in total. First, manual screening of relevant studies based on the title was considered. In the case of the title being relevant, abstract reading was undertaken, and in this elaborate process, 202 studies were excluded, which included conferences, workshops, books, editorial reviews, dissertations, and book reviews. The articles were narrowed down to 420 relevant studies, and after the elimination of 136 studies with repetition and similarity checks in multiple databases, the number of articles was reduced to 284. In the next step, inclusion and exclusion criteria were applied to each individual study by undertaking an intricate study of their introduction, literature review, results, and conclusion. A total of 169 studies were removed as a part of this exercise; thus, we were able to select 115 studies related to BEW in older adults. The obtained studies were further subjected to quality assessment, and 19 studies did not meet our specific quality criteria; the sample size was reduced to 96 papers. The elimination process is shown in Figure 1. The inclusion and exclusion criteria of the papers selected for review were as follows:

Figure 1. Flow chart of the selection process for review.

Inclusion criteria

The articles were included if they:

Exclusion criteria

Research articles were not considered if they:

The articles selected were under one of the four categories as follows:

Quality assessment

The evaluation of study quality poses a significant challenge in the context of an SLR. Determining what qualifies as a high-quality paper is largely subjective, as there are no standardized definitions for such assessments. However, certain factors, including the research context, design, relevant research questions, journal impact factor, precise definitions of key terms, and contributions to the body of knowledge, as outlined by Xiao and Watson (2019), are fundamental considerations for selecting articles. This study adopts an evidence-based SLR approach, and the criteria for assessing quality specifically align with the research context. A thorough process involved multiple readings of the articles and strict adherence to the inclusion and exclusion criteria, ensuring a comprehensive review and quality scrutiny of the selected articles. Additionally, the selection of articles was guided by key literature that underscores the synthesis of scientific and philosophical aspects of theories, with a focus on reproducibility for experimental purposes.

Data extraction perspectives

To streamline the process of extracting data, we formulated a Microsoft Excel form that encapsulates crucial aspects of each study. This measure was pivotal not only for organizing study features but also for consolidating data gleaned from the chosen studies. The examination of the created form concentrated on two viewpoints: initially, the overall traits of the research studies, and second, the utilized classification scheme. The subsequent sections elaborate on these two facets, which are integral to this procedure. Two reviewers independently extracted data from each report. A third reviewer resolved discrepancies when disagreements arose. Data extraction was conducted independently to reduce bias and enhance reliability. Data extracted by one reviewer was cross-checked by another to ensure accuracy and completeness. No direct contact with study investigators was reported in the manuscript for additional or missing data. The process relied on manual, reviewer-led efforts to maintain rigor and accuracy. This structured and collaborative approach ensured high-quality data extraction, minimizing errors and biases in synthesizing the included studies.

Data synthesis procedure

During the data synthesis, we thoroughly scrutinized and merged findings related to general characteristics, the identification of theories and articles, research design, target behavior, and the classification scheme of studies. The following section offers a detailed breakdown of these particulars.

Data extraction

The data extraction forms the basis for synthesis of the data in an SLR, and to facilitate this, we included two distinct parts: (i) identification of the general characteristics of the included studies and (ii) development of the classification scheme.

General characteristics of the papers

This section intends to provide an analysis of the papers incorporated in this research, specifically addressing the initial three research questions outlined in the introduction. The extracted data included information on (i) the country where the research was conducted, (ii) the database utilized for the study, (iii) the journal in which the study was published, (iv) the theory employed, (v) the article type, (vi) the source type (primary and secondary), (vii) the research design (qualitative, quantitative, and mixed methods), (viii) the target behavior, (ix) the type of sampling, and (x) the measurement of variables related to the BEW of older adults. Additionally, fundamental details about the studies, including the author’s name, study title, and study year, were documented for reference purposes.

Classification scheme

The selected studies were classified based on three perspectives that are relevant to this research: research contribution, research focus, and research type. Each of them is discussed in the following sections.

Contribution type

The BEW of older adults as a research construct can derive its theoretical foundation from theories in different areas of study, including sociology, urban planning, public health, gerontology, environmental psychology, and architecture.

Research focus

To answer RQ4 of this research, four categories of research focus areas were identified, as described below.

Past studies on the development of models for BEW have investigated the influence of antecedents such as social support, age-friendly urban design, and community engagement programs on BEW (e.g., John & Gunter, 2016). The focus was on understanding the relationships between these factors and the outcomes associated with increased physical activity, enhanced socialization, and improved quality of life for older adults. Researchers have employed a range of research designs, including cross-sectional analyses, longitudinal studies, and intervention-based trials, to explore the multifaceted dynamics between built environment features and the desired outcomes in the context of older adults’ walking behaviors (e.g., Annear et al., 2024). Studies have used geographic information systems (GISs) to analyse the relationship between the built environment and older adults’ physical activity levels (e.g., De Wolf & Bocken, 2024). Other studies have employed GPS devices to map individual activities within the environment, thereby providing measures of the life/activity space and destinations. Moreover, research has focused on the use of technology in facilitating older adults’ independence and participation in meaningful activities, such as managing daily tasks and overcoming environmental challenges.

In the realm of research studies focusing on model testing of the BEW of older adults, past investigations delved into various antecedents, including social support, age-friendly urban design, and community engagement programs (e.g., Rupp et al., 2020). These studies sought to understand the nuanced relationship between these factors and their impact on the outcomes associated with increased physical activity, enhanced socialization, and improved quality of life for older adults. Past research aimed to validate and refine models that could effectively predict and explain the complex interplay between built environment features, antecedents, and multifaceted outcomes in the context of older adults’ well-being. Some studies have tested specific aspects related to the walkability of older adults. Some studies have utilized semi structured interviews to gather insights from older adults about their walking habits and the factors influencing their decision to walk. Studies have shown that social support plays a significant role in encouraging older adults to continue walking despite challenges, such as inclement weather (e.g., Leyden, 2003). Studies have also revealed the importance of pedestrian facilities, such as benches and well-lit walking paths, in enhancing walking behaviors among older adults. The aesthetic appeal of the walking environment, including elements such as natural surroundings and cleanliness, was noted to make walking more enjoyable (e.g., Kou et al., 2019). Another stream of model testing focused on the fear of falling as a critical concern related to walking among older adults. The findings suggested that past falls increased older adults’ anxiety regarding walking, potentially preventing them from undertaking activities such as walking that might expose them to risky environments such as uneven ground surfaces, and specific interventions were administered to prevent falls in older adults. These studies have demonstrated the significance of model testing in understanding the impact of the built environment on older adults’ walking habits and the influence of various factors on their physical activity levels and social interactions.

Several types of research studies have been conducted in the past to advance the model of the BEW of older adults. These studies have focused on antecedents such as social support, age-friendly urban design, and community engagement programs and outcomes such as increased physical activity, enhanced socialization, and improved quality of life (e.g., Rookset al., 2022). Numerous quantitative studies have been conducted to measure the impact of these antecedents on outcomes. These studies often involve statistical analysis of data collected from surveys or observational studies. Studies have collected data on the frequency of walking among older adults in different neighbourhoods and then correlated this with factors such as the availability of age-friendly urban design features, community engagement programs, and social support (e.g., John & Gunter, 2016). Qualitative research has also played a significant role in advancing the model. This type of research involves detailed interviews or focus groups with older adults, urban planners, and community leaders to gain insights into the perceptions and experiences related to BEW. The findings from qualitative research have provided rich, nuanced data that complement the quantitative data. Some studies have employed experimental designs to test the effectiveness of different interventions aimed at improving BEW. Studies have compared the outcomes for older adults living in neighbourhoods with different levels of age-friendly urban design features before and after an intervention was implemented (Carlson et al., 2012). Longitudinal studies have tracked the changes in BEW over time, providing valuable insights into the long-term effects of interventions. These studies often involved follow-up surveys or observations over several years, allowing researchers to examine trends and changes in the outcomes. These types of research studies have contributed significantly to the advancement of the model of BEW for older adults, providing valuable insights into the antecedents and outcomes related to BEW.

The findings from studies with an orientation towards model integration have contributed valuable insights into the complex interplay between built environment features, social support structures, and community engagement initiatives, shedding light on the potential for positive outcomes in terms of the well-being and lifestyle of older adults. Studies have explored the relationship between the built environment and physical activity among older adults (e.g., Carlson et al., 2012; Van Dyck et al., 2013). Studies conducted by the Healthy Urban Living and Active Population (HULAP) project have investigated the associations between the built environment and physical activity in different countries. These studies utilized various methodologies, including surveys, interviews, and observations, to collect data and analyse the results. The findings of these studies indicate that the built environment plays a significant role in promoting physical activity and improving the quality of life of older adults. However, several researchers have emphasized that However, there is a growing consensus among scholars that additional research is required to unravel the complexities of these interactions and to establish evidence-based methods for fostering walkable spaces that cater to older adults.

Research type

Six different research types have been identified in publications on ECS in agribusiness, which are described in Table 2.

Data synthesis

In the context of an SLR, the synthesis of data involves systematically analysing and combining findings from various studies to generate new insights or conclusions. This systematic process includes extracting, organizing, and integrating data obtained from the included studies in accordance with the review’s research objectives or questions. The primary aim of data synthesis in a systematic literature review is to provide a thorough and evidence-based summary of the findings from the studies included in the review.

Results of the analysis of general characteristics

Publications on the BEW of older adults who adopt the CEUDT generally share several common characteristics. These publications often featured an interdisciplinary approach, drawing on insights from fields such as urban planning, gerontology, and community health. They tend to focus on the collaborative aspects of urban design, emphasizing the involvement of older adults and the broader community in the planning and implementation of walkability initiatives (e.g., Cheranchery et al., 2024). Moreover, these publications commonly highlight the social and environmental factors associated with CEUDT, emphasizing the importance of community engagement programs, age-friendly urban design, and social support structures (e.g., Davern et al., 2020). Some of the studies employed mixed-methods research designs, combining qualitative and quantitative approaches to capture both the subjective experiences and objective outcomes related to the adoption of CEUDT in enhancing the built environment for walking among older adults.

Publications exploring the BEW of older adults, particularly those adopting the EMA, exhibit distinctive characteristics. These studies encompass a comprehensive perspective, considering various ecological levels, such as individual, interpersonal, community, and societal factors, that influence the walking behavior of older individuals (e.g., Golden & Earp, 2012; Rosso et al., 2021). Researchers have delved into the intricate interplay among the physical environment, social structures, and individual characteristics, acknowledging the dynamic and multifaceted nature of aging within the context of the built environment (Davern et al., 2020). Publications employing the EMA have presented a holistic understanding of the factors shaping walkability, addressing the complex interactions between older adults and their surroundings (e.g., Van Dyck et al., 2013). Moreover, these studies commonly emphasize the importance of ecological approaches in developing interventions and policies aimed at enhancing walkability for older adults, contributing to a nuanced comprehension of the subject matter.

Publications on the BEW of older adults that have adopted the SEMHP have focused on the multifaceted interactions between individuals and their environment, emphasizing the dynamic interplay of factors at various levels, including individual, interpersonal, community, and societal aspects (e.g., Michael & Carlson, 2009; Rooks et al., 2022). Research within this framework has explored how the SEMHP can be applied to increase walkability for older adults by considering factors such as social support, neighbourhood design, community engagement, and policy implications. Moreover, these publications commonly employed a holistic approach, acknowledging that the impact of the built environment on walking behavior is influenced by a complex interconnection of social, environmental, and individual factors. The overarching goal of these studies has been to offer a comprehensive understanding of the factors affecting walkability among older adults within the context of the SEMHP.

Publications focusing on the BEW of older adults who adopt the AAF have delved into multifaceted aspects of the built environment, emphasizing its role in facilitating active aging among older individuals. Research within this framework has explored the impact of urban design, infrastructure, and community planning on the walking behavior of older adults. These studies have commonly employed a holistic perspective, considering not only the physical attributes of the environment but also the social and psychological dimensions (e.g., Carlson et al., 2012; Sundling & Jakobsson, 2023)). The integration of the AAF in these publications reflected a broader understanding of aging that goes beyond mere physical health, incorporating elements such as social engagement, accessibility, and quality of life into the discourse on the built environment and its implications for active aging among older adults.

Publications focusing on the BEW of older adults and adopting the NSET typically share common characteristics. These publications have investigated the intricate interplay between the physical environment and social factors influencing walking behaviors among older individuals (Emish et al., 2023; Litt et al., 2024). They often explore how neighbourhood design, social support systems, and community engagement initiatives impact the walkability of older adults. Some of the studies adopting NSET in this context have employed mixed-methods approaches, incorporating quantitative assessments and qualitative insights to comprehensively understand the dynamics at play. Furthermore, these publications emphasize the importance of considering the social environment alongside physical features in designing age-friendly neighbourhoods that promote walking and contribute to the overall well-being of older adults (e.g., Davern et al., 2020; John & Gunter, 2016). The general characteristics of such publications underscore the importance of a holistic and integrated approach to studying the built environment for walkability among older adults through the lens of neighbourhood social environment theory.

Analysing the publication trend based on various indexing agencies reveals distinct patterns in the dissemination of research on the BEW of older adults. Scopus emerged as the leading indexing agency, with 13 publications, constituting 13.5% of the total. Google Scholar closely followed with 11 publications (11.5%), whereas Web of Science accounted for 10 publications (10.4%). ProQuest SAGE and ScienceDirect shared similar levels of prominence, with 9 publications each, representing 9.4% each. JSTOR contributed 8 publications (8.3%), and the Wiley Online Library contributed 6 publications (6.3%). Springer Link, had 5 publications (5.2%). Taylor & Francis had 4 publications (4.2%). EBSCO and SSRN had 3 publications each (3.1%). ERIC, Emerald Insight, and Elsevier’s Science Direct each contributed 2 publications (2.1%). This trend analysis highlights the diverse sources contributing to the literature on the BEW of older adults, reflecting a wide-ranging interest and dissemination across reputable indexing platforms ( Figure 2). The trend analysis of the selected papers in this systematic literature review (SLR) reveals a diverse distribution across various databases. SCOPUS stands out as the predominant database, contributing 25 publications, constituting 26% of the total. Clarivate analytics followed closely, with 22 publications, accounting for 22.9% of the publications. ProQuest with 10 publications represents 10.4% of the total number of publications. SAGE had 9 publications, constituting 9.4%. JSTOR, with 8 publications, contributes 8.3%, whereas the Wiley Online Library and Springer Link, with 5 publications each, contribute 5.2%, and Taylor & Francis and EBSCO each contribute 4 publications, with a 4.2% share. Furthermore, ERIC and Emerald Insight, with 2 each, contribute 2.1% of the share. This trend highlights the wide-ranging exploration of BEW of older adults across multiple scholarly databases, highlighting a comprehensive and inclusive approach to the literature selection ( Figure 3).

Figure 2. Distribution of publications based on indexing agencies.

Figure 3. Distribution of publications in databases.

The trend analysis of the country-wide distribution of publications, as depicted in Figure 4, reveals insights into the geographical spread of research contributions. Among the 18 countries represented, the United States emerges as the leading contributor, with 22 publications, constituting 22.9% of the total publications, followed by the United Kingdom, with 13 publications (13.5%). Australia has 11 publications, accounting for 11.5%, whereas Canada has 9 publications, accounting for 9.4%. Similarly, the number of publications and percentage contributions of the remaining countries are as follows: New Zealand, 7 (7.3%); Denmark, 6 (6.3%); Spain and France, 5 (5.2%); Germany, 4.2%; Sweden and Italy, 3 (3.1%); and the Netherlands, Belgium, Taiwan, South Korea, Brazil, China, India, and Nigeria, 1 (1%). Thus, 57.3% of the publications concerning BEW in older adults were from the USA, the UK, Australia and Canada. The trend indicates that much research has to be undertaken on the BEW of older adults by the rest of the countries in this field in connection with the five theories of specific interest to this SLR.

Figure 4. Country wise distribution of publications.

The trend of publications on the BEW of older adults has consistently increased over time. According to the data provided, there are two publications in 2000 and 2001, followed by a small increase to three publications in 2002, 2004, 2006, and 2008. After 2008, the number of publications started to rise significantly, reaching four publications in 2012, 2014, 2016, and 2017 and peaking at eight publications in 2021. The trend continued in 2022, with ten publications, eleven in 2023, and it is reasonable to expect that the number will continue to grow. There could be several reasons why there was an increase in publications on BEW after 2018 ( Figure 5). First, as awareness of the importance of walkability for older adults grows, so does interest in studying and publishing research on this topic. Second, governments around the world have started to recognize the importance of walkability for older adults, leading to policy changes that may result in more research being conducted. Third, recent advances in technology, particularly in the areas of data analysis and spatial planning, have made it easier to conduct and publish research on BEW. Fourth, with the aging population, there is an increasing demand for research that addresses the needs of older adults. This has led to a surge in publications on topics related to the built environment and older adults. Thus, the increase in publications on BEW of older adults is likely due to a combination of growing awareness, policy changes, technological advancements, and an emerging research field dedicated to addressing the needs of older adults.

Figure 5. Year wise distribution of publication frequency.

Results of theory identification and frequency of use

The AAF is the most highly discussed theory (35.4%) in the context of the BEW of older adults. While there could be many reasons for the choice of this theory, the main reason observed was that it focused mainly on physical activity and health promotion, making it a frequent choice for research on the outcomes of increased physical activity and improved quality of life among older adults (e.g., Davern et al., 2020; MacCarthy et al., 2023; Marquet et al., 2017). Given its broad applicability to health behaviors and the importance of social networks in influencing health behaviors, SEMHP (25%) might be frequently referenced in studies examining socialization and quality of life (e.g., Leung et al., 2021; Michael & Carlson, 2009; Silveira & Motl, 2019). The CEUDT is the third most common line (18%), as this theory specifically addresses the design process and community engagement; it is likely to be referenced in studies that consider the role of urban design and community participation in shaping walkable environments (Kou et al., 2019; Fang et al., 2022; Rooks et al., 2022; Rupp et al., 2020). The fourth is NSET (11%) because this theory is focused on the social aspects of the environment, which could make it relevant to studies looking at the socialization aspect of BEW (e.g., Adkins et al., 2017; Koohsari et al., 2021; Leyden, 2003). EMA is the fifth (8%) theory used in the literature, while potentially influential, this theory might be less frequently referenced in BEW research than others are, as it deals more with the broader environmental and biological factors affecting aging rather than the specific built environment (e.g., Carlson et al., 2012; Rosso et al., 2021; Zheng & Yang, 2019) ( Figure 6).

Figure 6. Share of theories in publications.

Results and Analysis in the Publications

Based on the research design characteristics ( Table 4), there are almost equal contributions in terms of the qualitative approach (41.7%) and quantitative approach (45.8%); however, very few mixed methods (12.5%) based on research studies exist ( Figure 7). Among the 44 quantitative studies, the majority used exploratory factor analysis (50%), followed by confirmatory factor analysis (36.4%), and the remaining were descriptive studies (13.6%). With respect to the sampling techniques used for quantitative methods, among the 44 papers, the majority of the studies were based on nonprobability sampling (68.2%), followed by probability sampling (27.3%), and in the remaining (4.5%), no sampling details were mentioned. The qualitative studies (N = 40) involved mainly focus group interviews (60%), followed by in-depth interviews (30%), and the remaining studies involved semistructured interviews (10%).

Figure 7. Distribution of publications via the research approach.

Results of the classification scheme

The classification scheme, which has a bearing on RQ2 of this SLR, focuses on contribution type, research focus, and research type in connection. A total of 96 articles were reviewed, and by considering the number and types of theories reviewed and the research undertaken to date, the categorization could be the underpinning theories applicable to BEW of older adults based on the contribution type, various concepts were theorized based on the five theories, namely, the AAF, SEMHP, CEUDT, NSET, and EMA. The AAF (N=34) was the most widely used theory, the SEMHP (N=25) was the second most widely used theory, the third was the CEUDT (N=18), and the least used was the EMA (N=8), with the second least used being the NSET (11). Studies focused on Model Development (N=38), Model Testing (N=34), Model Advancement (N=16), and eight papers on Model Integration. Finally, in terms of research type, the highest number of papers were based on empirical research (N=36), followed by grounded theory (N=20), case studies (N=18), comparative studies (n=12), document analysis (N=08), and analytical research (N=02) ( Figure 8).

Figure 8. Research focus map.

Classification based on research focus

The classification of the theoretical models is shown in Figure 9 based on the research focus.

Figure 9. Distribution of studies by research focus.

Model development

Among the 38 papers on model development (accounting for 39.6% of the total papers) ( Figure 9), 14 papers were based on the AAF, 7 papers each on the SEMHP and CEUDT, 6 papers on the NSET, and 4 papers on the EMA ( Figure 8).

Model testing

Among the 34 papers on model testing (accounting for 35.4% of the total papers) ( Figure 9), 10 papers were based on the AAF, 12 papers each on the SEMHP, 7 papers on the CEUDT, 11 papers on the NSET, and 8 papers on the EMA ( Figure 8).

Model advancement

Among the 16 papers on model advancement (contributing to 16.7% of the total papers) ( Figure 9), 6 papers were based on AAF, 4 papers each on SEMHP, 3 papers on CEUDT, 1 paper on NSET, and 2 papers on EMA ( Figure 8).

Model integration

Among the 8 papers on model integration (contributing to an insignificant 8.3% of the total papers) ( Figure 9), 4 papers were based on AAF, 2 papers each on SEMHP, 1 paper on CEUDT, 1 paper on NSET, and no papers on EMA ( Figure 8).

Classification based on research type

Several different types of research have been reported in the literature on the ECS of agribusiness with respect to these four theories. The number of papers on these research types are as follows, and they are shown in Figure 10.

Figure 10. Distribution of papers by research type.

Grounded theory

There were 20 papers based on the grounded theory approach (20.8% of the total papers) ( Figure 10). These papers were distributed as follows: 06 each in model development, model testing, and model advancement and 2 papers in model integration ( Figure 8).

Comparative study

There were 12 papers based on the comparative study approach (12.5% of the total papers) ( Figure 10). These papers were distributed as follows: 06 involved model development, with 3 papers each for model testing and model advancement; however, there were no papers on mode integration ( Figure 8).

Document analysis

There were 8 papers (8.3% of the total papers) ( Figure 10) that used document analysis, of which 2 were in model development, 4 were in model testing, 2 were in model advancement, and there were no papers on model integration ( Figure 8).

Analytical research

There were 2 papers (1.1%) ( Figure 10) on analytical research, with 01 papers each in terms of model development and model testing. There were no papers on model advancement or model integration ( Figure 8).

Empirical research

This was the most commonly used research type in the literature. There were 36 papers (37.5%) ( Figure 10) in this category, among which 16 were on model development, 12 were on model testing, 2 were on model advancement, and 6 were on model integration ( Figure 8).

Case study

There were 18 papers in which case studies were adopted (18.8% of the total papers) ( Figure 10). Among these papers, 7 papers focused on model development, 8 papers focused on model testing, 3 papers focused on model advancement, and no papers focused on model integration ( Figure 8).

To summarize, the research focus map provides the areas where there is a dearth of research literature and possibly the areas that may be explored by future researchers in the BEW of older adults using the five dominant theories under consideration. In terms of research focus and research contribution, model integration can be attempted in EMAs. Model advancement may be attempted via analytical research. Additionally, model integration may be explored via comparative studies, document analysis, analytical research, and case studies. This is based on the finding that there was no evidence of research in these contexts considering the 96 papers shortlisted for the SLR. Furthermore, it may also be noted that there are relatively few research studies on integrative model development in terms of research focus, and there is scope for research to apply the theories NSET and EMA based on the contribution type. Finally, in terms of the research type, there is an opportunity to explore analytical research and document analysis. At the same time, researchers may also note that the AAF and SEMHP have been considered to be the most relevant theories applicable to the BEW of older adults; hence, there is scope to undertake further research using these two theories to test the available models, advance the theories, and integrate these theories to gain newer insights into making the BEW of older adults contribute more to outcome achievement.