Sustainable Development Decisions Research Articles

Analysis of Energy Consumption Related to the Use of Air Conditioning in University Buildings in a Tropical Climate

Objective: To evaluate aspects of energy consumption with the use of air conditioners in two teaching units at the Federal University of Bahia (UFBA): the Polytechnic School (POLI) and the Faculty of Architecture (FAU). Method: The method used was to carry out a level I energy audit, with the collection of energy consumption data in the two units and information about the air conditioning equipment for the period between 2013 and 2018. Results and conclusions: average energy consumption indicators were found corresponding to 58 kWh/m²/year at the Polytechnic School and 40 kWh/m²/year at the Faculty of Architecture. As for the representation of the percentage of energy consumption related to the use of air conditioning, 36% were observed in the Polytechnic School and 19% in the Faculty of Architecture. Research Implications: Contributes to sustainable development and managers' decision making based on the analysis of the collected indices, which can serve as a benchmark for other universities with a tropical climate. Originality and Value: Finally, this research becomes original insofar as it contributes to obtaining indices of energy consumption in universities and data on energy consumed with the use of air conditioning.

The profitability index and its impact on sustainable development decisions

The profitability index plays an important role in helping decision-makers, whether they are short-term decisions or long-term decisions, the profitability index is used in various ways to assist short-term decision-makers related to: - By using scarce economic resources and developing the optimum production plan. - Determining production lines or products that continue to work and those lines or products that are discontinued based on their profitability. - Pricing of products. - Granting incentives to salesmen. These decisions are part of sustainability activities for any company, Also, the profitability index is used in the comparison between long-term investment projects when the net present value criterion is positive for these projects, meaning that they are economically feasible, and it is necessary to choose some of them without the other.

Measuring Qinghai-Tibet plateau's sustainability

• We construct a new comprehensive development capacity framework to survey the sustainability. • Ecological capacity diversity, ecological footprint diversity and resources efficiencies were combined from systems view. • Qinghai-Tibet plateau (QTP) presented low in the southwest and high in the northeast in sustainability. • The comprehensive development capacity of QTP grew by 4.37 times, from 0.5751 to 3.0883. • Feasible suggestions are provided to promote the sustainable development of the plateau. Qinghai-Tibet Plateau (QTP) is a unique geographical unit on the earth with abundant habitat types and biological species and has an inimitable role and status—Ecological Security Barrier and Asian Water Tower. Its development has far-reaching impacts on the surrounding areas, countries and even the world. Understanding the overall development capacity and status of the Qinghai-Tibet Plateau is essential to implementing the ecosystem protection strategy while balancing the needs of people in western China. Integrating ecosystem dynamics, resource consumption changes and resource utilization levels from systems view can inform management strategies and decisions for sustainable development on the Plateau. This study constructs a comprehensive development capacity index to reveal the real sustainability and to grasp how the socioeconomic system evolves in this unique geographical unit by integrating ecological capacity diversity, ecological footprint diversity, and resources efficiencies. From 2000 to 2020, the comprehensive development capacity of the QTP increased by 4.37 times. Most regions undergo improvements in the comprehensive development capacity. By 2020, except Ganzi and Ali, all other regions surpass the medium-level development capacity. We discuss the spatiotemporal characteristics of comprehensive development capacity and the reasons leading to these changes, and put forward targeted measures to promote sustainable development.

Improving Agricultural Green Supply Chain Management by a Novel Integrated Fuzzy-Delphi and Grey-WINGS Model

This study suggests a novel hybrid model for calculating the interrelationships between factors by integrating the Fuzzy set, Delphi, the Grey theory, and Weighted Influence Nonlinear Gauge System (WINGS) approaches in agricultural green supply chain management (AGSCM). Fuzzy Delphi helps to select 12 indicators from 19 factors by defuzzification for ambiguity associated with subjective judgment by 10 experts in data collection. Grey WINGS can illustrate the relationships, direction, and strength of factors simultaneously, which illustrates that environmental law, green consciousness, product quality, and price are the most significant factors of AGSCM. The results can help operators not only to analyze these key influencing factors, but also to understand the complex cause-and-effect relationships between these factors. This integrated model will hopefully provide a useful tool to agricultural policy makers and decision makers for sustainable development.

Assessment of land use and land cover change on Gum Talha (Acacia seyal var. seyal) forest in Bahar Alarab, Sudan

Abstract. Younis AYI, Jonathan BN, Togun AO, Yasin EHE, Omer SO, Hamad GAI, Aissata SD. 2022. Assessment of land use and land cover change on Gum Talha (Acacia seyal var. seyal) forest in Bahar Alarab, Sudan. Biodiversitas 23: 4549-4560. Evaluating land use and land cover change (LULC) is essential for the sustainable management of natural resources, biodiversity conservation, monitoring of food security, and research related to climate change and ecology. A better assessment of land-use changes is highly needed for further investigation due to increasingly rapid changes in LULC in response to human population growth. The emerging climatic change also has a significant effect on LULC. The objective of this study is to assess land use and land cover in Bahar Alarab, East Darfur State, Sudan, using remote sensing data obtained from satellite images. For assessing the LULC changes, Landsat images of the years 1988, 2002, and 2020 were downloaded and analyzed using QGIS 3.22.1 and ERDAS 2014 software, where supervised classification was applied with GPS point verification, change detection, matrix, and accuracy assessment. The analysis on LULC showed considerable changes during the two study periods, where 2020 had a considerable increase in forest cover in which on that year it occupied 26.44% of the area compared to 2002 and 1988 with 21.27% and 21.45%, respectively. Whereas 2002 the area was covered by a vast herbaceous vegetation (33.41%) compared to 1988 and 2002. Moreover, in 1988, shrubland decreased from 31.95% to 29.06% and 23.67% in 2020 and 2002, respectively. Sparse vegetation covered a considerable area in 2020 (23.61%) compared to 2002 and 1988 (21.65% and 17.71%, respectively). The results highlighted that there was statistically significant correlation between climate factors and LULC. Average temperature was highly positively correlated with sparse vegetation at 98.2%, while rainfall was highly negatively correlated with forest (-96.9%) and sparse vegetation (-88%), and highly positively correlated with herbaceous vegetation (83.5%). This study provides a unique understanding of LULC changes and their implications in management and conservation efforts, as well as a road map for decision makers for sustainable development of LULC in the Bahar Alarab.

Analysis, of multi-temporal remotely sensed spectral indices influence on ecology of Singrauli sub-district, Madhya Pradesh using an ecological impact index

In this paper, the ecological quality of Singrauli sub-district over a decade was investigated based on images of IRS LISS III and Landsat series of 2005, 2010 and 2015 respectively. The Analytic Hierarchy Process (AHP) was employed to develop the Geo-Spatial Ecological Impact Index (GEII) by assigning weights to the five ecological parameters (vegetative cover, moisture content, built-up index, water index and Land Surface Temperature (LST) and to determine the degree of impact on each one due to the increased anthropogenic activities. The study concluded that, there was an increase in the built up and the overall LST by 6.24 °C whereas, the vegetation covers and moisture content has decreased during the years 2005 to 2015. Aggregate change in ecological quality can be inferred from the increasing mean of GEII values from 3.39 to 3.61 indicates deteriorating ecological quality. The predicted map of GEII 2025 prepared using artificial neural network (ANN) revealed that the high ecological impact zones will cover 37.95% of the area by 2025. The result obtained from the study can be useful for policy and decision makers for sustainable development of urban sectors and natural resource management of the area with respect to ecological impact assessment.

Suitability Evaluation of Tea Cultivation Using Machine Learning Technique at Town and Village Scales

Suitability evaluation of tea cultivation is very important for improving the yield and quality of tea, which can avoid blind expansion and achieve sustainable development; however, to date, relevant research at town and village scales is lacking. This study selected Xinming Township in Huangshan City, Anhui Province, as the study area, which is the main production area of Taiping Houkui Tea—one of the ten most famous teas in China. We proposed a machine learning-based tea cultivation suitability evaluation model by comparing logistic regression (LR), extreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), gradient boosting decision tree (GBDT), random forest (RF), Gaussian Naïve Bayes (GNB), and multilayer perceptron (MLP) to calculate the weight accuracy of the evaluation factors. We then selected 12 factors, including climate, soil, terrain, and ecological economy factors, using the RF with the highest accuracy to calculate the evaluation factor weights and obtained the suitability evaluation results. The results show that the highly suitable area, moderately suitable area, generally suitable area, and unsuitable area land categories for tea cultivation were 14.13%, 27.25%, 32.46%, and 26.16%, respectively. Combined with field research, the highly suitable areas were mainly distributed in northwest Xinming Town, which is in line with the distribution of tea cultivation at the Xinming township level. The results provide a scientific reference to support land allocation decisions for tea cultivation and sustainable green agricultural development at the town and village scales.

Zoning Strategy for Basin Land Use Optimization for Reducing Nitrogen and Phosphorus Pollution in Guizhou Karst Watershed

Eutrophication caused by excessive total nitrogen (TN) and total phosphorus (TP) emissions is of wide concern for society at large. Studies have revealed certain relationships among land use, TN, and TP. However, the relationships among land use compound topographic position, TP, and TN have seldom been studied. Therefore, the objectives of this paper are to construct optimal zoning of land use and reduce the nutrient load of lakes. Spearman correlation and redundancy analyses were used to reveal the relationship between land use comprehensive topographic position and TN and TP in the lakes of Guizhou Plateau. The results show that the nutritional state of the research area is medium. The trophic level index (TLI) value and TN concentration were high during flood periods, while TP concentration was high in dry periods. The TN concentration in the tributaries was higher than that in the reservoir area. Construction land and valley were the sources of the pollution, whereas forest land and gentle slope were the sink. According to the ”source–sink” effect, once the optimal zoning of land use is completed, the governance of urban land pollution governed areas should be strengthened next. This paper can provide decision support for water environment management and sustainable development decision-making.

Spatial Variations of Village-Level Environmental Variables from Satellite Big Data and Implications for Public Health–Related Sustainable Development Goals

The United Nations Sustainable Development Goals (SDGs) include 17 interlinked goals designed to be a blueprint for the world’s nations to achieve a better and more sustainable future, and the specific SDG 3 is a public health–related goal to ensure healthy living and promote well-being for all population groups. To facilitate SDG planning, implementation, and progress monitoring, many SDG indicators have been developed. Based on the United Nations General Assembly resolutions, SDG indicators need to be disaggregated by geographic locations and thematic environmental and socioeconomic characteristics for achieving the most accurate planning and progress assessment. High-resolution data such as those captured at the village level can provide comparatively more precise insights into the different socioeconomic and environmental factors relevant to SDGs, therefore enabling more effective sustainable development decision-making. Using India as our study area and the child malnutrition indicators stunting, underweight, and wasting as examples of public health–related SDG indicators, we have demonstrated a process to effectively derive environmental variables at the village level from satellite big datasets on a cloud platform for SDG research and applications. Spatial analysis of environmental variables regarding vegetation, climate, and terrain have shown spatial grouping patterns across the entire study area, with each village group having different statistics. Correlation analysis between these environmental variables and stunting, underweight, and wasting indicators show a meaningful relationship between these indicators and vegetation index, land surface temperature, rainfall, elevation, and slope. Identifying the spatial variation patterns of environmental variables at the village level and their correlations with child malnutrition indicators can be an invaluable tool to facilitate a clearer understanding of the causes of child malnutrition and to improve area-specific SDG 3 implementation planning. This analysis can also provide meaningful support in assessing and monitoring SDG implementation progress at the village level by spatially predicting SDG indicators using available socioeconomic and environmental independent variables. The methodology used in this study has the potential to be applied to other similar regions, especially low-to-middle income countries where a high number of children are severely affected by malnutrition, as well as to other environmentally related SDGs, such as Goal 1 (No Poverty) and Goal 2 (Zero Hunger).

Commitment Indicators for Tracking Sustainable Design Decisions in Construction Projects

The construction industry is considered one of the largest contributors to climate change through its consumption of natural resources and generation of greenhouse gases. Much of this can be attributed to inadequate decision making and follow-up within construction companies. To mitigate this problem, considerable research on Sustainable Development (SD) reports on decision support systems have been developed in order to make sound decisions with respect to the environment. Nonetheless, and despite the availability of such tools, these systems fail to track the commitment to SD decisions and goals during the different phases of construction projects in general and the design phase in particular. As such, this study identified three standard SD indicators: waste reduction, energy consumption, and carbon emissions as the main contributors, and developed the framework to track the project stakeholders’ commitment to the relevant SD indicators during the project design phase. The developed framework was validated via an expert panel and used to create a Sustainable Development Commitment Tracking Tool (SDCTT-D). The SDCTT-D tool was also applied in an infrastructure project case study. The results of this study gauged the usability of the developed tool and corroborated the research premise.

Sustainability Performance Assessment Framework for Major Seaports in India

In performing seaport operations, triple bottom dimensions and its related key performance indicators play a significant role in improving overall aspects of seaport sustainability. This research paper intends to examine key seaport practices that form sustainable seaport development in the Indian major seaports context from stakeholder collaboration and seaport internal sustainable management decision framework. Firstly, the key practices of sustainable seaport development were examined through a broad literature review considering sustainable seaport development and related management and stakeholder-based theories. Sustainability thematic analysis is carried out based on the identification of various dimensions and key performance indicators from various literary works. Based on the theoretical framework seaport sustainability conceptual model was developed. Semi-structured interviews were conducted with 87 seaport professionals and FAHP was performed on an input basis by 23 seaport authorities to analyze the prominence of the proposed sustainable seaport development dimensions. This study also indicated that the economic dimension is the most important, while the social dimension is the least vital dimension perceived by Indian seaport managers. This research paper will conclude with a few policy insights for seaport managers in sustainable development decisions to discover areas for improvements in maritime sustainability and enhance the seaport competitiveness.

Using artificial intelligence to make sustainable development decisions considering VUCA: a systematic literature review and bibliometric analysis.

Sustainable development emergent subfields have been rapidly evolving, and their popularity increased in recent years. Sustainable development is a broad concept having numerous sub-concepts including, but not limited to, circular economy, sustainability, renewable energy, green supply chain, reverse logistics, and waste management. This polymorphism makes decision-making in this field to be an abstruse task. In this perplexing circumstance, the presence of VUCA conditions makes decision-making even more challenging. By taking advantage of artificial intelligence tools and approaches, this paper aims to study with a concentration on sustainable development-related decision-making under VUCA phenomena elements using bibliometric and network analyses which can propose numerous novel insights into the most recent research trends in this area by analyzing the most influential and cited research articles, keywords, author collaboration network, institutions, and countries that finally provides results not previously fully comprehended or assessed by other studies on this topic. In this study, an extensive systematic literature review and bibliometric analysis are conducted using 534 research articles out of more than 3600. From the content analysis part, four clusters have been found. The decision parameters, presumptions, and research goal(s) for each model are pointed out too. The findings contribute to both conceptual and practical managerial aspects and provide a powerful roadmap for future research directions in this field, such as how real-life multidimensionality can be considered in sustainable development-related decision-making, or what are the effects of the VUCA in sustainable development considering the circular economy and waste management intersection.

Lessons from nine urban areas using data to drive local sustainable development

Cities are central to achieving the 2030 Agenda for Sustainable Development, yet many remain disengaged from the process. This paper examines nine city and subnational pilot projects conducted between 2015 and 2019, to assess the role of a data-based approach to governance in improving decision-making for sustainable development. We consider to what extent a data-based approach to governance can help cities in (a) localizing the sustainable development goals (SDGs); (b) integrating national and local datasets; (c) increasing openness of data and enabling better accountability for outcomes; and (d) encouraging innovation in data gathering. We find that data is considered a useful entry point for local sustainable development conversations and employing a focus on data management is welcomed by nearly all local governments, however, few localities explicitly focus on data to improve their sustainable development outcomes. Critically, despite the excitement around big data, most cities are unable to access them due to capacity challenges, data ownership, and privacy concerns.

Consumption-Based CO2 Emissions on Sustainable Development Goals of SAARC Region

Consumption-based CO2 emission (CBE) accounting shows the possibility of global carbon leakage. Very little attention has been paid to the amount of emissions related to the consumption of products and services and their impact on sustainable development goals (SDGs), especially in the SAARC region. This study used a CBE accounting method to measure the CO2 emissions of five major SAARC member countries. Additionally, a Fully Modified Ordinary Least Square (FMOLS) and a causality model were used to investigate the long-term effects of the CBE and SDG variables between 1972 and 2015. The results showed that household consumption contributed more than 62.39% of CO2 emissions overall in the SAARC region. India had the highest household emissions, up to 37.27%, and Nepal contributed the lowest, up to 0.61%. The total imported emissions were the greatest in India (16.88 Gt CO2) and Bangladesh (15.90 Gt CO2). At the same time, the results for the long-term relationships between the CBEs and SDGs of the SAARC region showed that only the combustible renewables and waste (CRW) variable is significant for most of these countries. The sharing of the responsibility for emissions between suppliers and customers could encourage governments and policymakers to make global climate policy and sustainable development decisions, which are currently stalled by questions over geographical and past emission inequities.

Controls on the epilimnetic phosphorus concentration in small temperate lakes.

Phosphorus (P) is one of the key limiting nutrients for algal growth in most fresh surface waters. Understanding the determinants of P accumulation in the water column of lakes of interest, and the prediction of its concentration is important to water quality managers and other stakeholders. We hypothesized that lake physicochemical, climate, and watershed land-use attributes control lake P concentration. We collected relevant data from 126 lakes in Maine, USA, to determine the major drivers for summer total epilimnetic P concentrations. Predictive regression-based models featured lake external and internal drivers. The most important land-use driver was the extent of agriculture in the watershed. Lake average depth was the most important physical driver, with shallow lakes being most susceptible to high P concentrations; shallow lakes often stratify weakly and are most subject to internal mixing. The sediment NaOH-extracted aluminum (Al) to bicarbonate/dithionite-extracted P molar ratio was the most important sediment chemical driver; lakes with a high hypolimnetic P release have low ratios. The dissolved organic carbon (DOC) concentration was an important water column chemical driver; lakes having a high DOC concentration generally had higher epilimnetic P concentrations. Precipitation and temperature, two important climate/weather variables, were not significant drivers of epilimnetic P in the predictive models. Because lake depth and sediment quality are fixed in the short-term, the modeling framework serves as a quantitative lake management tool for stakeholders to assess the vulnerability of individual lakes to watershed development, particularly agriculture. The model also enables decisions for sustainable development in the watershed and lake remediation if sediment quality is conducive to internal P release. The findings of this study may be applied to bloom metrics more directly to support lake and watershed management actions.

Remanufacturing Marketing Decisions in the Presence of Retailing Platforms in the Carbon Neutrality Era.

Background: In response to the specific goals of carbon peaking and neutrality, remanufacture is becoming increasingly popular. With the marketplace being more and more adopted, an independent remanufacturer (IR) could sell its products via either the reselling model or the marketplace model. In order to contribute more to carbon neutrality, we investigate the optimal marketing decision for remanufacturing. We construct two models namely reselling model and the marketplace model, and further explore the effects of each marketing model on the decisions and profits of both the IR and the platform firm. Methods: We examine a platform firm that sells new products and an IR that sells remanufactured products under two marketing models based on game theory: (1) a reselling model in which the IR sells remanufactured products to the platform firm; then the platform firm resells to consumers; (2) a marketplace model in which the IR sells remanufactured products to consumers through the platform. Results: Our results show that aiming at carbon neutrality, the IR would be induced by the marketplace model to undertake remanufacturing operations and remanufacture products as many as it could still meet the market demand. Meanwhile, the marketplace model encourages the IR to rethink its work and manufacture more products under certain conditions. Furthermore, both the platform firm and the IR prefer the marketplace model to the reselling model within a Pareto zone. In addition, we find that both the platform firm and the IR could benefit from the marketplace model when they take carbon neutrality under consideration. Conclusions: This study provides managerial insight from two aspects. Remanufactures could decide their marketing model via thorough consideration of market competition, commission rate, and production cost. The government could do more to protect the marketplace environment in order to stimulate the internal vitality of the platform in the achievement march of carbon neutrality purpose. That is, this study will provide good guidance for sustainable development decision-making of remanufacturing marketing platforms, and further contributes to the achievement of the carbon neutrality goal.

Reducing uncertainty in ecosystem service modelling through weighted ensembles

Over the last decade many ecosystem service (ES) models have been developed to inform sustainable land and water use planning. However, uncertainty in the predictions of any single model in any specific situation can undermine their utility for decision-making. One solution is creating ensemble predictions, which potentially increase accuracy, but how best to create ES ensembles to reduce uncertainty is unknown and untested. Using ten models for carbon storage and nine for water supply, we tested a series of ensemble approaches against measured validation data in the UK. Ensembles had at minimum a 5–17% higher accuracy than a randomly selected individual model and, in general, ensembles weighted for among model consensus provided better predictions than unweighted ensembles. To support robust decision-making for sustainable development and reducing uncertainty around these decisions, our analysis suggests various ensemble methods should be applied depending on data quality, for example if validation data are available.

Participatory mapping reveals biocultural and nature values in the shared landscape of a Nordic UNESCO Biosphere Reserve

Abstract Making the right decisions for sustainable development requires sound knowledge of the values and spatial distribution of the services co‐produced by ecosystems and people. UNESCO's Man and the Biosphere programme and associated Biosphere Reserves (BRs) are key learning sites or model regions for sustainable development providing key entry points for transdisciplinary work on sustainable development. However, there is limited research exploring spatial distribution of socio‐cultural Ecosystem Service (ES) values in BRs and how those values vary according to the BR zonation. We used a transdisciplinary approach to design and implement a public participation geographical information systems (PPGIS) survey in a recently designated BR to (a) asses the spatial distribution of ES values in the different zones, (b) identify hotspots of ES values, (c) identify spatial bundles of ES values and (d) assess the social‐ecological characteristics that determine the distribution of those values. We found that stakeholders identify high biocultural ES values, mapping predominantly places for outdoor recreation, biodiversity, agricultural products and cultural heritage. Buffer zones had high agricultural and cultural heritage values while extractive values were largely absent from cores zones. We identified five spatial ES‐value bundles highlighting distinct places important for ES values related to ‘multifunctional landscapes’ located close to settlements, ‘cultural landscapes’ associated with agricultural land, ‘wild animal resources’ along the coastlines, ‘outdoor recreation and biodiversity’ and ‘passive cultural values’ widely distributed in high and moderately populated areas. We found that accessibility was important for ES values and that people value nature close to where they live. We show the importance of biocultural values in the region, and agricultural landscapes were highly valued for multiple ES values beyond agricultural products alone. We show that BRs have become places that link cultural heritage, agricultural and biodiversity values in multifunctional landscapes. We put our findings into the local context and suggest how they can inform land‐use planning and management through policies aimed at maintaining key agricultural landscapes that provide social‐ecological resilience. Additionally, we discuss the value of our study for the wider BR network and how similar work can contribute to monitoring of BR implementation. A free Plain Language Summary can be found within the Supporting Information of this article.

Optimalisasi Penetrasi Internet bagi Intensitas Pelaksanaan Rapat Anggota Tahunan (RAT) dan Peningkatan Volume Usaha Koperasi (Studi Koperasi di Provinsi Jawa Timur, Provinsi Jawa Tengah, dan Provinsi Jawa Barat)

This study aims to simulate the contribution of internet penetration to the intensity of the implementation of the Annual Membership Meeting (RAT) and the achievement of business volume by cooperatives. The research methodology is literature study and field study. Researchers conducted a study of the contribution of internet penetration, the implementation of RAT and the achievement of business volume, especially in the regions of East Java Province, Central Java Province and West Java Province from 2017 to 2019. West Java Province has not optimally utilized the contribution of internet penetration to carry out RAT and has not optimally used the internet as a business process strategy to generate business volume in the receipt of cooperative goods and services compared to the Provinces of East Java and Central Java. This research is limited to the areas of West Java, Central Java and East Java Provinces. The contribution of this research to the implementation of the adoption of information and communication technology for the board and management team of cooperatives in Indonesia in preparing to welcome the digitization of cooperatives in Indonesia so as to strengthen internal cooperatives in making business decisions for sustainable cooperative development.

The best practices of port sustainable development: a case study in Korea

ABSTRACT This paper aims to examine the main practices that shape sustainable port development in the context of Korean ports and generalize a typology of port–stakeholder decision framework for sustainable port development. First, the main practices of sustainable port development were examined through a comprehensive literature review and a holistic conceptual framework underpinned by sustainable development and stakeholder management theories. Semi-structured interviews were then conducted with 67 port managers in Korea. Lastly, FAHP was performed based on inputs from 18 port managers to analyze the priorities of the proposed sustainable port development practices. It was found that all proposed practices should be used for evaluating sustainable port development. It was also indicated that Optimized Operation Planning is the most important factor while Internal Environment Management is the least important factor perceived by Korean port managers. A typology of port–stakeholder framework for sustainable development was also generalized to assist port managers in making phased investment decisions. This research contributes to theory building by empirically identifying and validating the sustainable port development practices considering all three aspects of sustainability. It has also generalized a typology of port–stakeholder framework for sustainable development which can be used as a guideline for sustainable development decisions.