The purpose of this paper is to do a systematic assessment and testing of identified human rights norms alongside social determinant approaches in relation to identified…
The purpose of this paper is to do a systematic assessment and testing of identified human rights norms alongside social determinant approaches in relation to identified health issues of concern in four Latin American countries (Argentina, Chile, Paraguay and Uruguay) to show how social determinants and human rights frameworks improve population health.
To do so, in the first part the authors analyze the inequalities both between and within each of the selected countries in terms of health status and health determinants of the population. Then, in the second section, the authors analyze the level of recognition, institutionalisation and accountability of the right to health in each country.
From the data used in this paper it is possible to conclude that the four analysed countries have improved their results in terms of health status, health care and health behaviours. This improvement coincides with the recognition, institutionalisation and creation of accountability mechanisms of human rights principles and standards in terms of health and that a human rights approach to health and its relation with other social determinants have extended universal health coverage and health systems in the four analysed countries.
Despite of the importance of the relation between human rights and social determinants of health, there are few human right scholars working on the issues of social determinants of health and human rights. Most of the literature of health and human rights has been focussed specific relations between specific rights and the right to health, but less human right scholar working on social determinants of health. On the other hand, just a few epidemiologists and people working on social medicine have actually started to use a universal human rights frame and discourse. In fact, according to Vnkatapuram, Bell and Marmot: “while health and human rights advocates have from the start taken a global perspective, social medicine and social epidemiology have been slower to catch up”.
Smart cities show a “booming” trend both in the academia and the industry in recent years. Scholars across the world have been investigating how new technologies are…
Smart cities show a “booming” trend both in the academia and the industry in recent years. Scholars across the world have been investigating how new technologies are applied to develop new services to the inhabitants and cities all over the world also address the “smart cities” challenges by promoting policymaking and governance. This paper aims to conduct in-depth research on smart cities by combining the study of governance policy study and information technology study.
This paper empirically mapped the trends of smart city development, outstanding scholars and hot topics about smart cities by analyzing important references using CiteSpace. The authors visualized references and topics to analyze smart city research, based on empirical data from Web of Science. Furthermore, two most important research branches – topics from smart city governance research and those from information systems (IS) research were studied, respectively.
First, the authors mapped the development of research and divided the development into three different stages. Second, the authors explored important, influential and instructive publications and publications’ attributes including authors, institutions, journals and topics. Third, the authors found there are different characteristics between the IS group and the governance group in publication situations, influential institutions, journals and authors, although the research points of the two branches are overlapping and fragmented. Finally, the authors proposed important topics, which include “internet of things (IoT)”, “big data”, “smart city systems” and “smart city management” and the authors predicted that “IoT” and “smart city challenge” would be future trends in recent years.
This study is an innovative research of its category because it visualized the development of smart city research, analyzed both governance and technology branches of smart city research synthetically using CiteSpace and forecasted future trends of smart city research by topics analysis and visualization of evolution.
Despite several efforts during the last years, the web model and semantic web technologies have not yet been successfully applied to empower Ubiquitous Computing…
Despite several efforts during the last years, the web model and semantic web technologies have not yet been successfully applied to empower Ubiquitous Computing architectures in order to create knowledge‐rich environments populated by interconnected smart devices. In this paper we point out some problems of these previous initiatives and introduce SoaM (Smart Objects Awareness and Adaptation Model), an architecture for designing and seamlessly deploying web‐powered context‐aware semantic gadgets. Implementation and evaluation details of SoaM are also provided in order to identify future research challenges.
Narrates the discussion between Juan (a corporate executive of a multinational company) and Audrey (an independent environmental consultant) when they sit next to each…
Narrates the discussion between Juan (a corporate executive of a multinational company) and Audrey (an independent environmental consultant) when they sit next to each other on a flight. Explains, through the dialogue, some of the environmental pitfalls companies can encounter when basing operations in the USA, such as regulations relating to clean air, clean water, emissions, toxic pollutants, land use restrictions, species protection plans etc.). Makes the point that it is individuals who face civil and criminal penalties for breaking these regulations, not the company. Provides an overview of US environmental regulations and recommends that companies can avoid falling foul of the law through education, training and taking legal advice. Mentions ISO 14000 and 14001 environmental standards as a potential way forward, although they do not yet carry any weight under US law.
Purpose — Fare validation data from transit smart card automatic fare collection (AFC) systems have properties that align with the direction of large-scale mobility…
Purpose — Fare validation data from transit smart card automatic fare collection (AFC) systems have properties that align with the direction of large-scale mobility surveys and the evermore demanding data needs of the transit industry. In addition to applications in transit planning and service monitoring, travel patterns and behaviour can effectively be studied by exploiting the continuous stream of observations from the same card. The paper proposes a methodology to enrich fare validation data in order to generate information that is hard to obtain with traditional travel surveys.
Methodology/approach — The methodology aims to synthesize individual-level attributes by summarizing multi-day validation records from each card. These new dimensions are then transposed to various levels of aggregation and studied simultaneously in multivariate analysis. The methodology can also be applied to synthesize other multi-day attributes and is transferable to other modes and other travel behaviour studies.
Findings — Results show that validation data can effectively be used to measure the distribution of travel patterns in time and space as well as the variation of those phenomena over time. The paper provides several examples based on millions of validation records from the metro sub-network of Montréal, along with interpretations and some practical implications.
Research limitations/implications — Limitations and bias regarding the data and the methodology as well as the strategies to handle them are discussed within the context of passive travel survey and travel behaviour studies.
Practical implications — Practitioners in transit planning, operations, marketing and modelling can benefit from studying the increasingly accessible and massive smart card datasets through a deeper understanding of multi-day travel patterns and behaviour of transit users.
Originality/value — This paper outlines a data modelling approach and simple-to-implement methodology which exploit the multi-day property of fare validation data from a smart card AFC. The concept of multi-day attributes is introduced. The analyses show that the approach is effective for extracting information on travel behaviour and its variation which would otherwise be hard to obtain through traditional travel surveys, opening up another dimension of this data source for practitioners and transport modellers alike.
Purpose: The purpose of this chapter is to review and critically evaluate robots, artificial intelligence and service automation (RAISA) applications in the restaurant…
Purpose: The purpose of this chapter is to review and critically evaluate robots, artificial intelligence and service automation (RAISA) applications in the restaurant industry to educate professors, graduate students, and industry professionals.
Design/methodology/approach: This chapter is a survey of applications of RAISA in restaurants. The chapter is based on the review of professional and peer-reviewed academic literature, and the industry insight section was prepared based on a 50-minute interview with Mr. Juan Higueros, Chief Operations Officer of Bear Robotics.
Findings: Various case studies presented in this chapter illustrate numerous possibilities for automation: from automating a specific function to complete automation of the front of the house (e.g., Eatsa) or back of the house (e.g., Spyce robotic kitchen). The restaurant industry has already adopted chatbots; voice-activated and biometric technologies; robots as hosts, food runners, chefs, and bartenders; tableside ordering; conveyors; and robotic food delivery.
Practical implications: The chapter presents professors and students with a detailed overview of RAISA in the restaurant industry that will be useful for educational and research purposes. Restaurant owners and managers may also benefit from reading this chapter as they will learn about the current state of technology and opportunities for RAISA implementation.
Originality/value: To the best of the authors’ knowledge, this chapter presents the first systematic and in-depth review of RAISA technologies in the restaurant industry.
The purpose of this treatise is to present an analysis of the importance of positive transformational crisis management. The analysis relates to the difficulty now being…
The purpose of this treatise is to present an analysis of the importance of positive transformational crisis management. The analysis relates to the difficulty now being faced by Nokia, historically the world's leading manufacturer of technologically advanced mobile phones, of Apple's innovative combination of its iTunes, iPhone, and applications that deliver internet content to the iPhone.
A crisis, typically considered to be a negative issue, can be a positive transformational event in the life of a business firm when that firm recognizes a crisis and makes appropriate changes in its operations to facilitate positive growth and development. However, the initial stage of a crisis must be recognized and appropriately responded to. The crisis management paradigm that is the foundation for this case analysis focuses on four stages of a crisis: the preliminary crisis, acute crisis, chronic crisis, and crisis resolution. The case deals with the innovations of Apple that have enabled the firm to become a direct competitor to Nokia in the smart phone market. The preliminary crisis stage was not appropriately recognized by Nokia, and the firm was thrust into an acute crisis that has now evolved into a chronic crisis. A brief overview is presented of the historical development of both Nokia and Apple, and an analysis of the present crisis situation in which Nokia now finds itself is presented in some detail.
It was concluded that Nokia is now in a very difficult position regarding Apple due to its failure to engage in a timely transformational response to the competitive innovations of Apple.
This is an excellent example of failure in positive transformational crisis management.
Behavioral pattern mining for intelligent system such as SmEs sensor data are vitally important in many applications and performance optimizations. Sensor pattern mining…
Behavioral pattern mining for intelligent system such as SmEs sensor data are vitally important in many applications and performance optimizations. Sensor pattern mining (SPM) is also dynamic and a hot research issue to pervasive and ubiquitous of smart technologies toward improving human life. However, in large-scale sensor data, exploring and mining pattern, which leads to detect the abnormal behavior is challenging. The paper aims to discuss these issues.
Sensor data are complex and multivariate, for example, which data captured by the sensors, how it is precise, what properties are recorded or measured, are important research issues. Therefore, the method, the authors proposed Sequential Data Mining (SDM) approach to explore pattern behaviors toward detecting abnormal patterns for smart space fault diagnosis and performance optimization in the intelligent world. Sensor data types, modeling, descriptions and SPM techniques are discussed in depth using real sensor data sets.
The outcome of the paper is measured as introducing a novel idea how SDM technique’s scale-up to sensor data pattern mining. In the paper, the approach and technicality of the sensor data pattern analyzed, and finally the pattern behaviors detected or segmented as normal and abnormal patterns.
The paper is focussed on sensor data behavioral patterns for fault diagnosis and performance optimizations. It is other ways of knowledge extraction from the anomaly of sensor data (observation records), which is pertinent to adopt in many intelligent systems applications, including safety and security, efficiency, and other advantages as the consideration of the real-world problems.
Purpose — Automated fare collection systems implemented in public transportation systems in the last decade have provided a massive, continuous and low-cost source of…
Purpose — Automated fare collection systems implemented in public transportation systems in the last decade have provided a massive, continuous and low-cost source of reliable travel information. A direct and useful application of these data is the estimation of highly representative, although not bias-free, origin-destination (OD) matrices.
Methodology/approach — We discuss several issues with current OD matrix estimation methodologies, such as fare evasion and group travel, and their derived biases, specifically focusing on the Santiago (Chile) case. We also propose and apply two methods of validation: endogenous and exogenous validation. We elaborate on some methodological improvements that could be implemented to upgrade the activity estimation mechanics.
Findings — Several sources of bias in the estimation of OD matrix estimation from passive data are pointed and some solutions proposed. We apply improvements to existing methodologies and increase the success rate of trip estimations.
Practical implications — The reliable estimation of public transport OD matrices from passive data results in a valuable planning tool for both transit authorities and operators, much more representative and with less errors and biases that conventional data collecting techniques.
Originality/value of paper — This paper is one of the first works to deal with the subject.