Aspiration Levels Research Articles

Performance information and issue prioritization by political and managerial decision-makers: A discrete choice experiment

Abstract Issue prioritization is the first stage of attention-based theories of decision-making, but remains theoretically and empirically uncharted territory in public administration research. We propose and test how issue prioritization is informed by the characteristics of the performance information on which decision-makers rely, in particular its source (internal or external information), nature (objective or subjective information), aspiration level (historical, social, or coercive aspirations), and required cognitive effort (attention costs). Furthermore, we theorize how these characteristics of performance information determine issue prioritization decisions of political and managerial decision-makers in different ways. We empirically examine issue prioritization decisions in road maintenance and primary school education using a discrete choice experiment among 2,313 local government officials. The experiment reveals that decision-makers are more likely to prioritize issues that are signaled through objective performance measures and that are articulated relative to coercive aspirations, but that the effects of the information’s source and attention costs differ between policy domains. Comparison of observational variation regarding decision-makers’ roles indicates that public managers more strongly prioritize road maintenance issues that are articulated in objective performance information, but not in primary school education. The study advances public administration research and theory with a “horizontal” behavioral perspective on decision-makers’ information processing to prioritize between simultaneous performance issues.

Quality Evaluation of College Students' Innovation and Entrepreneurship Education Based on the K-Means Clustering Algorithm

Innovation and entrepreneurship are increasingly recognized as vital components of modern higher education, fostering creativity, problem-solving skills, and economic growth. However, effectively catering to the diverse needs of students in these domains remains a challenge. This paper proposes a novel approach to address this challenge by applying the Cluster Swap Expectation Maximization (CSSEM) algorithm to cluster college students based on attributes relevant to innovation and entrepreneurship. Using a dataset encompassing metrics such as GPA, innovation score, entrepreneurship score, socioeconomic status, and gender, we demonstrate the effectiveness of the CSSEM algorithm in segmenting student populations. The findings reveal distinct clusters of students with varying levels of academic performance, innovation potential, and entrepreneurial aspirations. For instance, Cluster 1 comprises students with lower GPAs (mean GPA = 3.2) and moderate innovation and entrepreneurship scores (mean innovation score = 78, mean entrepreneurship score = 80), while Cluster 2 consists of high-performing students (mean GPA = 3.7) with strong innovation and entrepreneurship potential (mean innovation score = 90, mean entrepreneurship score = 88). These insights enable educators and policymakers to design tailored interventions and support mechanisms that cater to the specific needs of different student groups.

A Review on Green Chemistry and Its Applications

Green Chemistry is most investigated subject these days. It is also known as sustainable chemistry. Green Chemistry and sustainable chemistry are equals that helps to save and conserve resources. It decreases the effect of chemical products on human and atmospheric health. Green Chemistry gives 12 principles that reduce and prevent the utilization and manufacture of hazardous substance. These principles of green chemistry inform about the various issues related to production of chemical compound. Green Chemistry concept started approximately three decades ago. Green chemistry concept for the chemical synthesis and application launched in 1990. This review article purpose to study about Green chemistry and its application and how green chemistry connect to the phytochemistry. By establishing Green Aspiration Level (GAL) that is a quantifiable descriptor, process greenness becomes measurable. Green house gases and global warming are the problem that affected the human and environment health. Green chemistry is used in daily life mainly in medicines. Tree bark and Pine bark extracts are mostly used in anti-microbial, antioxidant and anticancer drugs. The matter that present in environment gives applicable things to the researchers and engineers for the changing and developing a sustainable culture. The word “Green chemistry” is given by the IUPAC which means: the invention, design and utilization of chemical product and process to reduce or to eliminate the use and production of unsafe substance.

Comparative analysis of videofluoroscopy and pulse oximetry for aspiration identification in patients with dysphagia after stroke and non-dysphagics

PurposeDysphagia is a prevalent symptom observed in acute stroke. Several bedside screening tests are employed for the early detection of dysphagia. Pulse oximetry emerges as a practical and supportive method to augment the existing techniques utilized during bedside swallowing assessments. Desaturation levels, as measured by pulse oximetry, are acknowledged as indicative of aspiration by certain screening tests. However, the predictive capability of pulse oximetry in determining aspiration remains a subject of controversy. The objective of this study was to compare aspiration and oxygen desaturation levels by time and aspiration severity in dysphagic patients compared to healthy controls. It also aimed to evaluate the accuracy of pulse oximetry by comparing it with VFSS findings in detecting aspiration in both liquid (IDDSI-0) and semi-solid (IDDSI-4) consistencies.Materials and methodsEighty subjects (40 healthy and 40 acute stroke patients) participated. Patients suspected of dysphagia underwent videofluoroscopy as part of the stroke unit’s routine procedure. Baseline SpO2 was measured before VFSS, and stabilized values were recorded. Sequential IDDSI-0 and IDDSI-4 barium tests were conducted with 5 ml boluses. Stabilized SPO2 values were recorded during swallowing and 3-min post-feeding. Patients with non-dysphagia received equal bolus monitoring. Changes in SPO2 during, before, and after swallowing were analyzed for each consistency in both groups.ResultsThe study revealed a statistically significant difference in SPO2 between patients with dysphagia and controls for IDDSI-4 and IDSSI-0. In IDDSI-4, 20% of patients experienced SpO2 decrease compared to 2.5% in control group (p = 0.013). For IDDSI-0, 35% of patients showed SpO2 decrease, while none in the control group did (p = 0.0001). Aspiration rates were 2.5% in IDDSI-4 and 57.5% in IDDSI-0. In IDDSI-0, SpO2 decrease significantly correlated with aspiration (p = 0.0001). In IDDSI-4, 20.5% had SpO2 decrease without aspiration, and showing no significant difference (p = 0.613). Penetration-Aspiration Scale scores had no significant association with SpO2 decrease (p = 0.602). Pulse oximetry in IDDSI-4 had limited sensitivity (0%) and positive predictive value, (0%) while in IDDSI-0, it demonstrated acceptable sensitivity (60.9%) and specificity (100%) with good discrimination capability (AUC = 0.83).ConclusionsA decrease in SPO2 may indicate potential aspiration but is insufficient alone for detection. This study proposes pulse oximetry as a valuable complementary tool in assessing dysphagia but emphasizes that aspiration cannot be reliably predicted based solely on SpO2 decrease.

Key antecedents of maximal levels of aspiration and minimal boundary goals: a structural equation modeling analysis

AbstractResearch findings indicate that two types of goals, which focus on the lowest (highest) levels of achievement possible in a learning setting, are strong predictors of how well students attain in school. Unfortunately, little is known about how these two goals, termed minimal boundary goals (MBG) and maximal levels of aspiration (MLA) relate to psychological constructs that are theorized to be antecedents of goals. To fill this knowledge gap, this research collected data from 463 secondary-school students and tested a model linking these goals to achievement motives and theory of intelligence. Results revealed that not believing that intelligence is fixed and devoting effort to studying was associated with a strong endorsement of MLA. At the same time, making low/no efforts to study, being afraid of failure, and believing that intelligence is fixed were strong predictors of MBG. These findings advance current knowledge and have important implications for teaching and learning.

Two-Case Study of Rural Migrant TVET Female Students in Western China: Aspirations of Learning English

This study is an investigation of the English language learning aspirations and deprivations of female rural migrant youth in technical and vocational education and training (TVET) schools in two locales in western China. This study adopted basic interpretive research focused on individual voices and experiences. The capability approach provided the conceptual framework. Participants in this research primarily aspired to learn English for instrumental purposes: to pass exams, earn higher degrees, find better jobs in cities, and support their children in learning English. A lack of English proficiency, economic situation, and living environment greatly limited their aspirations. Participants showed a spectrum of levels of aspirations of English learning. For participants with low levels of English proficiency, their English could neither support their educational and employment goals nor inspire them for greater future plans. Participants from the TVET–university joint program formulated a stronger and wider range of aspirations when compared to those encapsulated in secondary TVET. Recommendations include increasing opportunities for exposure to English, reforming exam-oriented English learning, enriching the prevailing culture of learning and the perceived value and social uses of English, increasing TVET school and university cooperation, and adapting the TVET English curriculum to economic imperatives.

Optimisasi Portofolio Saham Syariah dengan Pendekatan Fuzzy Goal Programming

This study discusses about solving the problem of stock portfolio optimization. The portfolio optimization problem can be modeled as a multiobjective model with two objective functions, they are maximizing return and minimizing risk. This study uses the mean-variance Markowitz model to model the portfolio. The fuzzy goal programming approach is used to solve stock portfolio problems by converting a multi-objective model into a fuzzy mathematical programming model which is solved using a nonlinear programming method. The results of implementing the model on stocks listed on the Jakarta Islamic Index show that the best investment proportion forms an optimal portfolio according to the level of aspirations. Several different optimal portfolios can be formed using the fuzzy goal programming approach. The difference in the results of these portfolios depends on the level of aspiration of investors.

Critical global citizenship of high school students in Indonesia and Japan

The COVID-19 pandemic has prompted a review of global citizenship and education to tackle global injustices. This study investigates the impact of school education and the national curriculums on students’ attitudes towards global citizenship and examines the features of critical global citizenship among Indonesian and Japanese students. According to a questionnaire survey, students in both countries had high levels of altruism, empathy and non-violent aspirations of the collective and low levels of fairness of rewards and non-violent aspirations of the personal. Indonesian students had a higher sense of personal and national responsibility; however, they did not recognize the structural violence of poverty. Japanese students recognized poverty as structural violence; however, they were uninformed about global human rights and lacked a sense of personal responsibility in global issues. Online international education and curricula should be improved to enable students to understand global issues and adopt a sense of responsibility towards them.

Solution of Uncertain Constrained Multi-Objective Travelling Salesman Problem with Aspiration Level Based Multi Objective Quasi Oppositional Jaya Algorithm

Solution of Uncertain Constrained Multi-Objective Travelling Salesman Problem with Aspiration Level Based Multi Objective Quasi Oppositional Jaya Algorithm

Cooperation among unequal players with aspiration-driven learning.

Direct reciprocity promotes the evolution of cooperation when players are sufficiently equal, such that they have similar influence on each other. In the light of ubiquitous inequality, this raises the question of how reciprocity evolves among unequal players. Existing studies on inequality mainly focus on payoff-driven learning rules, which rely on the knowledge of others' strategies. However, inferring one's strategy is a difficult task even if the whole interaction history is known. Here, we consider aspiration-driven learning rules, where players seek strategies that satisfy their aspirations based on their own information. Under aspiration-driven learning rules, we explore the evolutionary dynamics among players with inequality in endowments and productivity. We model the interactions among unequal players with asymmetric games and characterize the condition where cooperation is feasible. Remarkably, we find that aspiration-driven learning rules lead to a higher level of cooperation than payoff-driven ones over a wide range of inequality. Moreover, our results show that high aspiration levels are conducive to the evolution of cooperation when more productive players are equipped with higher endowments. Our work highlights the advantages of aspiration-driven learning for promoting cooperation among unequal players and suggests that aspiration-based decision-making may be more beneficial for the collective.

Sustainable multiple travelling salesman problem solved by reference point aspiration level based multi objective quasi oppositional Jaya algorithm under uncertain environment

Sustainable multiple travelling salesman problem solved by reference point aspiration level based multi objective quasi oppositional Jaya algorithm under uncertain environment

Cooperation transitions in social games induced by aspiration-driven players.

Cooperation and defection are social traits whose evolutionary origin is still unresolved. Recent behavioral experiments with humans suggested that strategy changes are driven mainly by the individuals' expectations and not by imitation. This work theoretically analyzes and numerically explores an aspiration-driven strategy updating in a well-mixed population playing games. The payoffs of the game matrix and the aspiration are condensed into just two parameters that allow a comprehensive description of the dynamics. We find continuous and abrupt transitions in the cooperation density with excellent agreement between theory and the Gillespie simulations. Under strong selection, the system can display several levels of steady cooperation or get trapped into absorbing states. These states are still relevant for experiments even when irrational choices are made due to their prolonged relaxation times. Finally, we show that for the particular case of the prisoner dilemma, where defection is the dominant strategy under imitation mechanisms, the self-evaluation update instead favors cooperation nonlinearly with the level of aspiration. Thus, our work provides insights into the distinct role between imitation and self-evaluation with no learning dynamics.

Improvement in Livelihood Security of Scheduled Caste Farmers through Integrated Farming System in Hassan District of Southern Karnataka, India

The study was conducted in the purposively selected Hassan district, a total sample of 223 respondents were purposively selected for the study. Data was collected by using pretested structured interview schedule and analyzed using appropriate statistical tools. The results revealed that, a majority of the respondents belonged to low category of education level, land holding, cropping pattern, livestock possession, innovativeness, mass media exposure and extension participation and then followed by medium category of cosmopoliteness, training undergone, willingness in agriculture and high category of social participation, level of aspiration and risk orientation. The Livelihood security of respondents in ‘highly satisfied category’ increased to 34.98 per cent from 23.77 per cent after implementation of the project. There was an improvement in livelihood security after the implementation of the project, out of seven dimensions, maximum increase was noticed in employment security (50.62%) followed by living amenities(49.86%),economic efficiency(40.89%),ecological security(39.82%), social equitability (35.56%),assets(35.37%)and coping strategies against stress (22.39%).Further, the characteristics such as land holding, cropping pattern, livestock possession, cosmopoliteness, innovativeness, mass media exposure, extension participation, level of aspiration, training undergone and willingness in agriculture had positive and significant relationship with livelihood security. The findings conveyed that six independent variables such as land holding, cropping pattern, innovativeness, extension participation, level of aspiration, training undergone had contributed significantly to livelihood security of farmers. The R2 value indicated that all the 13 independent variables had contributed to the tune of 64.40 per cent of variation in livelihood security of the respondents. The results pertaining to economic analysis indicated that BC ratio has been increased to 3.26 from 1.84 in crop improvement and livestock components after the implementation. Hence, the concerned development departments require to organize the demonstrations, trainings, field days, exposure visits etc., to educate the farmers about IFS. The positive and significantly related characteristics needs to be considered while selecting the farmers for the extension educational programmes in order to enhance their livelihood security.

A Hybrid Model for Fitness Influencer Competency Evaluation Framework

Fitness influencers are an emerging profession in recent years. At present, the main research on fitness influencers focuses on their personal traits, professional knowledge and skills, and course content, while there is still a large research gap on the social media marketing strategies of fitness influencers, how they interact with fans, and the reasons for their influence on fans. There is a lack of a comprehensive evaluation framework for fitness influencer research, and there is no clear research on what competencies are required to become a qualified fitness influencer. Therefore, it has become an important issue to establish a comprehensive fitness influencer competency evaluation. In this study, a hybrid model of fitness influencer competency evaluation framework was developed based on government competency standards and expert knowledge using the Multiple Criteria Decision-Making (MCDM) model perspective. This evaluation should expand to include the principles of sustainable development, emphasizing the influencers’ role in advocating for environmental responsibility, social equity, and economic viability within the fitness industry. First, the study developed 21 criteria in six dimensions of fitness influencer competencies through a literature survey and interviews with several experts. The 21 criteria resonate with many of the Sustainable Development Goals (SDGs), including SDG 3 (Good Health and Well-being), SDG 4 (Quality Education), SDG 5 (Gender Equality), SDG 10 (Reduced Inequalities), and SDG 11 (Sustainable Cities and Communities). The Bayesian Best-Worst Method (Bayesian BWM) was used to generate the best group weights for fitness influencer competencies. Then, a modified Technique for Order Preference by Similarity to the Ideal Solution Based on Aspiration Level (modified TOPSIS-AL) was applied to evaluate the performance ranking of major fitness influencers in Taiwan by integrating the concept of the aspiration level. The results of the study revealed that behavioral standards were the most important dimension, emphasizing the need for fitness influencers to establish a comprehensive set of norms for their own behavioral standards. The top five criteria for fitness influencers’ competencies were self-review, punctuality and prudence, creativity, rapport and motivation, and the need to conform to one’s body image. The performance ranking was used to compare the evaluated subjects to the desired level to obtain a basis for improvement. This study effectively identifies key fitness industry competency indicators and refines business performance through the management implications proposed in this study to facilitate the development of the fitness industry.

$\mathbb{T}-$Relative Fuzzy Linear Programming for $\mathbb{T}-$Relative Fuzzy Target Coverage Problems

Optimal set covering problems are commonplace in communication, remote sensing, logistics, image processing, and network fields [3]. Thus, studies on determining optimal covering sets (sensors) of points (targets) in a region have emerged recently. One characteristic of these studies is the consideration of cases where a target is considered fully covered when it falls within a coverage area ("Boolean" coverage). Consequently, optimality solutions/methods/algorithms founded on this coverage scheme are usually too restrictive and (or) precise and so are not suitable for many complex and real life situations, which are most times plagued with ambiguity, vagueness, imprecision and approximate membership of points and (or) covering sets. Fuzzy structures have proven to be suitable for the representation and analysis of such complex systems with many successful applications. Although fuzzy sets generalizes a set, a more recent generalization for both and its related concepts is the Relative fuzzy set [1] which gives a dynamic fuzzy representation to sets. $\mathbb{T}-$Relative Fuzzy fixed points results of $\mathbb{T}-$Relative fuzzy maps were studied in [5] and recently, the concept of $\mathbb{T}-$Relative fuzzy linear programming [6] was introduced as a generalization of fuzzy linear programming. The results were applied to generalize the Boolean set based covering problems in literature to a $\mathbb{T}-$Relative fuzzy Boolean coverage one. Although, Shan et al. in [15] and others [16] - [21] have given a probabilistic coverage consideration but this lacks subjectivity in representing vagueness and imprecision inherent in most systems. In this present article the Linear Programming (LP) formulation of “A Computational Physics-based Algorithm for Target Coverage Problems" by Jordan Barry and Christopher Thron is generalized by considering a fuzzy and relative fuzzy target coverage instead of the crisp set Boolean coverage. Also we introduce the Fuzzy Linear Programming (FLP) and the $\mathbb{T}-$Relative Fuzzy Linear Programming (RFLP) for the set coverage problem which allows for ascertaining dynamic optimality with aspiration levels.

An integrated GBWM-PROMETHEE-CLOUD & MCGP model for green supplier selection and order allocation (GSSOA) in an oil refinery

With the increase of environmental concerns in recent years and the prevalence of such issues, which originate mainly from large industries and manufacturing plants, green supply chain management (GSCM) issues have been given special attention among researchers. GSCM is a group of management applications integrating supply chain management with criteria related to environment and supplier selection with the purpose of reducing environmental pollution caused by processes involved in a company supply chain. In this research the main contributions is to draw a decision-making structure addressing the applicability of the green supplier selection (GSS) and order allocation (OA) problem in an Iranian Oil refinery company. A combination of Cloud-PROMETHEE along with using GBWM was taken into account for GSS as the first phase and MCGP method for OA as the second phase, in order to solve the GSSOA problem. The proposed technique lets the vagueness and uncertainty of experts' judgments be obtained by assisting uncertain linguistic variable derived from the cloud model. Furthermore, the group best-worst method (GBWM) obtains the optimal criteria weights by forming a nonlinear programing model and the prioritizing of nominated suppliers is established using the PROMETHEE method with the possibility to pick a distinct preference function for each criterion and draw a graph of supplier preferences. At last, MCGP method was applied considering with the possibility of multi-choice aspiration levels (MCAL) for each goal. The suggested model illustrated with actual figures in an oil refinery to provide insight to decision-makers of green supplier selection and order allocation. To do so, initially nine criteria have been derived after vast research on literature and experts’ opinions. Then the suppliers was successfully evaluated with considering uncertainties and randomness in a group of decision maker judgments. The order allocation was also completed by minimizing total cost and delays and maximizing purchase using results of supplier ranking in the first phase. Results have shown that the supplier with better ranking in GSS is preferred in allocating orders. A sensitivity analysis then performed and confirmed that the suggested method is highly stable against different changes in the data. The proposed method was also compared with the basic MCGDM cloud model and the method is approved. Finally, managerial implications and conclusions for additional researches are demonstrated.

Development of Scheduled Caste Farmers through Integrated Farming System in Bangalore Rural District, India

The study was conducted in Bengaluru Rural district of Karnataka State, a total sample of 275 respondents was selected for the study and the data was collected by using pretested structured interview schedule and analyzed using appropriate statistical tools. It was observed that, the livelihood security of the respondents under ‘highly satisfied’ category was improved from 23.64 per cent from the bench mark data to 38.18 per cent. In ‘less satisfied’ category it was decreased to 32.73 per cent from 41.82 per cent after implementation of the project. Out of seven dimensions of livelihood security, maximum increase was noticed in employment security (69.84%) followed by ecological security (60.96%), living amenities (52.39%), economic efficiency (51.76 %), coping strategies against stress (45.35%), assets (37.13 %) and social equitability (28.03%) and overall livelihood security increased by 48.17 per cent after implementation of the project. The personal, socio-economic and psychological characteristics of the beneficiaries; land holding, cropping pattern, livestock possession, innovativeness, mass media exposure, management orientation, level of aspiration, training undergone, participation in development programme, access to extension personnel and access to resources exhibited positive and significant relationship with livelihood security.The R2 value of 0.324 indicated that all 18 variables had contributed to the tune of 32.40 per cent of variation in Livelihood Security of respondents. Hence, the concerned development departments should promote and strengthen the IFS activities to enhance the livelihood security of resource poor framers. The positive and significantly related characteristics needs to be considered while selecting the farmers for IFS programs to enhance their livelihood security.

Neutrosophic data envelopment analysis based on parametric ranking method

The use of fuzzy numbers and their extensions, especially neutrosophic fuzzy numbers, is inevitable to express the value of the parameters of optimization problems derived from the real world. In this regard, the comparison and ranking of neutrosophic fuzzy numbers as one of the main research topics that can provide a suitable decision to solve optimization problems is of interest to researchers. In this study, we introduce a parametric approach to rank single value trapezoidal neutrosophic numbers which are based on decision–maker aspiration level for degree of the truth membership function and selecting appropriate levels for non-indeterminacy and non-falsity–membership functions. A prominent feature of this method is its high flexibility, which is due to the consideration of acceptable levels for evaluation by the decision maker. Therefore, in most decision issues, it can be used to determine the preferred option. Also, some theorems and reasonable properties are given to demonstrate the effectiveness of our proposed parametric approach. Furthermore, in an example of data envelopment analysis model with neutrosophic information the validity and applicability of the suggested method are examined.

Peran Media Pembelajaran dan Permainan dalam Meningkatkan Motivasi Belajar Siswa

A media is an intermediary or anything that is used for a process of transmitting messages or information that can stimulate students' thoughts, feelings and will so that it can encourage teaching and learning. Apart from learning media, games that are connected to learning material are also very helpful in creating interesting and enjoyable learning. Such games that involve students are: exploratory play, dynamic play (energetic play), skillful play, social play, imaginative play, and puzzle games. -it-out play). Through games, students' thinking and socializing abilities can be improved. Motivation in the learning process is also very necessary to make learning enjoyable. Teachers can provide motivation in the classroom in the form of: giving points, praise, prizes, group work, competition, goals and level of aspiration, sarcasm, assessments, field trips and excursions, educational films and learning via radio. The role of learning media and games in increasing student motivation in class is very necessary to eliminate feelings of boredom and saturation in learning. With media, games and motivation provided by the teacher, learning will be interactive, meaningful and fun and students will easily accept the teacher's explanations, the teacher will also be helped in explaining the material.

Lyceum and university aspirations among migrants and non‐migrants in Italy

AbstractScholars have argued that, on average, immigrant students are ‘optimists’ and have higher educational aspirations than non‐migrant students after accounting for students' socio‐economic background and educational performance. However, ethnic minority groups, which proxy the different origin backgrounds of migrants, may show mixed findings in terms of educational aspirations. This study aims to analyse the lyceum (the most theoretical school in Italy) and university aspirations of migrant‐origin students and their Italian counterparts, enrolled respectively in Italian lower (Grade 8: age 13) and upper secondary state schools (Grades 9–11: ages 14–16). The analyses are based on data from the Italian Integration of the Second Generation survey conducted during the 2014/15 school year. Our results show that students having Chinese, Moroccan, Moldovan and other non‐European Union Eastern European origins assume the lowest levels of lyceum aspiration after also considering compositional effects. Conversely, the largest proportion of migrants attending school in Grades 9–11 have higher levels of university aspiration compared to non‐migrants. When considering the role of migratory generation, lyceum and university aspirations are positively associated with the acculturation process of migrants. Furthermore, we found that high family expectations, social relationships and self‐perception benefits of studying have positive associations with both lyceum and university aspirations, especially among migrants.