Business logic vulnerabilities have become one of the most damaging yet least understood classes of smart contract vulnerabilities. Unlike traditional bugs such as reentrancy or arithmetic errors, these vulnerabilities arise from missing or incorrectly enforced business invariants and are tightly coupled with protocol semantics. Existing static analysis techniques struggle to capture such high-level logic, while recent large language model based approaches often suffer from unstable outputs and low accuracy due to hallucination and limited verification. In this paper, we propose LogicScan, an automated contrastive auditing framework for detecting business logic vulnerabilities in smart contracts. The key insight behind LogicScan is that mature, widely deployed on-chain protocols implicitly encode well-tested and consensus-driven business invariants. LogicScan systematically mines these invariants from large-scale on-chain contracts and reuses them as reference constraints to audit target contracts. To achieve this, LogicScan introduces a Business Specification Language (BSL) to normalize diverse implementation patterns into structured, verifiable logic representations. It further combines noise-aware logic aggregation with contrastive auditing to identify missing or weakly enforced invariants while mitigating LLM-induced false positives. We evaluate LogicScan on three real-world datasets, including DeFiHacks, Web3Bugs, and a set of top-200 audited contracts. The results show that LogicScan achieves an F1 score of 85.2%, significantly outperforming state-of-the-art tools while maintaining a low false-positive rate on production-grade contracts. Additional experiments demonstrate that LogicScan maintains consistent performance across different LLMs and is cost-effective, and that its false-positive suppression mechanisms substantially improve robustness.
Корупція у сфері публічних фінансів є одним із ключових викликів для економічного розвитку України, особливо в умовах реформування бюджетної системи та євроінтеграційних процесів. Високий рівень корупційних ризиків у розподілі та використанні бюджетних коштів знижує ефективність державного управління, посилює недовіру до влади та гальмує соціально-економічний розвиток країни. Метою статті є аналіз сучасних підходів до боротьби з корупцією у бюджетному процесі, виявлення основних проблем і недоліків чинних антикорупційних механізмів у сфері публічних фінансів та розробка рекомендацій щодо вдосконалення антикорупційних стратегій з урахуванням міжнародного досвіду та сучасних викликів. Для досягнення поставленої мети використано комплексний методологічний підхід, що включає аналіз нормативно-правових актів, порівняльний аналіз міжнародного досвіду антикорупційної політики, статистичні методи для оцінки рівня корупційних загроз. Встановлено, що ефективне запобігання корупції у сфері публічних фінансів можливе завдяки інтеграції міжнародних практик, зокрема посиленню громадського контролю та цифровізації бюджетних процесів. Основна гіпотеза полягає в тому, що адаптація цих механізмів до українських реалій сприятиме підвищенню прозорості та ефективності управління бюджетними ресурсами. У ході дослідження виявлено, що основними проблемами у сфері боротьби з корупцією в управлінні публічними фінансами є недостатній рівень прозорості бюджетного процесу, слабкий контроль за витрачанням коштів, неефективність превентивних заходів та низький рівень відповідальності за корупційні правопорушення. Аналіз міжнародного досвіду показав, що ефективні антикорупційні стратегії ґрунтуються на комплексному підході, що включає жорсткі санкції за корупційні злочини, громадський контроль, цифровізацію бюджетних процесів та підвищення рівня інституційної спроможності органів фінансового контролю. Теоретичне значення дослідження полягає у можливості застосування отриманих результатів для подальшого вдосконалення антикорупційної політики. Практичне значення полягає у розробці рекомендацій щодо підвищення прозорості та ефективності управління публічними фінансами. Оригінальність дослідження полягає в комплексному підході до аналізу міжнародного досвіду та розробці практичних рекомендацій для України. Основні висновки відображають необхідність посилення інституційної незалежності органів фінансового контролю, вдосконалення законодавчої бази та впровадження цифрових інструментів моніторингу. Перспективами подальших досліджень є детальне вивчення можливостей адаптації європейських антикорупційних практик до українських реалій.
Economics as a science, Business records management
This paper aims to provide a qualitative evidence synthesis of research articles
employing primary qualitative data on gamification in business and management
education. The scholarly background portrays several reviews and mostly quantitative
studies on this topic, dealing mainly with research performed on gamification in education
within other subjects (i.e., computer science, IT-related, STEM). These observations enable
the need to depict also current literature ground on qualitative studies within business and
management education. We employed a qualitative thematic synthesis on 10 studies
dealing with at least one form of qualitative methods, that revealed five descriptive themes,
such as entrepreneurial self-efficacy, engagement, motivation, and social completion; selfrelated competencies; knowledge, skills, and abilities; interaction, enjoyment, fun;
gamification downsides. The aggregated analytical themes revealed the importance of
game elements, game quality and game’s real-life correspondence in influencing learning,
motivation, engagement, in building up self-competencies, fostering participants’
involvement and sense of belonging. These results posit the need for further qualitative
studies on gamification in business and management and a better understanding of
gamification’s effects on education within this field
Economics as a science, Business records management
Customer churn is one of the challenges of business management in today's complex competitive environment. For this purpose, the organization must have an efficient system to detect and analyze the factors influencing customer churn. To conduct this research, an attempt has been made to build a hybrid model based on data mining approaches from information related to 5830 customers of a chain store (demographic information and information based on customer purchase records) with 17 qualitative and quantitative characteristics. The features of higher importance were identified to build the model in the first stage using the logistic regression algorithm. In the second stage, the support vector machine algorithm, a critical supervised learning algorithm, was used to classify the customers and rank the essential features. Finally, the proposed model has been implemented as a case study in the chain store industry. The results indicate the optimal efficiency of the proposed analysis method. This research has been done to identify the influential factors in customer churn and focus on providing new solutions to reduce churn in the retail industry. Also, the results show that age, marital status, and average monthly income from the set of demographic features and how to get to know the store, the share of online shopping, and special sales from the set of features related to customer transaction records are among the most important factors affecting customer churn. In addition, practical suggestions have been presented that can be used for tactical and strategic planning of chain stores to attract and retain customers.
Bastien Baldacci, Philippe Bergault, Olivier Guéant
This paper introduces a novel methodology for the pricing and management of share buyback contracts, overcoming the limitations of traditional optimal control methods, which frequently encounter difficulties with high-dimensional state spaces and the intricacies of selecting appropriate risk penalty or risk aversion parameter. Our methodology applies optimized heuristic strategies to maximize the contract's value. The computation of this value utilizes classical methods typically used for pricing path-dependent options. Additionally, our approach naturally leads to the formulation of a $Δ$-hedging strategy and disentangles therefore the repurchase strategy from the hedging of the payoff.
Narratives play a vital role in shaping public perceptions and policy on emerging technologies like quantum technology (QT). However, little is known about the construction and variation of QT narratives across societal domains. This study examines how QT is presented in business, media, and government texts using thematic narrative analysis. Our research design utilizes an extensive dataset of 36 government documents, 165 business reports, and 2,331 media articles published over 20 years. We employ a computational social science approach, combining BERTopic modeling with qualitative assessment to extract themes and narratives. The findings show that public discourse on QT reflects prevailing social and political agendas, focusing on technical and commercial potential, global conflicts, national strategies, and social issues. Media articles provide the most balanced coverage, while business and government discourses often overlook societal implications. We discuss the ramifications for integrating QT into society and the need for wellinformed public discourse.
Purpose This study aims to review and understand the state of records management practices in Malawi, focusing on both public and private sector organisations. Design/methodology/approach The hermeneutic framework underpinned a qualitative review of the study phenomenon. The inclusion and exclusion criterion for the literature was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology. Fifteen documents met the eligibility criteria and informed the study findings. The literature comprised of journal articles, dissertations at both master and doctoral levels, and conference papers. Findings The study found that records are created, captured and maintained both in print and electronic formats. It also confirmed that different types of organisations (public, private, academia and civil society) recognise the need for proper records management practices. However, effective and efficient records management is besieged by numerous obstacles, including lack of funding, absence of records management policy, standards and procedures at both institutional and national levels, poor records classification systems and a lack of top management support. Most importantly, the review shows that the majority of studies in Malawi have focused on academia, with little attention to other equally fundamental areas such as agriculture, trade, tourism, transport and energy. Thus, this situation calls for more empirical studies of records management practices in those sectors. Originality/value To the best of the authors’ knowledge, this is the first kind of review to be done at a national level, so the findings provide significant insights for policymakers and research practitioners on records management research trends to date in Malawi.
Актуальність теми, яка досліджується у даній роботі визначається процесом формуванням економіки знань на світовому рівні та трансформуванням функцій вищої освіти, яка отримує ознаки суспільного блага, продукування та розподіл якого визначається державою. Означена тенденція зумовлює посилення значущості державного фінансування сфери вищої освіти. В роботі проаналізовано роль держави у забезпеченні фінансування сфери вищої освіти, сучасні особливості та тенденції державного замовлення на підготовку фахівців, наукових та науково-педагогічних кадрів у закладах вищої освіти та наукових установах України за останні роки. Загальні результати, які були отримані в результаті дослідження, пов’язані з визначенням вирішальної ролі держави у фінансуванні вищої освіти, що виступає запорукою підвищення якості послуг цієї сфери. В умовах повоєнного відновлення нашої країни це стане базисом для реалізації інноваційної спрямованості розвитку України та можливості зайняти гідне місце у глобальному економічному просторі.
Economics as a science, Business records management
This paper investigates whether foreign investment (FDI) into Africa is at least partially responsive to World Bank-measured market friendliness. Specifically, I conducted analyses of four countries between 2009 and 2017, using cases that represent two of the highest scorers on the bank's Doing Business index as of 2008 (Mauritius and South Africa) and the two lowest scorers (DRC and CAR), and subsequently traced all four for growths or declines in FDI in relation to their scores in the index. The findings show that there is a moderate association between decreased costs of starting a business and growth of FDI. Mauritius, South Africa and the DRC reduced their total cost of starting a business by 71.7%, 143.7% and 122.9% for the entire period, and saw inward FDI increases of 167.6%, 79.8% and 152.21%, respectively. The CAR increased the cost of starting businesses but still saw increases in FDI. However, the country also saw the least amount of growth in FDI at only 13.3%.
Santosh Palaskar, Vijay Ekambaram, Arindam Jati
et al.
The efficiency of business processes relies on business key performance indicators (Biz-KPIs), that can be negatively impacted by IT failures. Business and IT Observability (BizITObs) data fuses both Biz-KPIs and IT event channels together as multivariate time series data. Forecasting Biz-KPIs in advance can enhance efficiency and revenue through proactive corrective measures. However, BizITObs data generally exhibit both useful and noisy inter-channel interactions between Biz-KPIs and IT events that need to be effectively decoupled. This leads to suboptimal forecasting performance when existing multivariate forecasting models are employed. To address this, we introduce AutoMixer, a time-series Foundation Model (FM) approach, grounded on the novel technique of channel-compressed pretrain and finetune workflows. AutoMixer leverages an AutoEncoder for channel-compressed pretraining and integrates it with the advanced TSMixer model for multivariate time series forecasting. This fusion greatly enhances the potency of TSMixer for accurate forecasts and also generalizes well across several downstream tasks. Through detailed experiments and dashboard analytics, we show AutoMixer's capability to consistently improve the Biz-KPI's forecasting accuracy (by 11-15\%) which directly translates to actionable business insights.
Table answering questions from business documents has many challenges that require understanding tabular structures, cross-document referencing, and additional numeric computations beyond simple search queries. This paper introduces a novel pipeline, named TabIQA, to answer questions about business document images. TabIQA combines state-of-the-art deep learning techniques 1) to extract table content and structural information from images and 2) to answer various questions related to numerical data, text-based information, and complex queries from structured tables. The evaluation results on VQAonBD 2023 dataset demonstrate the effectiveness of TabIQA in achieving promising performance in answering table-related questions. The TabIQA repository is available at https://github.com/phucty/itabqa.
Microservices architecture has been widely adopted to develop software systems, but some of its trade-offs are often ignored. In particular, the introduction of eventual consistency has a huge impact on the complexity of the application business logic design. Recent proposals to use transactional causal consistency in serverless computing seems promising, because it reduces the number of possible concurrent execution anomalies that can occur due to the lack of isolation. We propose an extension of the aggregate concept, the basic building block of microservices design, that is transactional causal consistent compliant. A simulator for the enriched aggregates is developed to allow the experimentation of this approach with a business logic rich system. The experiment results shown a reduction of the implementation complexity. The simulator is a publicly available reusable artifact that can be used in other experiments.
Zhang, Qing, Abdullah, Abdul Rashid, Hossan, Dalowar
et al.
The current study examined the effect of the style of transformational leadership on innovative work behavior as well as the internal locus of control’s moderating role and psychological empowerment between the relationships of them. We collected data from 422 respondents who are related to family business in Malaysia. Path coefficient analysis was employed to test the hypotheses and SPSS software was used for analyzing descriptive data. The results showed that transformational leadership style, psychological empowerment and internal locus of control have affirmative relationship and significant impact on innovative work behavior. Finally, psychological empowerment and internal locus of control were not found to have moderating effect between innovative work behavior and the style of transformational leadership.
Abstrak
Penelitian ini bertujuan untuk mengetahui bagaimana pengaruh komitmen organisasi dan kompetensi terhadap kinerja pegawai Sekretariat Daerah Kabupaten Pasuruan. Responden dalam penelitian berjumlah 150 pegawai baik ASN maupun non ASN dengan menggunakan explanatory research, yaitu penelitian yang diperlihatkan untuk menjelaskan hubungan kausal antara variabel penelitian dan menguji hipotesis yang dirumuskan. Berdasarkan total nilai persentase jawaban dari responden ASN, diketahui bahwa komitmen organisasi dan kompetensi pegawai berpengaruh terhadap kinerja pegawai ASN. Hal ini menunjukkan bahwa ASN di dalam lingkungan Sekretariat Daerah Pemkab Pasuruan memiliki loyalitas dan keinginan kuat dalam membawa organisasi mencapai tujuannya.Berdasarkan total nilai persentase jawaban dari responden non ASN, diketahui bahwa kompetensi pegawai yang lebih berpengaruh terhadap kinerja pegawai. Hal ini menunjukkan bahwa kemampuan kinerja non ASN diawasi sesuai kinerjanya, sehingga non ASN terus berusaha menunjukkan kinerja yang baik dan optimal. Hasil penelitian menunjukkan bahwa terdapat perbedaan komitmen organisasi dan Kompetensi Pegawai pada ASN dan Non ASN di Sekretariat Daerah Pemkab Pasuruan. Pada penelitian ini Kompetensi Pegawai Non ASN menunjukkan lebih tinggi daripada komitmen organisasi. Penelitian ini selanjutnya dapat menjadi bahan rujukan untuk masing-masing kepala instansi guna meningkatkan komitmen organisasi pegawai di masa depan, terutama untuk non ASN.
Kata kunci : Kompetensi dan komitmen organisasi, kinerja pegawai, ASN dan non ASN
Abstract
This study aims to determine how the influence of organizational commitment and competence on the performance of the employees of the Pasuruan Regency Regional Secretariat. Respondents in the study amounted to 150 employees both ASN and non ASN using explanatory research, namely research that is shown to explain the causal relationship between research variables and test the formulated hypotheses. Based on the total percentage value of answers from ASN respondents, it is known that organizational commitment and employee competence affect the performance of ASN employees. This shows that ASN within the Regional Secretariat of the Pasuruan Regency Government has a strong loyalty and desire to bring the organization to achieve its goals. Based on the total percentage value of answers from non ASN respondents, it is known that employee competence is more influential on employee performance. This shows that the performance ability of non ASNs is monitored according to their performance, so that non ASNs keep trying to show good and optimal performance. The results showed that there were differences in organizational commitment and employee competencies in ASN and non ASN at the Pasuruan Regional Government Secretariat. In this study, the competence of non ASN employees shows higher than organizational commitment. This research can then become a reference material for each head of the agency in order to increase employee organizational commitment in the future, especially for non ASN.
Keywords: Competence and organizational commitment, employee performance, ASN and non ASN
Dominik Dellermann, Nikolaus Lipusch, Philipp Ebel
et al.
One of the most critical tasks for startups is to validate their business model. Therefore, entrepreneurs try to collect information such as feedback from other actors to assess the validity of their assumptions and make decisions. However, previous work on decisional guidance for business model validation provides no solution for the highly uncertain and complex context of earlystage startups. The purpose of this paper is, thus, to develop design principles for a Hybrid Intelligence decision support system (HI-DSS) that combines the complementary capabilities of human and machine intelligence. We follow a design science research approach to design a prototype artifact and a set of design principles. Our study provides prescriptive knowledge for HI-DSS and contributes to previous work on decision support for business models, the applications of complementary strengths of humans and machines for making decisions, and support systems for extremely uncertain decision-making problems.
Empowerment and experience help and support organizations in enhancing their profitability, productivity and performance. This research aimed to examine the impact of empowerment and minimum experiences on the organizational performance. Structural Equation Modeling (SEM) was applied for analysis purpose. 237 questionnaires were collected from the Saudi workers who participated in the research. The research recommended that organizations must start encouraging their managers to implement more participative leadership styles such as providing subordinates with greater opportunities to get involved in decision-making and to adapt their ideas.
BPMN is a specification language widely used by industry and researchers for business process modeling and execution. It defines clearly how to articulate its concepts, but do not provide mechanism to represent the semantics of the produced models. This paper addresses the problem of how to improve the expressiveness of BPMN models, proposing a definition for the semantics of a business process within a BPMN model, and improving the completeness of the models in a systematic manner, so that models can describe far more situations with few extra managed complexity. We conceive a framework based on the business transaction patterns available in the enterprise ontology body of knowledge to prescribe the foundations of semantic BPMN models. A tool has been developed to automate the framework. Then, two industrial proof-of-concepts are used to measure its coverage, both positive and negative, and to argue about our proposal's usefulness. After that, the proposal is compared with others using a systematic literature review. A full BPMN pattern is proposed encompassing the happy flow, the declinations, the rejections and the revocations, without adding any new element to the BPMN specification. A software tool has been developed, and made publicly available, to support the automatic generation of the BPMN models from the proposed patterns. Our semantified BPMN pattern allowed the identification of a large amount of implicit, and other not implemented, situations in both proof-of-concepts. It is concluded that the usage of a semantic solution, grounded on a sound pattern, allows the systematic enrichment of the BPMN models with a bounded effort. Moreover, to simplify the BPMN executable models' implementation, its elements could be classified as implicit, explicit, or not implemented yet. Finally, related work indicates that this work is demanded, but no full solutions are available.
Faustino Prieto, José María Sarabia, Enrique Calderín-Ojeda
In this paper, we analyzed how business age and mortality are related during the first years of life, and tested the different hypotheses proposed in the literature. For that, we used data on U.S. business establishments, with 1-year resolution in the range of age of 0-5 years, in the period 1977-2016, published by the United States Census Bureau. First, we explored the adaptation of classical techniques of survival analysis (the Life Table and Peto-Turnbull methods) to the business survival analysis. Then, we considered nine parametric probabilistic models, most of them well-known in reliability analysis and in the actuarial literature, with different shapes of the hazard function, that we fitted by maximum likelihood method and compared with the Akaike information criterion. Our findings show that newborn firms seem to have a decreasing failure rate with the age during the first five years in market, with the exception of the first months of some years in which the risk can rise.
Paul A. Smith, Chiara Bocci, Nikos Tzavidis
et al.
Small area (or small domain) estimation is still rarely applied in business statistics, because of challenges arising from the skewness and variability of variables such as turnover. We examine a range of small area estimation methods as the basis for estimating the activity of industries within the retail sector in the Netherlands. We use tax register data and a sampling procedure which replicates the sampling for the retail sector of Statistics Netherlands' Structural Business Survey as a basis for investigating the properties of small area estimators. In particular, we consider the use of the EBLUP under a random effects model and variations of the EBLUP derived under (a) a random effects model that includes a complex specification for the level 1 variance and (b) a random effects model that is fitted by using the survey weights. Although accounting for the survey weights in estimation is important, the impact of influential data points remains the main challenge in this case. The paper further explores the use of outlier robust estimators in business surveys, in particular a robust version of the EBLUP, M-regression based synthetic estimators, and M-quantile small area estimators. The latter family of small area estimators includes robust projective (without and with survey weights) and robust predictive versions. M-quantile methods have the lowest empirical mean squared error and are substantially better than direct estimators, though there is an open question about how to choose the tuning constant for bias adjustment in practice. The paper makes a further contribution by exploring a doubly robust approach comprising the use of survey weights in conjunction with outlier robust methods in small area estimation.