Aldila Dinanti, Indira Januarti, Rr. Sri Handayani
Abstract This study investigates the performance and science mapping of ICT adoption in SMEs through a bibliometric analysis of Scopus-indexed publications. We examine how the ICT-in-SMEs literature evolved over 1997–2024 and where accounting and sustainability themes are situated within that corpus. Proxies are operationalized via author and index keywords, co-word structures, and controlled overlays linking ERP, e-invoicing, and cloud to sustainability-accounting mechanisms (measurement, reporting, assurance). The dataset comprised 450 records (1997–2024), of which 442 English-language documents were analyzed; computation and visualization used Biblioshiny (bibliometrix, R) and VOSviewer. We trace the field’s evolution—particularly how ICT underpins accounting for sustainability—identifying key intellectual structures, turning points, and emerging themes. Results show Alshamaila et al. (J Enterp Inf Manag 26(3):250–275, 2013. https://doi.org/10.1108/17410391311325225 ) as the most-cited document (577 citations, Journal of Enterprise Information Management; as of 28 May 2024); the same journal records the highest local H-index; Rogers and Venkatesh are prominent cited authors; “information and communication technologies” is the most frequent topic; and the United Kingdom emerges as a collaboration hub. Beyond mapping, we interpret platform-centric themes (ERP, e-invoicing/e-commerce, cloud) as digital accounting infrastructures that generate auditable sustainability information (e.g., cost/energy/material accounts, supplier compliance, payment traceability). We integrate thematic clusters with TOE/DOI mechanisms to explain antecedents of these data-generating routines in SMEs. The findings guide future research and adoption strategies, advancing SDG-oriented accountability through efficient, effective digital accounting records.
Historic and cultural villages in China are increasingly challenged by rapid urbanization, uneven commercial development, and fragmented preservation mechanisms. Understanding their spatiotemporal distribution and the factors shaping it is crucial for advancing the integrated development of cultural heritage conservation, ecological sustainability, and socio-economic growth. This study examines 487 historic and cultural villages using the nearest neighbor index (NNI) and kernel density analyses to reveal spatial differentiation patterns. Vector buffer analysis and the geographic detector method were further employed to identify the key drivers of village distribution. The results indicate that: (1) historic and cultural villages exhibit a distinctly clustered spatial pattern, characterized by “more in the southeast, fewer in the northwest; more in the northeast, fewer in the southwest” (NNI = 0.44, Z = –23.52, <i>p</i> = 0.00); (2) provincial-level spatial density demonstrates clear stratification, with high-density clusters concentrated in the Yangtze River Delta, southern Anhui, the Fujian–Zhejiang–Jiangxi junction, and along the Yellow River in Shanxi–Shaanxi–Henan. From the fifth to seventh designation batches, kernel density peaks (maximum ~0.11 × 10<sup>−2</sup>) increased significantly, reflecting stronger spatial clustering; and (3) the spatial distribution of villages is jointly shaped by natural geography, socio-economic conditions, transportation infrastructure, visitor markets, and tourism resources. Among these, nighttime light intensity was identified as the most influential individual factor (q = 0.6132), while the combination of slope aspect and per capita disposable income emerged as the dominant factor pair (q = 0.966).
Abstract Industrialization represents a key policy option for sustainable economic growth, and governments must pursue structural transformation. The Ethiopian government has been designing and implementing different industrialization policies to achieve the desired structural transformation of the country. However, an unintended jump or massive twisting was observed in the economic structure, mainly due to the shift in the dominance of output from agriculture to the service sector in the country. Hence, this study investigates the determinants of unintended service sector output growth in Ethiopia from 1990 to 2022 using the autoregressive distributed lag (ARDL) model. The findings suggest that differences in labor productivity among agriculture, manufacturing, and the service sector positively influence service sector output growth in the country. This implies that labor productivity disparities play a significant role in shaping the growth trajectory of the service sector, with higher productivity levels in services and low productivity in other sectors contributing to the faster expansion of the service sector. In addition, variables such as per capita GDP, gross fixed capital formation, and credit to the private sector are found to have a favorable impact on service sector growth, while openness has a negative effect. This study adds to the understanding of unintended structural transformations in developing countries by highlighting how labor productivity disparities can drive shifts in economic dominance, particularly the rapid growth of the service sector at the expense of traditional sectors like agriculture. Furthermore, it emphasizes that such transformations may not align with national development objectives if not managed strategically. Therefore, enhancing labor productivity in agriculture and manufacturing through technology, training, and education is crucial to achieve the desired structural change. In addition, increasing gross fixed capital and improving access to credit for the private sector could further stimulate service sector expansion. Finally, encouraging domestic industries and implementing protective measures against unfair competition may mitigate the adverse effects of trade openness on service sector growth in Ethiopia. These insights are crucial for policymakers aiming to navigate structural transformations effectively while promoting sustainable economic development.
We develop a resource-efficient methodology for measuring economic outlook in news text that combines document embeddings with synthetic training data generated by large language models. Applied to 27 million news articles, the resulting indicator significantly improves GDP growth forecast accuracy and captures sentiment shifts weeks before official releases, proving particularly valuable during crises. The indicator outperforms both survey-based benchmarks and traditional dictionary methods and is interpretable, allowing identification of specific drivers of economic sentiment. Our approach addresses key institutional constraints: it performs sentiment classification locally, enabling analyses of proprietary news content without transmission to external services while requiring minimal computational resources compared to direct large language model classification.
One of the themes that have been approached more and more within the specialised literature is being represented by economic cycles. The analysis of these is very useful in the long term predictions, in finding solutions for the economic raise and for detecting the economic crisis. At the same time, it is underlined in a lot of scientific and research papers, the importance of the sustainable development in the present and future society. In this paper we intend to bring contributions to the study of the cycles of a sustainable economy and we will analyse it having in mind the purpose of creating the sustainable economy. We will demonstrate the fact that curves that represent graphically all these, are not simple logistics anymore, bi-logistics or multilogistics curves, but curves in plan that are obtained by composing logistics functions with the function of the sustainable development or with the function that shapes the economic component of it mathematically. We will present an interpretation of mathematic models within the frame of the sustainable development.
In an economic environment characterized by rapid changes and significant technological innovations, the
printing industry in Romania is undergoing a period of transformation and adaptation. Although traditional, this
industry plays a vital role in the national economy by contributing to the production and distribution of cultural and
commercial goods. In the face of these transformations, risk management becomes a critical component for ensuring
the sustainability and competitiveness of firms in this sector. In our study, we will evaluate the economic performance
and associated risks of the top 20 companies operating in the Romanian printing industry, registered under the NACE
code 1812, selected based on their turnover in 2023. The analysis covers a seven-year period from 2017 to 2023,
providing a detailed assessment of the evolution of these companies. This comparison allows for a deep understanding
of the sector's dynamics and how different companies manage risks and optimize their financial performance. The
study is structured around three main classes of indicators: economic, profitability, and risk. Each class of indicators is
analyzed to identify significant trends and variations in company performance, as well as to assess the impact of risk
management strategies. Within the analysis of risk and profitability indicators, modern methods and techniques for risk
mitigation and profitability enhancement are introduced, aiming to provide practical and innovative solutions for
companies in the industry.
Commercial geography. Economic geography, Economics as a science
Knowing that nowadays information is one of the strongest weapons a company can have, it has a relevant role
in the decision-making part of the company. Building the right structures and using the right tools for these structures
is essential for a certain company or business to be a leader in the field where it operates. Building IT infrastructure in
business is a must for businesses today, one of the most innovative areas today is undoubtedly Business Intelligence. BI
has restructured the company's decision-making processes, becoming the main pillar on which decision-making is
based. This paper sheds light on the main concepts related to BI, also it focuses on the main techniques of Business
Intelligence, BI techniques, and analysis of the current situation of use and involvement of BI in Albanian companies.
Commercial geography. Economic geography, Economics as a science
This paper explores the evolution and future perspectives of agricultural policies in Tunisia, focusing on their role in enhancing food security. The agricultural sector, while contributing around 9% to GDP and employing 16% of the active population, faces numerous challenges including water scarcity, climate change, and economic pressures from international trade. The study identifies that despite economic diversification, agriculture remains crucial for rural livelihoods and food security. Also,
the paper critiques existing policies, particularly the inefficiencies in subsidies and the complexity of administrative procedures, which disadvantage small farmers. The
analysis underscores the need for policy reforms aimed at improving farmers’ incomes, reducing policy costs, and enhancing efficiency. Recommendations include developing infrastructure, promoting modern agricultural technologies, and adjusting trade policies to better balance export promotion with import substitution. The study concludes that a dynamic and transparent agricultural policy, responsive to international changes and inclusive of all farmer categories, is essential for sustainable agricultural development and food security in Tunisia.
Our research aims to examine the effectiveness of university teaching via “The Facebook Group,” especially in teaching entrepreneurial culture. The choice of the latter as a subject of study is explained, on the one hand, the specificity of this unit and on the other hand, the digitization of the economy and the emergence of digital startups, on the other hand. To do this, we conducted a survey of questionnaire among the students of different disciplines from Iset Zaghouan during the 2022/2023 and the 2023/2024 academic years.
Through this empirical work, we seek to explore the role that the digital social network Facebook can play in teaching “Business Creation” through online collaborative work between students from different disciplines within the same higher education institution.
Commercial geography. Economic geography, Marketing. Distribution of products
Nicole Immorlica, Brendan Lucier, Aleksandrs Slivkins
Traditionally, AI has been modeled within economics as a technology that impacts payoffs by reducing costs or refining information for human agents. Our position is that, in light of recent advances in generative AI, it is increasingly useful to model AI itself as an economic agent. In our framework, each user is augmented with an AI agent and can consult the AI prior to taking actions in a game. The AI agent and the user have potentially different information and preferences over the communication, which can result in equilibria that are qualitatively different than in settings without AI.
Being a happy student during unprecedented times depends on coping behavior that lessens their anxiety level while learning. This article stresses to explain the level of happiness and coping behavior amid the COVID-19 pandemic while learning mathematics online. The study also determines the different factors of happiness and coping behavior using a statistical model. Primary data were gathered through a Google form survey of 233 students at Visayas State University during the second semester of the academic year 2021-2022. Results showed that students are moderately happy and coping with learning mathematics amid the challenges they have experienced in distance learning. The findings revealed that the students’ happiness level is dependent on their coping strategies in learning. Hence, students coping behavior in the learning process will positively influence their well-being and cognitive thinking. The regression model (I) reveals that the factor of being a happy student in learning mathematics is to have an older age or more experience. In addition, students are happy if their teachers are helping them with their learning activities online. Meanwhile, the regression model (II) depicted that the students’ coping behavior is influenced by study habits, money spent on their internet load, teacher support, and teachers’ strategies on how the learning environment is comfortable. Hence, teachers must develop a positive attitude towards their students and give them activities that are suitable and appropriate for online learning. Furthermore, it is recommended that the mathematics curriculum must be enhanced concerning distance education and students’ well-being.
Our aim is to identify the level of adoption of green practices at the university, and the problem was: what is the effect of green practices on reducing costs at the University of Medea? This is by testing the hypothesis that green practices will reduce costs. For this propose a questionnaire was developed to collect data from 75 persons from professors and administrators who were selected using the appropriate sampling method. The results showed that it is possible to adopt green practices in universities.
Commercial geography. Economic geography, Marketing. Distribution of products
تركز إشكالية هذه الدراسة على الدور الذي يحتله إصلاح وعصرنة الإدارة الضريبية في زيادة التحصيل الضريبي في الجزائر لما لهذا الأخير من أهمية في تمويل التنمية، حيث انطلقنا من فرضية أن إصلاح لإدارة الضريبية لم يساهم في الرفع من التحصيل الضريبي بالرغم من التدابير المتخذة خاصة في ظل العصرنة، وتسعى هذه الدراسة أساسا إلى تسليط الضوء على واقع التحصيل في الجزائر في ظل الجهود لمبذولة لإصلاح الإدارة الضريبية، لهذا اعتمدنا على المنهج الوصفي والتحليلي، ولقد توصلنا إلى أن تطور الحصيلة الضريبية في الجزائر بقي محتشما ولم يصل إلى النتائج التي كانت منتظرة .
The reaserch problem focuses on the role of reform and modernization of tax administration in increasing tax collection in Algeria. The main hypothysis is that the reform did not contribute to raising tax collection despite the measures taken. This study aims to highlight the reality of tax collection in Algeria (in light of administration reform). We relied on descriptive and analytical approach. where we concluded that tax revenues in Algeria remains low and does not reach the expected results
Commercial geography. Economic geography, Marketing. Distribution of products
We discuss the economic reasons why the predictions of price and return statistical moments in the coming decades, in the best case, will be limited by their averages and volatilities. That limits the accuracy of the forecasts of price and return probabilities by Gaussian distributions. The economic origin of these restrictions lies in the fact that the predictions of the market-based n-th statistical moments of price and return for n=1,2,.., require the description of the economic variables of the n-th order that are determined by sums of the n-th degrees of values or volumes of market trades. The lack of existing models that describe the evolution of the economic variables determined by the sums of the 2nd degrees of market trades results in the fact that even predictions of the volatilities of price and return are very uncertain. One can ignore existing economic barriers that we highlight but cannot overcome or resolve them. The accuracy of predictions of price and return probabilities substantially determines the reliability of asset pricing models and portfolio theories. The restrictions on the accuracy of predictions of price and return statistical moments reduce the reliability and veracity of modern asset pricing and portfolio theories.
Ben-Hur Francisco Cardoso, Eva Yamila da Silva Catela, Guilherme Viegas
et al.
Research on productive structures has shown that economic complexity conditions economic growth. However, little is known about which type of complexity, e.g., export or industrial complexity, matters more for regional economic growth in a large emerging country like Brazil. Brazil exports natural resources and agricultural goods, but a large share of the employment derives from services, non-tradables, and within-country manufacturing trade. Here, we use a large dataset on Brazil's formal labor market, including approximately 100 million workers and 581 industries, to reveal the patterns of export complexity, industrial complexity, and economic growth of 558 micro-regions between 2003 and 2019. Our results show that export complexity is more evenly spread than industrial complexity. Only a few -- mainly developed urban places -- have comparative advantages in sophisticated services. Regressions show that a region's industrial complexity is a significant predictor for 3-year growth prospects, but export complexity is not. Moreover, economic complexity in neighboring regions is significantly associated with economic growth. The results show export complexity does not appropriately depict Brazil's knowledge base and growth opportunities. Instead, promoting the sophistication of the heterogeneous regional industrial structures and development spillovers is a key to growth.
This paper addresses a key question in economic forecasting: does pure noise truly lack predictive power? Economists typically conduct variable selection to eliminate noises from predictors. Yet, we prove a compelling result that in most economic forecasts, the inclusion of noises in predictions yields greater benefits than its exclusion. Furthermore, if the total number of predictors is not sufficiently large, intentionally adding more noises yields superior forecast performance, outperforming benchmark predictors relying on dimension reduction. The intuition lies in economic predictive signals being densely distributed among regression coefficients, maintaining modest forecast bias while diversifying away overall variance, even when a significant proportion of predictors constitute pure noises. One of our empirical demonstrations shows that intentionally adding 300~6,000 pure noises to the Welch and Goyal (2008) dataset achieves a noteworthy 10% out-of-sample R square accuracy in forecasting the annual U.S. equity premium. The performance surpasses the majority of sophisticated machine learning models.
This study provides new evidence on how medical care mitigates the economic consequences of health shocks for individuals and their partners. To identify causal effects, I focus on medical scientific discoveries and exploit longitudinal administrative data for Sweden, using a triple differences design. The results indicate that medical innovation strongly mitigates the negative economic consequences of health shocks for individuals and have spillover effects on their partners. These spillovers are relatively large because medical innovation compensates for partners wage losses in conditions when welfare support for caregiving is insufficient. Overall, the findings indicate that medical innovation not only produces substantial economic gains but also reduces disease-related economic inequalities.