A Proposed Metrics Based on Sustainable Development Goals (SDGs) for Public Self-Service Machines

Abstract

With the growing environmental issues, the World Commission on Environment and Development (WCED) has developed a strategy for sustainable development that will enable the present generation to meet its needs for development without harming the environment for future generations. By introducing a 24-h self-service via Public Self-Service Machines, several issues can be alleviated, such as the congestion in the traditional service environment, to support specific services outside of the traditional office hours, and to allow citizens to feel that the government is committed to providing convenience and mindful public services. However, few existing studies have examined sustainability as a fundamental attribute of these Public Self-Service Machines. This lack of focus would result in Public Self-Service Machines not being sustainable in the long run. Therefore, further research on how to design and measure sustainable development attributes for Public Self-Service Machines is necessary to address this issue effectively. In this paper, the sustainable development attributes of Public Self-Service Machines based on the 17 Sustainable Development Goals (SDGs) are firstly presented. Then, a questionnaire survey was conducted to collect and analyze the views of industry experts to propose 13 metrics to measure the sustainable development attributes of Public Self-Service Machines.

1. Introduction

With the increasing environmental issues, the World Commission on Environment and Development (WCED) has proposed a strategy for Sustainable Development to enable current generations to meet their development needs to support future generations’ survival and development [1]. In 2015, the United Nations convened a Sustainable Development Summit, where “Transforming our world: the 2030 Agenda for Sustainable Development” was adopted. The agenda includes the 17 Sustainable Development Goals (SDGs) and emphasizes the critical role of science in achieving the 17 SDGs adopted by the international community [2]. The integration of sustainable development with specific industries has become a hot research topic [3]. Additionally, as network technology advances through the introduction of the Internet of Things, and Artificial Intelligence, Self-Service Machines are becoming increasingly dominant in daily activities, especially in the public sector. Public Self-Service Machines can provide “24-h self-service”, alleviating the dilemma of overcrowding in government departments and supporting after-hours services for citizens. This indirectly allows the citizens to have a sense of the government’s commitment to providing convenient and considerate public services [4]. Furthermore, during the COVID-19 pandemic, Public Self-Service has effectively reduced person-to-person contact and the spread of the coronavirus [5]. Therefore, the government regards the provision of high-quality and efficient Public Self-Service as an important part of improving its governance capacity [6,7,8]. As such, there is an increase in the research and development of Self-Service Machines in relevant areas within the academia and industry domains [4].

So far, the design approach of the Self-Service Machine can be summarized by two categories. The first category is to design a Self-Service Machine that meets the needs of target users from the user’s perspective. For example, Chen et al. [4] explored the perspective of consumer value theory and proposed that three factors—personalization, aesthetics, and time spent in AI-based operations—would significantly impact user experience. Therefore, these three factors must be considered when designing any Self-Service products. Shi et al. [9] used both Kansei Engineering theory and Service Design theory to conduct qualitative and quantitative research on the interface of hospital Self-Service Machines. Based on the interface service function block and key perception vocabulary, they summarize the improvement strategy by improving the interface readability, optimizing interface interaction logic, and strengthening interface guidance. Similarly, Wang et al. [10] studied the usability and ease of use for elderly users, and then proposed a Self-Service Machine design scheme based on behavior trajectory complexity, task completion time, and other indicators. For elderly users, Shang et al. [11] designed the Self-Service Machine with four aspects of humanized hardware design, interface visibility, operation process, and operation feedback.

The second category is designed from a functional point of view for the machine. For example, Alnowaini et al. [12] designed a Self-Service Machine for the banking industry. This machine is used for query, withdrawal, and other functions. Multiple subsystems are specially designed to work together to detect and recognize the currency notes of Yemen. Xing et al. [13] designed the hardware, external service interface, and application software of the Self-Service Machine from the perspective of smart campus function requirements. Yigitbas et al. [14] developed a distributed multi-channel Self-Service system using a model-based integration method. Liu et al. [15] designed a composite Self-Service terminal system from the perspective of business functions to realize complex Self-Service functions. However, few studies have considered sustainability as an essential attribute of a Public Self-Service Machine that should be integrated during the machine’s development. Failure to integrate this attribute may lead to the Public Self-Service Machine industry failing to align with the 17 Sustainable Development Goals (SDGs) set by the United Nations. As the issue of sustainable development is a key focus on the global level, it is essential to design Public Self-Service Machines with this attribute in mind. A key step in this process is to examine how to describe and measure the sustainable development attributes of Public Self-Service Machines. Based on the research gaps, the following research questions are posed: (1) What are the essential sustainable development attributes for Public Self-Service Machines based on the United Nation’s Sustainable Development Goals (SDGs)? (2) How do we measure the sustainable development attributes that have been integrated into these Public Self-Service Machines?

In this work, the specific content of sustainable development attributes of Public Self-Service Machines is examined in relation to the 17 Sustainable Development Goals (SDGs). This is followed by a questionnaire survey used to collect and analyze the views of industry experts to propose relevant metrics to measure the sustainable development attributes of Public Self-Service Machines.

2. Experimental

2.1. Experimental Flow

The experimental flow was designed as shown in Figure 1 to assist in answering the proposed objectives. Firstly, the UN Sustainable Development Goals were analyzed to select the specific sustainable development attributes for Public Self-Service Machines. Then, a questionnaire was designed and conducted based on this specific content. Subsequently, the collected questionnaire data were analyzed. Finally, the metrics of sustainable development attributes based on the SDGs were obtained based on the analysis results.

2.2. Analyze the Sustainable Development Goals

The concept of sustainable development emerged during the 20th century’s global environmental crises. The world’s population has recognized that if environmental concerns such as ozone depletion, acid rain pollution, and biodiversity loss are not addressed, human society will perish. On 5 June 1972, the United Nations convened the “Conference on the Human Environment” in Stockholm on the idea of the “human environment”, and discussed the notion of sustainable development for the first time. Over the next decade or two, countries developed hundreds of definitions of “sustainable development”, on international, regional, municipal, and specially specified levels [16]. In 2015, the United Nations held a Sustainable Development Summit and adopted the notion of “Transforming our world: the 2030 Agenda for Sustainable Development”. The agenda contains 17 Sustainable Development Goals (SDGs) and stresses that science should play a fundamental role in implementing the 17 SDGs endorsed by the international community [2]. Sustainable development is a major trend in today’s production processes, and it is gaining popularity among academics, professionals, and policymakers [3]. Therefore, the development, and use of the Public Self-Service Machine must also be consistent with the goal of sustainable development. Based on the interconnection and interaction between human activities and the natural environment and the social environment, the SDGs are composed of 17 Goals, each containing a series of targets. Based on the selection criteria for SDGs and their targets (refer to

Table 1. The selection criteria for SDGs and their targets.

Selection Criteria	Examples
If there is a “a kind of” relationship between the content of the target and the Public Self-Service Machine.	Target 9.1 is checked because Public Self-Service Machines are a kind of infrastructure.
If all or some of the functions described in the target are required to be performed by the public Self-Service Machine.	Target 11.7 is selected because the public services provided by Public Self-Service Machines are part of the functions required to build safe, inclusive, accessible, green, and public spaces.
If there is anything described in the target, then that is a possible attribute for a Public Self-Service Machine.	Because sustainable management and efficient use of natural resources is a possible attribute for a Public Self-Service Machine, target 12.2 is checked.

), the Goals and their targets related to Public Self-Service Machines were filtered out. A specific analysis was then carried out for each of these targets to obtain the nine candidate requirements for developing Public Self-Service Machines on these targets. The results of the analysis are shown in

Table 2. The candidate requirements for sustainable development attributes of Public Self-Service Machines on SDGs.

Goal	Targets of Goal	The Candidate Requirements for Sustainable Development Attributes of Public Self-Service Machines
Goal 9: Build resilient infrastructure, promote sustainable industrialization, and foster innovation	9.1 Develop quality, reliable, sustainable, and resilient infrastructure, including regional and transborder infrastructure, to support economic development and human well-being, with a focus on affordable and equitable access for all 9.4 By 2030, upgrade infrastructure and retrofit industries to make them sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies and industrial processes, with all countries taking action in accordance with their respective capabilities	1. Public Self-Service Machines should be of high quality, reliable, and resilient. 2. Public Self-Service Machines should be affordable and have equitable access for all. 3. Public Self-Service Machines should be sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies and industrial processes.
Goal 11: Make cities inclusive, safe, resilient, and sustainable	11.7 By 2030, provide universal access to safe, inclusive, accessible, green, and public spaces, in particular for women and children, older persons, and persons with disabilities	4. Public Self-Service Machines should provide safe, inclusive, accessible, and green services for all, especially women, children, the elderly, and people with disabilities.
Goal 12: Ensure sustainable consumption and production patterns	12.2 By 2030, achieve the sustainable management and efficient use of natural resources 12.4 By 2020, achieve the environmentally sound management of chemicals and all wastes throughout their life cycle, in accordance with agreed international frameworks, and significantly reduce their release to air, water, and soil in order to minimize their adverse impacts on human health and the environment 12.5 By 2030, substantially reduce waste generation through prevention, reduction, recycling, and reuse 12.6 Encourage companies, especially large and transnational companies, to adopt sustainable practices and to integrate sustainability information into their reporting cycle	5. Public Self-Service Machines should use natural resources efficiently. 6. Public Self-Service Machines should have functions to support the sustainable management of the natural resources consumed. 7. Achieve the environmentally sound management of chemicals and all wastes related to Public Self-Service Machines throughout their life cycle, by agreed international frameworks, and significantly reduce their release into the air, water, and soil to minimize their adverse impacts on human health and the environment. 8. In the production and use of Public Self-Service Machines, waste generation needs to be significantly reduced through prevention, reduction, recycling, and reuse. 9. Public Self-Service Machines should be able to collect statistics and generate sustainability information.

.

2.3. Questionnaire Survey

2.3.1. Questionnaire Question Design

Questionnaire surveys are a very efficient way of collecting expert opinions. Chen et al. [4] adopted the questionnaire method to study the AI-based self-service technology in public service delivery. Additionally, Mashur et al. [17] used a questionnaire to study the attributes of fodder bank sustainability. Therefore, a questionnaire survey was used to collect expert opinions in the field of Public Self-Service Machines for this paper. Firstly, two questions were designed to collect relevant background information from the participants. Then, 15 questionnaire questions were designed (refer to

Table 3. Questions in the questionnaire based on the requirements for the development of Public Self-Service Machines on 17 SDGs.

Question ID	Question Description
Question 3	Do Public Self-Service Machines need to have sustainability features?
Question 4	When examining the sustainable development attributes of the Public Self-Service Machine, should the quality of the Public Self-Service Machine be one of the metrics?
Question 5	When examining the sustainable development attributes of the Public Self-Service Machine, should the reliability of the Public Self-Service Machine be one of the metrics?
Question 6	When examining the sustainable development attributes of the Public Self-Service Machine, should the resilience of the Public Self-Service Machine be one of the metrics?
Question 7	When examining the sustainable development attributes of the Public Self-Service Machine, should the cost of using the Public Self-Service Machine be one of the metrics?
Question 8	When examining the sustainable development attributes of the Public Self-Service Machine, should the resource-use efficiency of the Public Self-Service Machine be one of the metrics?
Question 9	When examining the sustainable development attributes of the Public Self-Service Machine, should the adoption of clean and environmentally sound technologies and industrial processes be one of the metrics?
Question 10	When examining the sustainable development attributes of the Public Self-Service Machine, should the environmentally sound treatment of waste generated by the public Self-Service Machine be one of the metrics?
Question 11	When examining the sustainable development attributes of the Public Self-Service Machine, should the recycling of the Public Self-Service Machine be included as one of the metrics?
Question 12	When examining the sustainable development attributes of the Public Self-Service Machine, should the reuse of the Public Self-Service Machine be included as one of the metrics?
Question 13	When examining the sustainable development attributes of the Public Self-Service Machine, should the security of the Public Self-Service Machine be included as one of the metrics?
Question 14	When examining the sustainable development attributes of the Public Self-Service Machine, should inclusive services be included as one of the metrics?
Question 15	When examining the sustainable development attributes of the Public Self-Service Machine, should accessible services be included as one of the metrics?
Question 16	When examining the sustainable development attributes of the Public Self-Service Machine, should adequate support for women, children, the elderly, people with disabilities, etc., be included as one of the metrics?
Question 17	When examining the sustainable development attributes of the Public Self-Service Machine, should the ability to collect statistics and generate sustainability information be one of the metrics?

). Of these, question 3 was used to gather participants’ opinions on whether Public Self-Service Machines should have sustainability features. Questions 4 to 17 were designed based on the candidate requirements for sustainable development attributes of Public Self-Service Machines on 17 SDGs. Both questions 15 and 16 are essentially about the characteristics of accessible services, and participants’ responses to both questions should be consistent, so these two questions can also be used to check whether participants’ opinions are valid. A 5-point scale was used for statistical analysis to design these questions [17] where a value of 1 means Strongly Disagree and a value of 5 means Strongly Agree. Finally, an open-ended question was also included to allow the participants to express their opinions on the selected 15 concepts.

2.3.2. Criteria for Inclusion and Exclusion of Participants

In the Public Self-Service Machine industry, these institutions are usually included: Manufacturers of Public Self-Service Machine components, Public Self-Service Machine system integrators, Public Self-Service Machine sellers, Users of Public Self-Service Machines, and Public Self-Service Machine recycling companies. Of these, the Public Self-Service Machine system integrator is a company that can implement system integration for industry users. System integration includes equipment system integration and application system integration. The system integrator is therefore an important link in the Public Self-Service Machine industry, with close links to sellers, component manufacturers, users, and recycling companies. A typical business process is as follows: the system integrator purchases components from component manufacturers and then assembles the hardware into a self-service machine and develops the application software. This is then sold to the user through the seller. Often the seller will delegate the after-sales service to the system integrator. Therefore, the system integrator is also closely linked to the user.

To further clarify the selection criteria of the participants, the relationship between candidate demands and work content was analyzed. The results of the analysis are shown in

Table 4. Degree of relevance between candidate requirements and work content.

Candidate Requirement (CR)	Hardware Design and Manufacturing	Software Design and Development	Administration	Operation and Maintenance	Human Resources
CR1	High	High	High	High	Low
CR2	High	Medium	High	High	Low
CR3	High	High	High	Medium	Low
CR4	High	High	High	High	Low
CR5	High	High	High	Medium	Low
CR6	High	High	High	Medium	Low
CR7	High	High	High	Medium	Low
CR8	High	High	High	High	Low
CR9	High	High	High	Medium	Low

. In these institutions, hardware design and manufacturing, software design and development, administration, and operation and maintenance work are closely linked to the candidate requirements for sustainable development attributes of Public Self-Service Machines. Therefore, participants need to be screened according to the criteria (

Table 5. Screening criteria for participants.

Screening Criteria	Range of Values for the Criteria
Type of institution	Manufacturer of Public Self-Service Machine components Public Self-Service Machine system integrator Public Self-Service Machine seller User of Public Self-Service Machines Public Self-Service Machine recycling companies
Technical field	Hardware design and manufacturing Software design and development Operation and maintenance Administration

).

2.3.3. Distribution Method of Questionnaires

For the questionnaire survey, the WJX system was selected for the generation and distribution of the questionnaire. The WJX system is a large survey collection company in China that not only has an efficient questionnaire software system that can design and collect questionnaires online, but also has extensive data security and confidentiality clauses included in their platform. This may increase the respondents’ willingness to participate in a survey because of the increased privacy or security.

A precise distribution method based on the industry sector was adopted, whereby the distribution center was the company engaged in the integration of the Public Self-Service Machine system, the sales company, or the user. The management and professional staff of the organization and the component manufacturers, customers, and other organizations with which it had business connections were the preferred respondents. They were then asked to distribute the questionnaire to other companies in the industry with whom they were associated. This allowed for the efficient and accurate distribution of the questionnaire. The WJX system works well with China’s mainstream social networking software, for example, questionnaires can be forwarded via the sharing function in WeChat or QQ software.

Beijing Hongtai Heili Technology Co., Ltd. and Chongqing Gaoxin District Government Affairs Service Center were used as distribution centers for this survey. Beijing Hongtai Heli Technology Co., LTD., founded in 2009, is a leading service manufacturer committed to intelligent and intelligent multimedia self-service terminal equipment solutions in China. Chongqing is one of the four municipalities directly under the Central Government in China. Because government affairs service centers are an important platform for strengthening government services, improving administrative efficiency, and providing quality, convenient, and efficient services to the people, Chongqing has made them a key construction project for the government. A variety of Self-Service Machines have been deployed, which can provide many self-service functions such as real estate registration, social affairs, public security, taxation, and so on. These organizations can be used as representatives of the public self-service sector and are therefore used as questionnaire distribution centers.

2.3.4. Analyze Survey Data

After completing the returned questionnaires, the questionnaire data were analyzed using IBM SPSS Statistics 26 software. Firstly, the reliability of the survey data was analyzed using Cronbach’s alpha coefficient, Average Variance Extracted, and Composite Reliability as reliability evaluation indicators. Cronbach’s alpha coefficient is a reliability coefficient that measures the internal consistency of a test. Average Variance Extracted is a statistical measure that tests the internal consistency of structural variables. Composite Reliability is the reliability of a combined variable, which is a new variable consisting of the sum of more than one variable. These indicators can be used to test the reliability of the scale data. Secondly, the respondents’ background data, scale data, and data collected from open-ended questions were analyzed. Finally, based on the analysis of the previous questionnaires, the relevant metrics were designed to measure the sustainable development attributes of Public Self-Service Machines.

3. Results and Discussion

3.1. Reliability Analysis

The Cronbach’s alpha for the 15 scales in the survey data was calculated using SPSS Statistics 26 as 0.978 (

Table 6. Reliability statistics.

Cronbach’s Alpha	Cronbach’s Alpha Based on Standardized Items	N of Items
0.978	0.978	15

). This value is greater than 0.9 and is close to 1, indicating a high degree of consistency [18], which indicates that the reliability of this data is acceptable.

The Average Variance Extracted and Composite Reliability calculated for the 15 scales in the survey data are 0.824 and 0.986 (

Table 7. Average Variance Extracted and Composite Reliability.

Item	Value
Kaiser-Meyer-Olkin Measure of Sampling Adequacy	0.940
Sig. of Bartlett’s Test of Sphericity	0.000
Factor Loadings	{0.860,0.894,0.932,0.921,0.884,0.933, 0.943,0.915,0.926,0.919,0.902,0.923, 0.910,0.868,0.881}
Average Variance Extracted	0.824
Composite Reliability	0.986

). The Average Variance Extracted is greater than 0.5 and the Composite Reliability is greater than 0.6, which indicates that the internal consistency of the structural variables and the Composite Reliability of the questionnaire data are appropriate.

3.2. Background of the Questionnaire Participants

A total of 120 people from different technical fields and different types of institutions provided their feedback through this questionnaire. From this number, 51 were from the Manufacturer of the Public Self-Service Machine component, of which 32 were in hardware design and manufacturing, 10 in software design and development, 5 in operation and maintenance, and 4 in administration. There were 28 respondents whose institution type was Public Self-Service Machine system integrator. Seven of them were in hardware design and manufacturing; 11 in software design and development; 6 in operation and maintenance, and 4 in administration. Sixteen respondents work for Public Self-Service Machine sellers, of which 2 work in software design and development, 4 in operation and maintenance, and 10 in administration. Twenty-five respondents were users of Public Self-Service Machine, including 3 in hardware design and manufacturing, 3 in software design and development, 9 in operations and maintenance, and 10 in administration (Figure 2).

The largest number of questionnaire participants, 42.5%, were from Manufacturers of Public Self-Service Machine components and 62.7% of them were involved in Hardware design and manufacturing. This is in line with the fact that in the real world, the number of component manufacturers in the Public Self-Service Machine chain is high and that a relatively large number of professionals in these companies are involved in Hardware design and manufacturing.

Based on the participants from the Public Self-Service Machine system integrator, 39.3% were involved in Software design and development, which is 14.3% higher than the number involved in Hardware design and manufacturing.

The low number of participants from organizations in the sales category suggests that these organizations are less concerned with the sustainability features of Public Self-Service Machines.

Most participants from user organizations are involved in operation, maintenance, and management, which is in line with the actual situation of the user organizations.

Another non-negligible phenomenon was the low response rate collected from the participants of the Public Self-Service Machine recycling companies. According to the set distribution method, questionnaires are sent from the distribution center to the organizations with whom they are associated with. It is therefore likely that the lack of returned questionnaires is due to the low number or small size of companies in the Public Self-Service Machine chain that carry out Public Self-Service Machines recycling operations. This shows that Public Self-Service Machine recycling centers are not sufficiently developed at present. Therefore, although there were no responses from businesses engaged in the type of recycling of Public Self-Service Machines in the questionnaire survey, recycling should still be included when studying the sustainable development attributes of Public Self-Service Machines.

3.3. Industry Experts’ Views on the Need for Sustainability Features in Public Self-Service Machines

Around 52.50% of industry experts believe that Public Self-Service Machines must have sustainability features. A total of 20.80% of industry experts believe that Public Self-Service Machines need to have sustainability features (Figure 3). Of the group of participants, 73.30% of them supported the sustainability of Public Self-Service Machines being included in the development. Therefore, this shows that it is necessary to study the sustainability characteristics of Public Self-Service Machines.

3.4. Industry Experts’ Views on Metrics for the Sustainable Development Attribute of Public Self-Service Machines

The percentage of industry experts who thought it was very necessary to use these metrics ranged from 45.80% to 50.80%; The number of industry experts who considered the adoption of these metrics to be necessary was between 20.00% and 30.80%; The proportion of industry experts who believed that the adoption of these metrics was not necessary ranged from 2.50% to 8.30%; the ratio of industry experts who felt that the use of such metrics was not necessary at all was in the range of 3.30% to 10.00% (Figure 4).

Most industry experts support the use of these metrics to measure the sustainable development attribute of Public Self-Service Machines. Combining the percentage of industry experts who felt it was very necessary and necessary to adopt the given metrics provided a range of 70.80% to 80.00% of industry experts who support the adoption of these metrics. In addition, for Question 15, 72.50% of industry experts were supportive. For Question 16, 70.80% of industry experts were supportive, and Question 16 is a specific formulation of Question 15 on accessibility. The high level of agreement between the data on these two questions indicates the high quality of the questionnaire. In conclusion, this suggests that it is reasonable and necessary to adopt these metrics to measure the sustainable development attributes of Public Self-Service Machines.

3.5. Other Suggestions from Industry Experts

Additionally, around 80.83% of industry experts did not provide an opinion; 13.33% of industry experts entered “None”; “Must be strictly enforced” was filled in by 0.83% of industry experts; 0.83% of industry experts filled in the “Needs to be managed”; 0.83% of the industry experts wrote: “The convenience of location, Aesthetics of The machine, And keeping up to date with the content of queries”; 0.83% of industry experts answered “After-sales operation and maintenance need to respond quickly”; 0.83% of industry experts completed “As soon As possible”; 0.83% of industry experts put in “Data security and confidentiality are a priority”; 0.83% of industry experts responded “Operations and maintenance quality assessment” (Figure 5).

Most industry experts felt that the indicators included in the previous questionnaire were sufficient to test the sustainable development attribute of Public Self-Service Machines and that no additional indicators were needed. The recommendations made by a few industry experts, such as “Must be strictly enforced”, “Needs to be managed”, “As soon as possible”, “Operations and maintenance quality assessment”, and “After-sales operation and maintenance need to respond quickly”, are in essence part of a national or corporate regulation or management system to promote sustainable development. They should not be used as metrics to assess the sustainable development attribute of the Public Self-Service Machine itself. “The convenience of location”, as suggested by some industry experts, is something that needs to be considered when planning and building projects for users of Public Self-Service Machines. The “aesthetics of the machine”, as suggested by some industry experts, should be one of the specific items of quality metric for the sustainable development attribute of the Public Self-Service Machine. In response to the advice of some industry experts to “keep up to date with the content of queries”, an effective architecture should be used to design services that correspond to sustainable development attributes when creating them. “Data security and confidentiality are a priority” should be included as a security metric in the sustainable development attribute of the Public Self-Service Machine. Therefore, it can now suggest that the metrics included in the questionnaire questions are sufficient to test the sustainable development attribute of the Public Self-Service Machine.

3.6. The Metrics of Sustainable Development Attributes

The results of the questionnaire and the discussion indicate that Question 4 to Question 17 of the questionnaire contain indicators to measure the sustainability attributes of Public Self-Service Machines. Of these, Question 15 and Question 16 are different statements of the same metric. Therefore, 13 metrics have been summarized to measure the sustainability attributes of Public Self-Service Machines (

Table 8. The metrics of the sustainable development attribute of Public Self-Service Machines.

The Attribute

The Metrics

The sustainable development attribute of Public Self-Service Machines

Metric 1: The quality of the Public Self-Service Machine Metric 2: The reliability of the Public Self-Service Machine Metric 3: The resilience of the Public Self-Service Machine Metric 4: The cost of using the Public Self-Service Machine Metric 5: The resource-use efficiency of the Public Self-Service Machine Metric 6: The adoption of clean and environmentally sound technologies and industrial processes Metric 7: The environmentally sound treatment of waste generated by the public Self-Service Machine Metric 8: The recycling of the Public Self-Service Machine Metric 9: The reuse of the Public Self-Service Machine Metric 10: The security of the Public Self-Service Machine Metric 11: Inclusive services Metric 12: Accessible services Metric 13: The ability to collect statistics and generate sustainability information

). Each Goal in the SDGs contains specific targets, cumulatively, over 100 of these targets. However, these targets are still presented at a macro level, and it is difficult to directly associate Public Self-Service Machines with these targets in public self-service. However, it is possible to specify at a micro level using a lower level, relatively specific set of 13 metrics. This would be more feasible to determine if the Public Self-Service Machine fulfills the sustainability requirements.

4. Conclusions

From the perspective of the United Nations, sustainable development is of great significance to human society. Sustainable Public Self-Service Machines have become an important emerging area of research due to their advantages of being able to improve the efficiency and effectiveness of government governance, as well as achieving the prevention of the spread of COVID-19 and various possible future viruses among humans by reducing human interaction. However, few existing studies have examined sustainability as a fundamental attribute for these Public Self-Service Machines. This lack of focus would result in Public Self-Service Machines not being sustainable in the long run. This work presents the specific content of sustainable development attributes of Public Self-Service Machines based on the 17 Sustainable Development Goals (SDGs). Then, a questionnaire was used to collect and analyze industry experts’ opinions, and 13 metrics were proposed to measure the sustainable development attributes of Public Self-Service Machines. The selection of suitable metrics to measure the sustainability attributes of Public Self-Service Machines is not only a meaningful research effort, but also has great engineering applications. These metrics can help enterprises to develop sustainable Public Self-Service Machines. In addition, the research methodology and findings can also encourage research work on Self-Service Machines in other fields.

As the results are more closely related to the national conditions in China, future surveys in other countries would allow for more holistic data to be obtained. This shortcoming, however, will not impact the application of this study’s results. This is because in Goal 16 of the 17 SGDs, “Promote just, peaceful and inclusive societies”, states that sustainable development needs to consider the differences between countries and the different levels of development.