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The purpose of this paper is to examine a recent comprehensive corporate real estate (CRE) alignment model which was derived from previous CRE alignment models. This study proposes several modifications and additions based on business and decision-making literature to increase the framework’s multidisciplinary strength and extend its implementation phase.

Literature from various fields is reviewed and “lessons” incorporated into the framework. The business literature review began with corporate strategy theories cited in CRE alignment theory and extended to critiques of those and more recent theories. Likewise, decision-making and implementation both began with material cited in CRE literature and “rippled” out to encompass pertinent material.

The model used provides a robust framework, and this study has identified several areas that would appear to improve that model from a theoretical and practical perspective. Areas of further research are identified that appear to offer opportunities to further develop the framework.

Historically, there has been a tendency for new CRE alignment models to be created rather than existing ones being developed further. Here, a framework derived from a meta-study of CRE alignment models is reviewed, and improvements are proposed to further develop CRE alignment theory and its application in practice through the addition of viewpoints from the business field and more focus on the implementation phase of the model.

Weick and Sutcliffe identified five principles that enable high-reliability organizations (HROs) to address environmental complexity and manage unexpected events. The current study aims to adopt this sensemaking perspective to analyze accidents within a typical HRO sector, namely maritime transport.

Through a retrospective case study analysis, this study focused on seven oil tanker accidents, using them as illustrative examples.

Findings show how the five principles contributed to the accidents' occurrence, explaining how failures in sensemaking affected the crew's capability to both prevent errors and cope with their consequences, thus leading to disasters.

Overall, the study offers an applicative contribution showing how this model may provide a reliable framework for analyzing the psychosocial factors affecting an accident. This approach deepens the understanding of how latent factors are enacted and how the prevention and error management phases interrelate within a comprehensive flow of the entire accident sequence. Furthermore, the study emphasizes consistent patterns that emerge across multiple accidents within the same sector, in order to learn valuable lessons to improve safety measures in the future.

This study constitutes an exemplary application in support of how Weick and Sutcliffe’s model is valuable for investigating HROs. It offers a second-order interpretative framework to understand accidents and underscores the interplay among these factors during the dynamic development of an accident.

Korea’s Institute for Basic Science (IBS), the first research institute dedicated to basic science in Korea, started ten years ago as part of a science policy called the Science Belt. It is noteworthy that Korea, with a short history of basic science, established such a research institute exclusively for basic science within a short period of time and made it one of the representative institutions of basic science in Korea. This paper aims to uncover the impetuses and constraints surrounding the policy of Science Belt, centering on the IBS.

Kingdon’s stream theory is used to clarify the factors that acted as impetuses or constraints for the Science Belt. For the analysis, in-depth interviews with the active policy participants were conducted in addition to the thorough literature review. The interviews enabled an in-depth understanding of the underlying factors for the Science Belt and the actual procedures of the policy decision.

This study found that the most powerful impetus in the Science Belt policymaking process was the President and a small group composed of a few scientists who played a leading role in the political stream. The constraint of the Science Belt was that the participation of scientist experts and governmental officials, the so-called invisible participants of Kingdon, was insignificant. In particular, there was no system in place to select policy alternatives for basic science through discussion between scientists and governmental officials.

The temporal scope of this study was limited to policy formation, that is, until the establishment of IBS. Therefore, future studies shall conduct a research on the implementation of the actual policy, IBS’s achievements and IBS’s impact of Korea’s basic science community.

This study applied both a theoretical framework and in-depth interviews along with the literature overview to understand a policymaking process from various angles.

This paper aims to discuss the practical dilemmas of institutional change to tackle the climate crisis in a UK university, identifying key assumptions and issues that block meaningful change. The research was part of an initiative to define a theory of change (ToC) to meet the university’s institutional climate commitments.

The findings are based on interviews with members of an inter-disciplinary ToC working group, a staff–student climate coalition and student representatives at the university. Interviewees were purposively selected to gain insights into assumptions about the nature of the university and its role in tackling the climate crisis, which must be addressed for the university to effectively implement its climate plan.

This paper identified tensions between the university’s role as a public and commercial institution, a lack of clarity over decision-making processes and the difficulties in balancing (and being transparent about) actions with commitments to tackle the climate crisis. A democratic and flexible approach to change is essential to mitigate these issues, providing an opportunity to reflect on the diversity of the university community and openly debate goals and commitments.

In setting out the initial steps of a ToC in a UK university, this paper offers practical insights for higher education institutions looking to change practices. By highlighting assumptions at a particular institution, this paper also contributes a level of granularity to a growing field of research on efforts in higher education institutions to tackle the climate crisis.

This study aims to examine the relationship between the environment and tourism flows, as well as the economic variables of the 32 states of Mexico for the period 1999–2019 based on data availability. The related literature studying tourism and environmental impacts is scarce at a national level, with most of them being local case studies. Some international studies find that if the relationship exists, it is weak or nonexistent, using CO₂ as a proxy in most cases.

The present study uses panel data and cointegration panel methodologies, while also using geographic information systems to observe the distribution of variables at a state level between tourism and environmental variables.

The findings of the study are as follows: state gross domestic product, the inertia of environmental variables (i.e. volume of water treatment and solid waste), occupied rooms (proxy variable for tourism activity) and average temperature have an impact on the contemporary evolution of environmental variables; national and international tourist variables have no impact on the environment; the panels are integrated in such a way that there is a long-term equilibrium between states and some environmental care variables; and no conclusive evidence is found regarding the impact of tourism activity on the considered environmental variables.

The main limitations and areas of opportunity of the work refer to the amount of data available over time and the precision of the measurement of the variables. The availability, temporality and frequency of the data are also limitations of the research. An example of this is the nonexistence of CO₂ emissions at the state level. Additionally, studying other countries and regions for which there are limitations of data and applied studies is also a challenge.

The results are important for economies (in growth) and societies whose economic growth depends on tourism flows and have done little to reverse the damage that tourism has on the environment.

The models can contribute to study the relation between tourism and environmental variables and could be extended to regions, states and provinces for decision-making on actions to be taken for the present and future.

The originality of the research is innovative for the region: Mexico, Central and Latin America. There are no works that have studied these problems with this methodology and these variables. In terms of originality, the classic models of panel data and cointegration of panel data are useful and easily replicable for others to use for different countries. The results are relevant because there is apparently no relationship between tourism and some environmental variables in the short run, but there exists a weak and strong long-run relation between some of them.

本研究采用面板数据和协整面板模型方法, 同时利用地理信息系统(gis)观察州一级层面旅游和环境方面的变量分布。

本研究根据数据可用性, 研究了墨西哥32个州1999–2019年期间环境与旅游流量及经济变量之间的关系。在国家层面上研究旅游与环境影响的相关文献很少, 而且大多是地方的个案研究。一些国际研究发现, 即使有这种关系, 大多数案例中使用二氧化碳作为替代变量, 这种关系也是很弱或不存在。

i)国家国内生产总值, 环境变量的惯性(即水处理量和固体废物量), 占用的房间(旅游活动的代理变量)和平均温度对环境变量的现有演化有影响。ii)国内和国际旅游变量对环境没有影响。iii)面板数据以这样一种方式集成, 即国家和一些环境变量之间存在一种长期平衡。iv)关于旅游活动对所考虑的环境变量的影响没有确凿的证据。

这项工作的主要局限和机会领域是指随着时间的推移可获得的数据量和变量测量的精度。数据的可用性、时效性和频率也是本研究的局限性。这方面的一个例子是在州一级不存在二氧化碳排放。此外, 由于数据和应用研究的局限, 研究其他国家和地区也是一个挑战。

研究结果对经济增长依赖旅游业流量的经济体和社会具有重要意义, 这些经济体和社会对扭转旅游业对环境的破坏方面做得还不够。

这些模型有助于研究旅游业与环境变量之间的关系, 并可推广到地区、州和省, 以制定当前和未来的行动决策。

这项研究的原创性对该地区(墨西哥、中美洲和拉丁美洲)来说是具有创新性的。没有人用这种方法和这些变量研究过这些问题。就原创性而言, 面板数据和面板数据协整的经典模型是有用的且易于复制, 可供其他国家使用。 研究结果具有一定的相关性, 因为旅游业与部分环境变量在短期内不存在明显的相关性, 但在它们中的一些变量在长期内存在着或强或弱的相关性。

Se examina la relación entre medio ambiente y flujos turísticos, así como variables económicas de los 32 estados de México para el período 1999-2019 basado en la disponibilidad de datos. La literatura relacionada que estudia el turismo y los impactos ambientales es escasa a nivel nacional, siendo la mayoría de ellos estudios de casos locales. Estudios internacionales encuentran que, si la relación existe, es débil o inexistente, utilizando el CO2 como un indicador en la mayoría de los casos.

Se utilizaron metodologías de datos de panel y cointegración de panel, además sistemas de información geográfica para observar la distribución de variables a nivel estatal.

i) El Producto Interno Bruto Estatal, la inercia de las variables ambientales (es decir, volumen de tratamiento de agua y residuos sólidos), habitaciones ocupadas (proxy de la actividad turística) y temperatura promedio tienen un impacto en la evolución contemporánea de las variables ambientales, ii) las variables turísticas nacionales e internacionales no tienen un impacto en el medio ambiente, iii) los paneles están integrados de tal manera que existe un equilibrio a largo plazo entre turismo, crecimiento económico y algunas variables ambientales, y iv) no se encuentra evidencia concluyente con respecto al impacto de la actividad turística en las variables ambientales consideradas.

Las principales limitaciones y áreas de oportunidad del trabajo se refieren a la cantidad de datos disponibles en el tiempo y a la precisión de la medición de las variables. La disponibilidad, temporalidad y frecuencia de los datos también son limitaciones de la investigación. Un ejemplo de ello es la inexistencia de emisiones de CO2 a nivel estatal. Además, el estudio de otros países y regiones para los que existen limitaciones de datos y estudios aplicados también es un reto.

Los resultados son importantes para las economías (en crecimiento) y las sociedades cuyo crecimiento económico depende de los flujos turísticos y que han hecho poco por invertir los daños que el turismo produce en el medio ambiente.

Los modelos pueden contribuir a estudiar la relación entre el turismo y las variables medioambientales y podrían extenderse a regiones, estados y provincias para la toma de decisiones sobre las acciones a emprender para el presente y el futuro.

El artículo proporciona un análisis innovador y exploratorio hacia una perspectiva futura que agrega valor al turismo y la planificación para la sostenibilidad. La relación entre turismo y medio ambiente se ha estudiado durante varios años. La UNTWO ha abordado las consecuencias del turismo en el medio ambiente, particularmente, más basura, mayor consumo de agua, emisiones de CO2 y otros aspectos. Pocos trabajos estudian la relación entre estas variables.

La originalidad de la investigación es innovadora para la región: México, América Central y América Latina. No existen trabajos que hayan estudiado estos problemas con esta metodología y estas variables.

En términos de originalidad, los modelos clásicos de datos de panel y cointegración de datos de panel son útiles y fácilmente replicables para que otros los utilicen en diferentes países.

Los resultados son relevantes porque aparentemente no hay una relación entre el turismo y algunas variables ambientales a corto plazo, existe una relación débil y fuerte a largo plazo entre algunas de ellas.

Our study examines how artificial intelligence (AI) can enhance decision-making processes to promote circular economy practices within the utility sector.

A unique case study of Alia Servizi Ambientali Spa, an Italian multi-utility company using AI for waste management, is analyzed using the Gioia method and semi-structured interviews.

Our study discovers the proactive role of the user in waste management processes, the importance of economic incentives to increase the usefulness of the technology and the role of AI in waste management transformation processes (e.g. glass waste).

The present study enhances the circular economy model (transformation, distribution and recovery), uncovering AI’s role in waste management. Finally, we inspire managers with algorithms used for data-driven decisions.

This study aims to examine social determinants and social strains of cyberbullying victimization among expatriate populations in high-income countries such as Qatar. The authors argue that expatriate students will be exposed to stains and pressures due to several factors, such as feeling alienated, lonely, homesick, insecure and helpless. This study examines a partial assumption of general strain theory (GST), which posits that expats’ cyberbullying victimization can create negative stimuli that lead to negative feelings and, as a result, to delinquent behavior. The delinquent behavior can be seen as a coping method in encountering strains. Logistic regression analysis is applied (using SPSS v. 21) to test the hypothesis that the victimization of expats’ cyberbullying could lead to strain and delinquency.

A sample of 2,428 expatriate students (46% males and 54% females) was randomly selected from seven public schools in Qatar. The average number of siblings in the household was 2.7. Around 10.8% of the sample reported victimization by cyberbullying. Most came from intact families (80.6%) compared to 19.4 living in broken homes. Concerning the birth order of the student in the family, 25% of the sample were firstborn, and 20% were middle-born. Students’ mother relationships were higher than students’ father relationships (69% vs 51%, respectively). Fathers were higher in undergraduate education than mothers (60% vs 49%, respectively). Considering that 58% of women did not have a job, most fathers work in administrative positions (47% in administrative work and 39% in professional positions) as opposed to mothers’ positions (15% and 21%, respectively). The survey was distributed among expatriate students by trained researchers, teachers and social workers in public schools. The researchers explained the purpose of the study, confidentiality and potential risks and provided directions for completing the survey. Parents and their children provided signed informed consent before participation, following the institutional review boards of Qatar University’s Human Subject Research Committee and the Ministry of Social Development. The victimization of cyberbullying is measured at the dichotomy level by asking a general cyberbullying question (In the last 12 months, had you been bullied by other students using mobile messages, email, voice or video messages? Responses were 1 – yes and 0 – no). A definition of cyberbullying was included in the questionnaire. Independent measures are as follows: (1) demographic variables: gender, belief, health, number of friends and exposure to violence; (2) family variables: delinquent family, coercive parenting, family relations, family disputes, father absence and family ties; (3) school variables: school satisfaction, school violence, student fighting, teachers' violence, school truancy and going late to school; (4) imprudent behavior: smoking, alcohol, not using a seat belt, gambling, stealing less than 100 QR, chewing tobacco, stimuli, volatile drugs, sexual harassment, throwing garbage out of the car, cheating, vandalism and victimization.

Findings showed that n = 255, 10.8% of the expats’ sample N = 2,428 reported victimization of cyberbullying, of whom 46% were males and 54% were females. A total of 24% of the victims of cyberbullying were males, and 5.8% were females. About a third of the sample were cyberbullying perpetrators (n = 716, 29.5%). Victims of cyberbullying came from intact families (62.4%) compared to broken families (37.6%). A round third of the victims reported the absence of a father during their childhood (n = 78, 31.7%). Most of the victims came from a typical community compared to the delinquent community (71.2% vs 28.2%). About a third of the victims reported it was easy to talk with the father when needed (32% compared to 42.7%), who said it was easy. More than half of the victims do not use seat belts. A low percentage of them were gambling (n = 68, 27% or 2.9% of the total sample). Regarding escaping imprudent and delinquent behaviors, findings showed that a third and more than a tenth of the cyberbullying were smokers and alcoholics (n = 69, 27.4% and n = 42, 16.7% respectively). Moreover, among the most serious, widely spread student problems, around a quarter of the victims reported using chewing tobacco (Sweeka is the local name) (n = 54, 21.4%). Finally, drug use among victims was more than a tenth of them (n = 41, 16.3%). About a quarter of the victims reported stealing less than 100 QR (n = 67, 26.8% or 2.9% of the total sample). Concerning the crimes committed by victims, findings showed that more than forth of them committed assault (n = 71, 28.3%), student fights (n = 202, 80.8%), school violence (n = 117, 46.6%) and half of the victims (50.2%) were also victims of face-to-face bullying. Little below half of the sample was exposed to violence (n = 120, 48.6%) and was the victim of violence in the past 12 months (n = 100, 40.8%). A significant gender differences was found in the victimization of cyberbullying (1 = yes, 0 = no) (a = 000). Moreover, significant mean differences were found between expatriates student victimization of cyberbullying at (a = 000) in all strain variables. Using binary regression analysis to examine the equality of probability of being a victim of cyberbullying as accounted for by the independent variables, the model’s predictability was 89.4%. The Hosmer and Lemeshow test and omnibus tests support the model’s fit (a = 000). Nagelkerke R² shows that the stain variables accounted for 24% of the variance in the expat's student victimization of cyberbullying.

Conceptualization and determination of what constitutes cyberbullying from the criminal law perspective are needed. Cyberbullying is defined as a form of violence and crime involving new technologies (Sun et al., 2016, p. 62). Policymakers should provide accessible and equitable access to the criminal justice system, the integration of expatriates and the provision of support services to avoid delinquency.

A social cohesion, inclusion and well-being policy is needed for expatriate students and their families in Qatar. In particular, cultural diversity policy and programs, a source of strength and enrichment should be promoted in educational settings. Social inclusion and cultural diversity programs could ease the alienation and marginalization that expatriate students may encounter in their host societies to prevent stains and negative emotions that lead to delinquency and criminal behaviors. Access to support services without discrimination to avoid health and psychological strains and risk factors. This includes but is not limited to avoidance of stigmatization, embarrassment, sense of helplessness, humiliation and other negative feelings toward expatriates. Awareness and promotion of cultural diversity values are needed to enhance cultural acceptance to reduce victimization among the expatriate population. Criminal law and security implications conceptualization and determination of what constitutes cyberbullying from the criminal law perspective are needed. Cyberbullying is a form of violence and crime involving new technologies (Sun et al., 2016). Policymakers should provide accessible and equitable access to the criminal justice system, integrating expatriates and providing support services to avoid delinquency. There is a pressing need for further research within the realm of crime and law to establish the precise legal boundaries surrounding cyberbullying and to delineate the potential scope for legislative measures aimed at safeguarding against victimization in Qatar. Although the state of Qatar has taken steps to address cyberbullying by incorporating it into relevant legal frameworks, there remains a gap in terms of specifically targeting cyberbullying involving children and adolescents. Despite the introduction of the new Cybercrime Prevention Law, the issue of cyberbullying among these vulnerable groups is not adequately addressed.

Social implication includes but is not limited to avoidance of stigmatization, embarrassment, sense of helplessness, humiliation and other negative feelings towards expatriate. Awareness and promotion of cultural diversity values is needed to enhance cultural acceptance to reduce victimization among expatriate population.

The present study examines some strain theory assumptions and the victimization of the cyberbullying expatriate population. This study tests a partial assumption of GST, which states that the expatriate population’s exposure to the victimization of cyberbullying can lead to negative stimuli that, in return, create negative feelings and, as a result, imprudent and delinquent behavior. The cyberbullying behavior can be seen as an escaping and coping method in encountering strains. This study underscores the presence of cyberbullying within high schools among expatriate students, exerting significant effects on their personal, social and emotional behaviors. The novel insights gleaned from this investigation contribute substantively to the comprehension of both the pervasiveness and repercussions of cyberbullying on the well-being of expatriate students. This contribution is particularly vital, given the dearth of research in the field, largely attributable to the growing dependence of students on the internet for various cyber activities. This study examines a partial assumption of GST (in non-Western country). Moreover, it uses an advanced statistical analysis and large sample.

Autonomous mobile robots (AMRs) play a crucial role in industrial and service fields. The paper aims to build a LiDAR-based simultaneous localization and mapping (SLAM) system used by AMRs to overcome challenges in dynamic and changing environments.

This research introduces SLAM-RAMU, a lifelong SLAM system that addresses these challenges by providing precise and consistent relocalization and autonomous map updating (RAMU). During the mapping process, local odometry is obtained using iterative error state Kalman filtering, while back-end loop detection and global pose graph optimization are used for accurate trajectory correction. In addition, a fast point cloud segmentation module is incorporated to robustly distinguish between floor, walls and roof in the environment. The segmented point clouds are then used to generate a 2.5D grid map, with particular emphasis on floor detection to filter the prior map and eliminate dynamic artifacts. In the positioning process, an initial pose alignment method is designed, which combines 2D branch-and-bound search with 3D iterative closest point registration. This method ensures high accuracy even in scenes with similar characteristics. Subsequently, scan-to-map registration is performed using the segmented point cloud on the prior map. The system also includes a map updating module that takes into account historical point cloud segmentation results. It selectively incorporates or excludes new point cloud data to ensure consistent reflection of the real environment in the map.

The performance of the SLAM-RAMU system was evaluated in real-world environments and compared against state-of-the-art (SOTA) methods. The results demonstrate that SLAM-RAMU achieves higher mapping quality and relocalization accuracy and exhibits robustness against dynamic obstacles and environmental changes.

Compared to other SOTA methods in simulation and real environments, SLAM-RAMU showed higher mapping quality, faster initial aligning speed and higher repeated localization accuracy.

An abundance of techniques has been presented so forth for waste classification but, they deliver inefficient results with low accuracy. Their achievement on various repositories is different and also, there is insufficiency of high-scale databases for training. The purpose of the study is to provide high security.

In this research, optimization-assisted federated learning (FL) is introduced for thermoplastic waste segregation and classification. The deep learning (DL) network trained by Archimedes Henry gas solubility optimization (AHGSO) is used for the classification of plastic and resin types. The deep quantum neural networks (DQNN) is used for first-level classification and the deep max-out network (DMN) is employed for second-level classification. This developed AHGSO is obtained by blending the features of Archimedes optimization algorithm (AOA) and Henry gas solubility optimization (HGSO). The entities included in this approach are nodes and servers. Local training is carried out depending on local data and updations to the server are performed. Then, the model is aggregated at the server. Thereafter, each node downloads the global model and the update training is executed depending on the downloaded global and the local model till it achieves the satisfied condition. Finally, local update and aggregation at the server is altered based on the average method. The Data tag suite (DATS_2022) dataset is used for multilevel thermoplastic waste segregation and classification.

By using the DQNN in first-level classification the designed optimization-assisted FL has gained an accuracy of 0.930, mean average precision (MAP) of 0.933, false positive rate (FPR) of 0.213, loss function of 0.211, mean square error (MSE) of 0.328 and root mean square error (RMSE) of 0.572. In the second level classification, by using DMN the accuracy, MAP, FPR, loss function, MSE and RMSE are 0.932, 0.935, 0.093, 0.068, 0.303 and 0.551.

The multilevel thermoplastic waste segregation and classification using the proposed model is accurate and improves the effectiveness of the classification.

Smart cities in India are going to be a reality very soon by turning challenges into opportunities for the society. However, due to rapid increase in population burden, fast urbanization and growing demand of advanced services in the smart cities, the quantity of per capita municipal solid waste (MSW) has escalated. Moreover, the COVID-19 pandemic has further challenged the municipal solid waste management (MSWM) system with the increasing amount of infectious wastes coming from households (HHs), quarantine centers, healthcare facilities, vaccination centers, etc. Therefore, the present study attempts to explore and analyze the various dimensions of sustainable MSWM system in the smart cities.

The study identifies 13 factors of sustainable MSWM system from the literature, field surveys and stakeholders' opinions. Thereafter, stakeholders' opinions are collected and analyzed using total interpretive structural modeling (TISM) approach to explore the interrelationships among the factors of sustainable MSWM system. These relationships are further validated through the empirical investigation of the real-life case study of Rourkela Municipal Corporation (RMC), Odisha, India.

The TISM approach places all 13 factors into six levels in the hierarchical digraph depending upon the inputs received from the various stakeholders on their interrelationships. Study also validates the proposed TISM model by collecting the data of RMC, Odisha, on the development of MSWM system over the period of 2015–2021.

The study also highlights various implications for the other developing cities and stakeholders to set up the roadmap for developing the sustainable MSWM system. Study defines “IT platform” and “awareness among citizens” as the base of the sustainable MSWM system in any smart city.

The present study is the first of its kind to explore the interrelationships among the factors of sustainable MSWM system by using TISM approach. Moreover, the proposed TISM framework is further validated through the empirical journey of one of the smart cities in India.