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This research was performed with the aim of determining if the emptying of latrines in a flood‐prone urban slum area would be a sustainable and profitable business for private‐sector service providers.

Monte‐Carlo analysis was used to evaluate the economic sustainability of a proposed public‐private waste transportation service. A GIS‐assisted route analysis was also performed, with participation by private and public sector stakeholders.

The analysis also showed that if a low‐cost subscription service is implemented in the area, the commercial service providers will operate at a loss in all cases, unless changes are made in the truck fuel efficiency, the operating hours of discharge sites, and the transportation network.

The research was based on service provider operations costs extrapolated from previous studies and updated through informal interviews. A thorough and transparent review of cost accounting procedures is necessary to validate the results.

This study identified challenges and potential solutions which must be addressed by practitioners in order to ensure success of a subscription‐based service.

This study adds to the existing literature by demonstrating the applicability of an analytic modeling technique based on Monte‐Carlo simulation and provides an example of how academic research can be tightly coupled with practitioner needs in order to have a direct impact on operational humanitarian projects.

Internet use has a high environmental footprint that is often overlooked by end users. This paper contributes to limiting the negative environmental footprint of Information Technology (IT) use by understanding the relationship between environmental concerns and use of IT amongst users who are aware of the environmental footprint of IT use. Second, the paper argues that taking environmental concerns into account in technology acceptance studies is relevant, even in studies concerning ordinary IT (i.e. IT not commonly classified as “green” technology).

The authors conduct two vignette-based surveys in two different countries: the USA and Belgium. Partial least squares structural equation modeling (PLS-SEM) is used to analyse the effect of environmental concerns on the intention to use the webcam during online meetings and binary logistic regression is used to analyse the relationship between environmental concerns and reported actual use of webcams.

The higher the respondents' environmental concerns, the higher their intention to use internet systems in a more environmentally responsible way, provided the respondents are aware of the environmental footprint of internet system use. Moreover, the higher the respondents’ environmental concerns, the more likely they are to use internet systems in a more environmentally responsible way.

This study is the first to distinguish “Greening of IT Use” from “Greening of IT” and “Greening by IT” and to show that environmental concerns has an impact on the way end users (intend to) use internet systems, provided the users are aware of the environmental footprint of that use.

Green lean six sigma (GLSS) is a sustainable development approach that leads to improved patient care with improved safety and quality of service to patients. This study aims to identify, study, model and analyze GLSS success factors for the Indian health-care facility.

Interpretive structural modeling (ISM) and Impact Matrix Cross-Reference Multiplication Applied to a Classification analyses have been used to understand the hierarchical structure among the GLSS success factors. This enabled the development of dependency relationships between success factors, in particular, which factors support the development of other factors.

Specifically, this study found that the success factors “commitment of management” and “financial availability” are the most critical to GLSS implementation success, as they support the development of all other success factors. Meanwhile “embedding sustainable measures at each stage of the service”; “the capability and effectiveness of real-time data collection”; and “feedback and corrective actions” most directly support the GLSS implementation in the health-care facility and serve as the final indicators of implementation progress.

The major implication of this research work lies in suggesting a direction for practitioners to execute the GLSS approach through a systematic understanding of classification and structural relationships among different enablers. This study also facilitates health-care managers to explore different GL wastes in hospitals and challenges to sustainability pursuits in health-care that assist in an organization’s efforts toward sustainable development.

This research work is the first of its kind that deals with the identification and analysis of the prominent factors that foster the inclusive implementation of GLSS within the health-care facility.

This paper describes the sustainability partnership between the City of Vancouver and the University of British Columbia (UBC) and, in particular, the co-curricular Greenest City Scholars graduate student internship program, which has been developed by the two organizations. Through the program, UBC graduate students work on projects at the City that help to advance sustainability targets. The paper aims to explore the successes, challenges and lessons learned from the program.

This case study uses literature and document review, observations, program participant evaluation surveys and project impact survey feedback.

The Greenest City Scholars program model has contributed to the sustainability goals at UBC and the City of Vancouver and has supported the partnership between the two organizations. The program has grown over its five-year history and is considered to be a central part of the partnership. Breadth of student participants from across the university and high participation from City departments have been achieved. The model is now being adapted to be delivered within other partnerships.

The experiences presented in this case study can help other higher education institutions understand how a co-curricular graduate student work experience program could help to bolster their own sustainability partnerships.

This paper makes a contribution by providing insight into the use of a graduate student program to advance the goals of a university–community sustainability partnership.

The aim of this paper is to better understand European consumers' behaviour in relation to Short Food Supply Chains (SFSCs), so as to provide insights to support their development as part of a sustainable food system. Specifically, it aims to analyse consumer purchase patterns, motivations and perceived barriers and to identify patterns of behaviour amongst different consumer groups.

An online consumer survey was conducted in 12 European countries (n = 2,419). Quantitative data analysis, including principal component analysis (PCA) and cluster analysis, was undertaken using SPSS.

Four consumer clusters are named according to their behavioural stage in terms of SFSC engagement: Unaware Unengaged, Aware Unengaged, Motivationally Engaged and Executively Engaged. Unaware Unengaged and Aware Unengaged are in the non-engagement phase of behaviour. Motivationally Engaged are motivationally activated to engage in the behaviour but fail to do so consistently. Executively Engaged is the fully engaged cluster, being motivated to act and purchasing local food on a frequent basis. The results show an interesting interplay between motivations and barriers, i.e. higher scores for motivations and lower scores for barriers do not necessarily translate into higher purchase frequency.

The research gleans insights into the contextual factors that may inhibit SFSC purchases in different consumer segments. It offers practical implications for policymakers and others seeking to develop SFSCs as part of a sustainable food system.

The coronavirus (COVID-19) pandemic has led to a surge in demand for health-care facilities, medicines, vaccines and other health-care items. The purpose of this study is to investigate different facets of integrated Green Lean Six Sigma and Industry 4.0 approach in the context of COVID-19 for better healthcare management. Integrating Green Lean Six Sigma (GLSS) and Industry 4.0 (I4.0) has the potential to meet the modern demand of health-care units and also leads to improving the quality of inpatient care with better safety, hygiene and real-time diagnoses. A systematic review has been conducted to determine the tools/techniques, challenges, application areas and potential benefits for the adoption of an integrated GLSS-I4.0 approach within health-care facilities from the perspective of COVID management. Further, a conceptual framework of integrated GLSS-I4.0 has been proposed for better COVID management.

To conduct the literature review, the authors used the preferred reporting items for systematic reviews and meta-analysis and covers relevant papers from the arrival of COVID-19. Based on the systematic understanding of the different facets of the integrated GLSS-I4.0 approach and through insights of experts (academicians and health-care personnel), a conceptual framework is proposed to combat COVID-19 for better detection, prevention and cure.

The systematic review presented here provides different avenues to comprehend the different facets of the integrated GLSS-I4.0 approach in different areas of COVID health-care management. In this study, the proposed framework reveals that the Internet of Things, big data and artificial intelligence are the major constituents of I4.0 technologies that lead to better COVID management. Moreover, integration of I4.0 with GLSS aids during different stages of the COVID management, right from diagnosis, manufacture of items and inpatient and outpatient care of the affected person.

This study provides a significant knowledge database to the practitioners by understanding different tools and techniques of an integrated approach for better COVID management. Moreover, the proposed framework aids to grab day-to-day information from the affected people and ensures reduced hospital stay with better space utilization and the creation of a healthy environment around the patient. This inclusive implementation of the proposed framework will enhance knowledge base in medical areas and provides different novel prospects to combat other medical urgencies.

To the best of the authors’ knowledge, this study is the first of its kind to review different facets of the integrated GLSS-I4.0 approach with a view of the COVID health-care perspective and provides a conceptual framework.

Internationally publicized cases of police violence against unarmed black men have led to calls for accountability in policing. Increased footage of police–public interactions, specifically through the form of police body-worn cameras (BWCs), is encouraged and considered an innovation that can improve the policing profession. However, BWC adoption is likely more feasible in big city departments than in small and rural departments, who respond to many of the same issues as their larger counterparts. The purpose of this study is to explore perceptions of BWC among leaders of small and rural police departments.

Using a mixed methods approach, the authors surveyed 349 chiefs of small and rural Pennsylvania police departments and conducted qualitative follow-up interviews with 53 chiefs.

The results indicate that both adopters and non-adopters esteem BWC in a positive light, particularly toward the ability to improve professionalism and police–community relations. Other findings and implications of these results will be discussed.

This study focuses on small and rural police departments, which make up the majority of police departments but are often understudied.

Research on human trafficking largely focuses on large, urban areas, yet it is a problem in small, rural areas. Police in these areas must have the training to identify human trafficking and resources to combat the issue – both of which may be lacking in small, rural areas. The purpose of this project is to explore police chiefs' perspectives on human trafficking in small, rural areas.

A mixed-methods approach was used to assess Pennsylvania police chiefs' understanding of human trafficking and their perspective of the extent of the problem in their area. First, 349 police chiefs completed an online survey during the summer of 2020. Follow-up in-depth interviews were conducted with 52 police chiefs.

Most chiefs believed human trafficking is a problem in Pennsylvania (81%) or in their local area (12%). Logistic regression analysis indicated chief experience, department budget and the number of employees affect small and rural police chief perceptions of human trafficking. Qualitative analyses identified three themes of police chief perceptions of human trafficking: conflation with prostitution, definitional debates and competing beliefs about prevalence. Training on identifying human trafficking would benefit small and rural police departments. Chiefs recommended outside assistance investigating human trafficking cases and other state-level resources would be helpful.

Scant research exists on small and rural police departments in the United States, especially in regards to human trafficking. This study contributes to the literature by addressing this gap with a mixed-methods approach.

The purpose of this study was to improve the quoting, scheduling, invoicing and paying for campus office moves at a university. The Lean Six Sigma project goal was to improve the campus office move process by making it less complicated, free-up program managers’ time and pay the vendor on time.

The team used the Lean Six Sigma Define-Measure-Analyze-Improve-Control methodology to improve the process.

The average time from the campus move to when the invoice was paid improved by 27%, with an improved median of 16%. The standard deviation was greatly reduced by 51%. The average invoiced date to paid date remained statistically the same, and the median increased from 20 to 30 days, due to a policy change to move the target from 20 to 30 days. The standard deviation of the invoice to paid date was greatly reduced by 38%. This was a successful project because the sponsors were on-board from the beginning and included the process owners in the improvement effort.

Other higher education institutions or other industry areas with a similar process can implement this methodology and processes outlined in this case study to improve efficiency and cost effectiveness and as a guide for improving other processes within institutions.

This study aims to evaluate the color accuracy of HP Jet Fusion 580 3D printing, comparing 3D-printed outcomes against original digital input colors.

A custom cyan, magenta, yellow and black (CMYK) and red, green, blue (RGB) color chart was applied to the top, bottom and side surfaces of a 3D model. Four of each model were 3D-printed on a HP Jet Fusion 580, and half the samples were finished with a cyanoacrylate gloss surface finish, while half were left in raw form. A spectrophotometer was used to document CIELAB (L*a*b*) data, and comparisons made to the original input colors, including calculation of ΔE.

The CMYK samples were significantly more accurate than RGB samples, and grayscale samples in both color spaces were the most accurate of all. Typically, CMYK swatches were darker than the input values, and gloss samples were consistently darker than raw samples. The chromaticity (a*b*) range was found to be significantly smaller than what can be achieved digitally, with highly saturated colors unable to be produced by the printer.

This is the first study, to the best of the authors’ knowledge, to characterize the full color spectrum possible with the HP Jet Fusion 580, recommending that designers use the CMYK color space when applying colors and textures to 3D models. A quick-reference color chart has been provided; however, it is recommended that future research focus on developing a color management profile to better map digital colors to the capabilities of the printer.