Data Collection Methodology Research Articles

Spatial Distributions of Yield Gaps and Production Increase Potentials of Spring Wheat and Highland Barley in the Qinghai-Tibet Plateau

Low grain yield caused by high altitude; cold climate; small, cultivated land area, and poor soil fertility is the critical factor posing a potential risk to local food security in the Qinghai-Tibet Plateau (QTP). Analyzing spatial distribution of the increase potential of grain production in the QTP could be contributable to developing a regional increase in the space of grains to ensure food security. Taking spring wheat and highland barley as objectives, this study simulated the annual potential yields of spring wheat and highland barley at the site level. They estimated their yield gaps and production increase potentials at the regional and county level and mapped their spatial distribution in 2020, based on the methodologies of the literature data collection, using the WOFOST model and GIS analysis. The yield gaps of spring wheat and highland barley were 3.7 and 2.4 t ha−1 for the whole QTP, accounting for 51.4% and 39.5% of their potential yields, respectively. At the county level, the yield gap ranges of spring wheat and highland barley were 1.5–7.0 t ha−1 and 0.3–5.9 t ha−1 across the QTP, respectively. When the yield gap was fully developed, spring wheat and highland barley productions had the potentials of 497.4 and 717.4 Kt for the whole QTP, equal to 118.2% and 75.2% of their current total production, respectively. Spatially, the counties with a large increase potential of spring wheat were mainly distributed in Haidong, Hainan, Xining, Shannan, Nyingchi, and Lhasa, while those with low potential were located in Xigaze and Shannan. Regarding highland barley, Lhasa, Shannan, Xigaze, Yushu, and Hainan had a larger potential to increase. To increase grain production in the QTP, the priority should be given to the shrinkage of the yield gap in the counties with larger potentials to increase, such as Hainan, Shannan, Lhasa, etc., through improving the irrigation rate and fertilizer usage in the farmland.

The application of the sensemaking perspective for the examination of employees’ behavioural responses to the HR chatbot

Abstract Background and Purpose The emergence of new technologies affects different business areas, including HR activities. Employee communication is an HR activity that can be automated with the application of chatbots. Besides the numerous advantages these artificial entities offer, the challenges generated by them also need to be considered. One such challenge is user acceptance, which plays a substantial role in the implementation. This study aims to explore employees’ behavioural responses to HR chatbots. Thus, we applied the sensemaking perspective, according to which new, unknown phenomena induce the need for interpretation in individuals that simultaneously shape individuals’ behaviour toward the phenomenon. Methodology For data collection, we conducted semi-structured interviews that were analysed with interpretive phenomenological analysis (IPA). The sample consisted of 6 HR professionals and ten general users. The study took place at the Hungarian organisations of a multinational company. Results The analysis revealed that subjects who attributed positive meanings to the HR chatbot typically engaged in actions that aligned with organisational expectations, i.e., using the digital assistant became part of their routine. Interestingly, the closer HR professionals are to technology in their work activities, the more positively they perceive it. However, having ambivalent feelings towards technology resulted in occasional use or avoidance, while experiencing negative feelings led to the rejection of use. Conclusion We explored the different meanings employees attributed to the HR bot and their actions directed towards it both in the initial and transitional technology adoption phase. The results contribute to understanding how an HR chatbot can be successfully implemented in an organisation.

Descriptive Epidemiology of Pediatric Inflammatory Bowel Disease in Oceania: A Systematic Review and Meta-Analysis.

Pediatric inflammatory bowel diseases (IBDs) are chronic, idiopathic illnesses of the digestive tract, which can impact adversely on children's quality of life and burden health systems. International studies have shown these diseases are increasing. The aim was to describe pediatric IBD epidemiology across Oceania by conducting a systematic review and meta-analysis of incidence and prevalence. Medline, EMBASE and Web of Science databases were searched in October 2022 for studies reporting rates of IBD, Crohn disease (CD), or ulcerative colitis (UC) in children (≤19 years). Several data collection methodologies were included and pooled estimates of incidence and prevalence were calculated using a random effects model with I2 measures of heterogeneity. Nineteen articles provided 15 incidence and 7 prevalence studies. Fourteen studies were from Australia, 8 studies from New Zealand, and no studies were found from the Pacific Islands. Study dates ranged from 1950 to 2020 with 11 studies using population-based designs. Pooled estimates for annual incidence were IBD 4.1 (3.4-4.8, I2 = 98.7), CD 2.3 (1.9-2.7, I2 = 98.6), and UC 0.9 (0.6-1.1, I2 = 96.8) per 100,000 person-years. Prevalence rates were IBD 36.0 (23.5-48.5, I2 = 98.4), CD 23.2 (6.6-39.8, I2 = 97.8), and UC 7.6 (2.7-12.5, I2 = 99.6) per 100,000 persons. Pediatric IBD is prevalent in Oceania with high incidence rates, particularly for CD. Low rates of IBD were observed in indigenous Australian, Māori, and New Zealand Pacific children and there were no studies from the Pacific Islands highlighting this as an area in need of further research.

The Implementation of an Online Distance Learning Program with an Independent Curriculum-Based on Improving Child-Parent Relations

The transition from the 2013 curriculum (K-13) to the Independent Curriculum in Indonesia represents an evaluative measure aimed at enhancing the overall educational standards in the country. Homeschooling Kak Seto Surabaya is a non-formal educational institution program that incorporates an independent curriculum. The establishment of a strong and effective partnership between students and parents plays a pivotal role in the attainment of learning objectives within distance learning programs. Hence, the purpose of this study was to examine the implementation of the independent learning curriculum in the context of distance learning programs, specifically focusing on its impact on enhancing the parent-child relationship within the Homeschooling Kak Seto Surabaya. The employed methodology is a qualitative approach utilizing a case study design. The employed methodology for data collection encompassed participatory observation as well as semi-structured interviews conducted with both managers and parents of students. The data analysis model utilized in this study is the Miles and Huberman model, which encompasses the sequential stages of data collection, data reduction, data presentation, and drawing conclusions. The findings of this study indicate that the implementation of an independent curriculum has a significant impact on enhancing the relationship between children and parents during the learning process.

A Guide to Data Collection for Computation and Monitoring of Node Energy Consumption

The digital transition that drives the new industrial revolution is largely driven by the application of intelligence and data. This boost leads to an increase in energy consumption, much of it associated with computing in data centers. This fact clashes with the growing need to save and improve energy efficiency and requires a more optimized use of resources. The deployment of new services in edge and cloud computing, virtualization, and software-defined networks requires a better understanding of consumption patterns aimed at more efficient and sustainable models and a reduction in carbon footprints. These patterns are suitable to be exploited by machine, deep, and reinforced learning techniques in pursuit of energy consumption optimization, which can ideally improve the energy efficiency of data centers and big computing servers providing these kinds of services. For the application of these techniques, it is essential to investigate data collection processes to create initial information points. Datasets also need to be created to analyze how to diagnose systems and sort out new ways of optimization. This work describes a data collection methodology used to create datasets that collect consumption data from a real-world work environment dedicated to data centers, server farms, or similar architectures. Specifically, it covers the entire process of energy stimuli generation, data extraction, and data preprocessing. The evaluation and reproduction of this method is offered to the scientific community through an online repository created for this work, which hosts all the code available for its download.

Transfer of Airport PAS Administration Procedures from Offline to Online at the Makassar Regional V Airport Authority Office

Airport Public Address System (PAS) Card is a limited area entry permit card in the Airport area. Airport PAS is issued by the Directorate General of Civil Aviation. In order to improve security at airports, Minister of Transportation Regulation Number PM 167 of 2015 has been stipulated which is an amendment to Minister of Transportation Regulation Number PM 33 of 2015 concerning Access Control to Limited Security Areas at Airports. In it there are several articles that regulate airport security areas, control of entrances to airports and administrative sanctions for violating airport security regulations. To find out the form of transition of airport pass administration procedures from offline to online at the Makassar Region V Airport Authority Office? This research is a qualitative research with a comparative descriptive type of research that uses data collection methodologies with literature studies, observations and interviews. Sugiyono (2018), explains the notion of a qualitative research method is a research method that is based on the philosophy of postpositivism, used to research on natural object conditions, (as opposed to experiments) where the researcher is the key instrument, data collection techniques are carried out by triangulation (combined ), data analysis is inductive/qualitative in nature, and the results of qualitative research emphasize the meaning of generalizations. Comparative descriptive qualitative research in this study is used to describe and analyze the transition of airport pass administration procedures from offline to online at the Makassar Region V Airport Authority Office from the side of officers and applicants.

KEKERABATAN BAHASA TETUN DAN BAHASA DAWAN (LINGUISTIK HISTORIS KOMPARATIF)

This research aims to describe the relationship between the Tetun and Dawan languages which is entitled “The kinship relationship between the Tetun and Dawan languages” using the theory of comparative historical linguistics. The method used qualitative and quantitative approaches using a lexicostatistic technique. The data collection methodology and technique used are effective methods of observation, interviewing, and recording. This research was conducted at the village of Rafae, Raimanuk District, Belu Regency. The research instrument used in the interview was a list of questions containing 200 basics (Swadesh) vocabulary. The results showed that there was a relationship between the Tetun and Dawan languages, attempts through 33 pairs of related words, with 5 pairs of identical words category, phonetic match 10, phonetically similar 6, and a different phonemic 12. The level of kinship Bahasa Tetun and Bahasa Dawan has a kinship at the level of rock (stock) with a percentage of 16,5 %.

Dampak Perkembangan Pariwisata Terhadap Lingkungan Di Pantai Cacalan Banyuwangi

The tourism industry is crucial to the success of initiatives to enhance government income. The tourist industry in Indonesia needs to grow since the country is home to both breathtaking natural beauty and cultural variety. Banyuwangi Regency is one of the regions helping to boost the country's GDP by attracting more tourists. The methodology of this study is qualitative. Qualitative research is a methodology that sheds light on a specific social situation by an accurate description of reality, shaped by words derived from appropriate data collection and analytic methodologies used to information gathered in natural settings. Data is obtained from primary data and secondary data. The purpose of this article is to determine the impact of tourism on the environment in Cacalan Beach in the management and development of Cacalan Beach. The results obtained are known first, the development of tourism has been very good in terms of aspect 5 A. Second, facilities and infrastructure have developed. Third, in its development, public awareness is still not optimal. Fourth, there is a clean tourism program that can preserve nature.
 Keywords: Tourism Development, Impact, environment

Increasing Individual Taxpayer Compliance by Taxpayer Awareness

The objectives of this study were to ascertain and examine the level of taxpayer awareness, individual taxpayer compliance, and the impact of taxpayer awareness on individual taxpayer compliance at the Pratama Tax Office. The employed data analysis techniques encompassed descriptive analysis and verification analysis. The data collection methodology employed in this study entailed disseminating questionnaires to tax officials at a specific Pratama Tax Office in Bandung City. The sample consisted of 40 individuals who were directly involved in the subject matter under investigation. The study employed the Exhaustive Sampling (Census) technique under Nonprobability Sampling. The research findings revealed that the product-moment correlation analysis yielded a coefficient of 0.860, indicating a highly significant and robust relationship between the variables. The results of the simple linear regression analysis indicate that there is a positive relationship between Taxpayer Awareness and Individual Taxpayer Compliance. The equation derived from the analysis is Y = 8.305 + 0.834X, where Y represents the level of Individual Taxpayer Compliance, and X represents Taxpayer Awareness. The coefficient of determination, which measures the proportion of variance in Individual Taxpayer Compliance (Y) explained by Taxpayer Awareness, is 0.739. This condition indicates that Taxpayer Awareness has a significant influence of 73.9% on Individual Taxpayer Compliance. The remaining 26.1% of the variance in Individual Taxpayer Compliance is attributable to other factors not examined in this study, including tax amnesty, e-filing, tax audits, tax penalties, tax bills, and other relevant variables.

Compensatory effects of individual differences, language proficiency, and reading behavior: an eye-tracking study of second language reading assessment

Reading in a second language (L2) is a complex process that incorporates linguistic knowledge and literacy abilities, as well as strategic competence to approach different types of reading tasks depending on reading goals. However, much of the previous research was limited to correlational studies and focused on the relative contribution of broad categories of L2 proficiency and first-language (L1) literacy to L2 reading comprehension. However, investigations into L2 reading performance can benefit from advances in real-time, concurrent data collection methodologies such as eye-tracking. This study utilized eye-tracking methods to examined L2 reading comprehension of 102 readers across three different reading tasks [Cloze reading, Multiple-choice (MC) quiz, and reading-to-summarize], comparing the comprehension scores to L2 proficiency, individual differences (reasoning, working memory, motivation) and reading behavior (eye-tracking metrics related to attention to reading texts and tasks, length of fixations). Results indicate that the score on each task could be modeled each using a different mix of predictors, with the cloze task being most strongly predicted and the MC task being least predicted. The Summary task was in-between, but with a highly interpretable model. Interactions between fixation duration and cognitive abilities were found, showing how efficient fixation is generally important for comprehension, but the impact can be compensated for with motivation and reasoning ability.

Emotional speech Recognition using CNN and Deep learning techniques

Emotions are considered an integral and vital part of human life. It acts as a means of expressing one's opinions and informing others about one's bodily and emotional well-being. The Speech Emotion Recognition (SER) system is used to extract and predict the emotional tone of a speaker through audio signals. Universally, emotions can be often categorized and grouped into mere types like Anger, Happiness, Sadness, and even Neutral emotional state. One can then use this as a criterion to develop a system provided, they are equipped with finite and required resources. Then through proper training and procedure, the system can be made to recognize the speaker’s emotional state. In these situations, speech emotion detection is performed using spectral and prosodic capabilities because each of those aspects includes the essential data to determine the speaker's emotional state. Mel-frequency Cepstral Coefficients (MFCC) are one of the spectral features that can be used to detect the speaker’s emotional state. Frequency, loudness, and pitch of a sound signal are some of the many available prosodic features that would then be able to help train and construct a machine-learning model that can uniquely identify and differentiate between the underlying emotions present in a given speech signal. It is known that the pitch of an audio signal is unique and can be used as a measure to easily distinguish between different audio signals. They can be detected from the selected features, allowing us to classify the gender type of the speaker. Support Vector Machines (SVM) are supervised learning models that examine the data for regression and classification in machine learning. They generally identify and classify the gender of the speaker in the case of a Speech Emotion Recognition system. Furthermore, some studies rely on Radial-Basis Function (RBF) and Back Propagation networks. They are capable enough to be used to identify and recognize the human emotions in the signal constrained on specific and selected features. This study presents a Speech Emotion Recognition system that outperforms an existing system in terms of data, feature selection, and methodology. Its goal is to identify speech precepts based on emotions more accurately, on average 78% accurately, and with fewer false positives. The paper aims to discuss the importance of emotions in human communication and introduce the concept of Speech Emotion Recognition, which extracts and predicts the emotional tone of a speaker through audio signals. It explains how spectral and prosodic features can be used to identify the emotional state of the speaker, with MFCC being one of the commonly used spectral features. Prosodic features such as pitch, loudness, and frequency can also be used to identify gender and differentiate between emotions in speech signals. SVM, RBF, and Back Propagation networks are machine learning models used in speech emotion recognition; these more advanced models outperform existing systems in data collection and feature selection methodology, achieving an accuracy rate of 78% with fewer false positives.

Концепция глобального упадка насилия Стивена Пинкера и реакция научного сообщества

Two widely discussed books on violence by Steven Pinker offer a grand metanarrative about the movement of humanity towards reason, progress, and humanism. The article briefly generalizes the main author’s methodological predispositions. The article also deals with the conceptual analysis of the theory. The scholar’s theory is based on several key ideas: the state, gentle commerce, the taming of manners, and the Enlightenment. The main point is that society, passing successively through such stages-ideas, moves in the direction of greater progress and limitation of violence. As for the criticisms, we illustrate the limitations of the method chosen and the inadequacy of its objectives. First, the author uses the criminological method of counting the number of murders per hundred thousand in a population, which can only characterize one segment of violence. Secondly, the measured violence does not always correlate with other violent crimes. We also point out objective difficulties in working with the available statistics. In particular, we are confronted with fragmented data and incomparable methodology of data collection from predecessors. In addition, we reveal many mistakes, inaccuracies, and in many cases even deliberate discrepancies within representative data. Steven Pinker often resorts to overly sweeping generalizations and comparisons of difficult-to-compare cases. Many scholars have also noted the author’s use of unprofessional literature. In terms of conceptual ideas, critics note the author’s ignorance of contemporary debates and disregard for differences in the works of those classics used in the work. We should also note the rather unfriendly tone of the discussion on the part of all the participants, since the dispute is about big ideas, which often leads to direct insults and labeling. In conclusion, we praise the communicative gesture of challenging the scientific community, but it seems clear that the main goal to give proof towards violence decline is inconclusive.

Effect of Liquidity and Profitability on The Level of Financial Distress Using the Altman Z-Score Model

This research aimed to examine the impact of the current ratio and return on assets on the degree of financial distress in the automotive and component manufacturing sectors of the Indonesia Stock Exchange during the period of 2015–2020, utilizing the Altman Z-score model. Furthermore, the objective of this investigation is to examine the primary determinant between the current ratio and return on assets about the degree of financial distress, utilizing the Altman z-score model, within the automotive and component sub-sector manufacturing firms that are publicly traded in the Indonesia Stock Exchange from 2015 to 2020. The present study employs a descriptive-verification research methodology. The present study employs secondary data from information sourced from https://idx.bei.co.id/. Conduct data collection methodologies utilizing documentation techniques. The present study has selected a population of 13 manufacturing companies in the automotive and component sub-sectors listed on the Indonesia Stock Exchange from 2015 to 2020. Non-Probability Sampling was utilized to determine the sample size of ten companies that meet the established criteria. The data underwent analysis through the utilization of multiple linear regression as well as hypothesis testing via the t-test and F-test. The findings of the present investigation suggest that the current ratio and the return on assets exhibit a noteworthy and favorable impact on the degree of financial distress, as measured by the Altman z-score, at a rate of 73.4%.

The Cross-Generational Impacts of Digital Remarketing: An Examination of Purchasing Behaviours among Generation Z and Generation Y

The dynamically evolving digital environment makes crucial the remarketing, a strategy used to re-engage consumers who previously showed interest in a product or service. However, the influence of this tactic on different generations, specifically the Generation Y and the Generation Z, remains under-explored. This paper investigates the impact of digital remarketing strategies on the purchasing behaviours of Generation Y (Millennials) and Generation Z consumers, a topical exploration of the rapidly evolving field of digital marketing. A mixed-method approach, utilising both qualitative and quantitative methodologies for data collection is employed. It focuses on five key remarketing tactics: email, display, social media, search engine, and video remarketing. The total sample size was 316 participants, with 147 Gen Y participants accounting for 46.5% of the total and 169 Gen Z participants accounting for 53.5% of the total. The results reveal significant differences in the response of these generations to different remarketing tactics, thus offering an unprecedented perspective on their unique purchasing behaviours. The study concludes with valuable insights for both academic discourse and practical applications. The research enriches the existing body of knowledge on digital remarketing techniques for scholars, and advocates for further studies in the area, especially concerning unexplored remarketing tactics. For practitioners, it delivers actionable insights for the development of generation-specific marketing campaigns, thereby improving their overall performance in the digital marketplace. Consequently, this paper provides an essential foundation for the enhancement of remarketing strategies, catering to the evolving needs and expectations of Generation Y and Z consumers.

Racial and Ethnic Disparities in Retirement Outcomes: Impacts of Outreach

We review select literature on racial and ethnic disparities in retirement outcomes in the United States and the impact of outreach on such outcomes. First, there are significant disparities in retirement outcomes, reflecting a long history of racism and structural barriers. Second, there is comparatively little work on the differential impact of retirement outreach across race and ethnicity. Future work should consider designing interventions that cater to the needs of specific demographic groups, for example, by embracing the fact that Blacks, Hispanics, and Whites acquire retirement information from different sources. Future work should also incorporate behavioral insights, particularly from prior interventions, and innovate on methodologies for data collection, linking, and analysis.

Assessment of Youth Unemployment Impact on the Socio-Economic Development of Ondo State: A Study of Akure South Local Government Area

Unemployment has become the major source of concern in every society. In recent time, it is often presented as a major problem that is seen to undermine the social-economic development of Nigeria ditto Ondo State. In 2021, the unemployment rate in the country was put at 33% the highest in 13 years. From the figures released by the National Bureau of Statistics (NBS), about 21, 765, 614 Nigerians are jobless within the age group of young people who are between 15-34 years. In comparison to other 181 countries of the world with up-to-date labour data, Nigeria ranks the 41st country with highest unemployment rate. This study assessed the magnitude and dimension of unemployment and its implications on socio-economic development of ondo state referencing unemployed youth in selected communities in Akure South local government area. Several methods were adopted by this study to elicit information; Primary sources of generating data through administration of questionnaires and interviews while secondary sources involve data from journals, articles and internet materials. The study adopted triangulation mixed research methodologies for data collection. Analysis of quantitative data was done using descriptive statistics (sample frequency tables, percentages and numbers.) while qualitative data were analyzed separately. Questionnaires were administered to 350 respondents and 16 interviewees between the ages of 18-35 years through multistage sampling technique. The study relied on Keynesian and Marxist theories as theoretical fulcrum to discuss the multi- dimensional situation of unemployment in Nigeria .The findings from the study revealed that corruption, neglect of Agricultural sector ,infrastructural decay , Bad Leadership and bad governance, unfavourable government reforms and policies, unfavourable terms and conditions for jobs recruitments, ineffective education system, insecurity are among major factors contributing to the rising unemployment in Akure south local government area of Ondo state. The findings also revealed socio-economic implications of youth unemployment to include; poverty, criminalities, insecurity, substance, addiction, psychological effects, health issues, brain drain, dysfunctional social and emotional relationship among others. The study concluded that there are many deleterious socio-economic implications associated with youth unemployment in Akure south local government area of Ondo state.Against this backdrop, the study recommended strong anti-corruption crusades by governments at all levels, infrastructural development, diversification of economic, bail-out funds for ailing industries, enthronement of good leadership and good governance, introduction of Entrepreneurial trainings as part of school academic system and aggressive fight against insecurity as panacea that will checkmate the unemployment scourge.

Machine learning based canine posture estimation using inertial data.

The aim of this study was to design a new canine posture estimation system specifically for working dogs. The system was composed of Inertial Measurement Units (IMUs) that are commercially available, and a supervised learning algorithm which was developed for different behaviours. Three IMUs, each containing a 3-axis accelerometer, gyroscope, and magnetometer, were attached to the dogs' chest, back, and neck. To build and test the model, data were collected during a video-recorded behaviour test where the trainee assistance dogs performed static postures (standing, sitting, lying down) and dynamic activities (walking, body shake). Advanced feature extraction techniques were employed for the first time in this field, including statistical, temporal, and spectral methods. The most important features for posture prediction were chosen using Select K Best with ANOVA F-value. The individual contributions of each IMU, sensor, and feature type were analysed using Select K Best scores and Random Forest feature importance. Results showed that the back and chest IMUs were more important than the neck IMU, and the accelerometers were more important than the gyroscopes. The addition of IMUs to the chest and back of dog harnesses is recommended to improve performance. Additionally, statistical and temporal feature domains were more important than spectral feature domains. Three novel cascade arrangements of Random Forest and Isolation Forest were fitted to the dataset. The best classifier achieved an f1-macro of 0.83 and an f1-weighted of 0.90 for the prediction of the five postures, demonstrating a better performance than previous studies. These results were attributed to the data collection methodology (number of subjects and observations, multiple IMUs, use of common working dog breeds) and novel machine learning techniques (advanced feature extraction, feature selection and modelling arrangements) employed. The dataset and code used are publicly available on Mendeley Data and GitHub, respectively.

Disposable Diaper Usage and Disposal Practices in Samora Machel Township, South Africa

Single-use disposable diapers have a major impact on climate change due to greenhouse gas emissions from landfills, especially those that are unlined, and particularly when such diapers are not well-managed and dumped in water courses and open spaces or burnt. The aim of this study was to explore the current usage and disposal practices of disposable diaper users in Samora Machel, a township in Cape Town, South Africa. The findings were to be used to inform the design and implementation of a pilot diaper collection model to follow. This urban/peri-urban area comprises lower-income, high-density communities in formal basic housing, with many backyarders and informal shacks. The dumping of diapers in open spaces and sewage systems causes severe problems. Therefore, we employed a theoretical socio-ecological system approach to guide the understanding of these complex environmental issues; the data collection methodology entailed a community-based participatory study process. Four hundred and eight (408) questionnaires consisting of quantitative and qualitative answers were codeveloped with members of the community and completed by trained community-based fieldworkers. A community walkabout and two focus groups provided rich data. The results show that complex waste streams such as disposable diapers and the related environmental issues are testing the limits of current management approaches; managing disposable diapers in underserved low-income communities creates a major burden for these already fragile communities. Single solutions will not suffice for these complex problems, so innovative waste management systems need to be codesigned with communities and relevant stakeholders to ensure sustainability, equality, and social justice.

Entrepreneurial Accounting as a Driver of SMEs’ Sustainability: A Systematic Review

Purpose: This paper conducted a systematic review of entrepreneurial accounting (EA) articles published over the last ten years (2012 – 2022). Using the Systematic Qualitative Assessment Techniques (SQAT) to review 79 EA journal articles to provide an understanding of the antecedent and importance of the concept on business venture survival or otherwise.
 Methodology: This paper analysed the time distribution, geographic distribution, theory used, article type, data collection methodologies and themes of the EA article reviewed.
 Findings: The key findings show that EA interest has increased in Asia and Africa over the last decade, while Oceania (Australasia) were least represented. The most striking theme out of the five identified is the impact of EA as the heart of business ventures’ sustainability, while the resource-based theory was most used to provide a clear understanding of the concept of the need for inherent management and cost accounting skills.
 Implications: Findings from the review confirm the importance of entrepreneurial accounting (EA) in SMEs as scholarly work has increased in recent times in the most developing economies, especially in Asia and Africa. This study recommended that EA skills should form part of the funding requirements for start-ups in accessing finance.
 
 Keywords: entrepreneurial accounting, systematic review, sustainability, financial literacy.

Peran Perpustakaan Daerah Kabupaten Karo Dalam Pemanfaatan Program Literasi Inklusi Sosial

The existence of social inclusion-based regional libraries is a regional library that helps develop community potential by improving the quality of library services in order to foster a successful and enlightened society. Regional library services must now be more proactive in inviting the public to use libraries, so that famous libraries are more than just lending and returning books. As a result, library services can be transformed by social inclusion. The purpose of this paper is to optimize libraries in order to provide individuals with the means to improve their quality of life. This study used qualitative methodology for data collection, including interviews, observations, and documentation in the regional library of Karo Regency. After collecting the data, it is evaluated by reducing the data, presenting the data, and coming up with conclusions. The findings of this study show that the Karo regional library has been able to transform its library services through the use of literacy programs aimed at encouraging social inclusion. It seems that the Karo regional library service has been transformed into a library with flexible services based on people's information needs, as evidenced by the implementation of a number of social inclusion services.