Penelitian ini bertujuan untuk menganalisis pengaruh content marketing dan adopsi e-commerce terhadap kinerja pemasaran usaha mikro, kecil, dan menengah (UMKM) dengan digital customer engagement sebagai variabel mediasi menggunakan pendekatan PLS-SEM. Data dikumpulkan melalui survei terhadap 160 pelaku UMKM di Blitar dan dianalisis menggunakan SmartPLS 4. Hasil penelitian menunjukkan bahwa content marketing dan adopsi e-commerce berpengaruh positif dan signifikan terhadap digital customer engagement, namun keduanya tidak berpengaruh secara langsung terhadap kinerja pemasaran. Digital customer engagement terbukti memiliki pengaruh yang kuat terhadap kinerja pemasaran serta memediasi secara penuh hubungan antara content marketing, adopsi e-commerce, dan kinerja pemasaran. Temuan ini menegaskan bahwa keberhasilan pemasaran digital UMKM di era digital sangat bergantung pada kemampuan pelaku usaha dalam membangun dan mendorong keterlibatan pelanggan secara berkelanjutan guna meningkatkan daya saing bisnis dan keberlanjutan usaha dalam lingkungan ekonomi digital yang kompetitif.
Economics as a science, Management of special enterprises
Marco Tonnarelli, Filippo Scaramuzza, Simon Harrer
et al.
Computational data governance aims to make the enforcement of governance policies and legal obligations more efficient and reliable. Recent advances in natural language processing and agentic AI offer ways to improve how organizations share and use data. But many barriers remain. Today's tools require technical skills and multiple roles to discover, request, and query data. Automating data access using enterprise AI agents is limited by the means to discover and autonomously access distributed data. Current solutions either compromise governance or break agentic workflows through manual approvals. To close this gap, we introduce Data Product MCP integrated in a data product marketplace. This data marketplace, already in use at large enterprises, enables AI agents to find, request, and query enterprise data products while enforcing data contracts in real time without lowering governance standards. The system is built on the Model Context Protocol (MCP) and links the AI-driven marketplace with cloud platforms such as Snowflake, Databricks, and Google Cloud Platform. It supports semantic discovery of data products based on business context, automates access control by validating generated queries against approved business purposes using AI-driven checks, and enforces contracts in real time by blocking unauthorized queries before they run. We assessed the system with feedback from $n=16$ experts in data governance. Our qualitative evaluation demonstrates effectiveness through enterprise scenarios such as customer analytics. The findings suggest that Data Product MCP reduces the technical burden for data analysis without weakening governance, filling a key gap in enterprise AI adoption.
Asset Liability Management (ALM) represents a fundamental challenge for financial institutions, particularly pension funds, which must navigate the tension between generating competitive investment returns and ensuring the solvency of long-term obligations. To address the limitations of traditional frameworks under uncertainty, this paper implements Distributionally Robust Optimization (DRO), an emergent paradigm that accounts for a broad spectrum of potential probability distributions. We propose and evaluate three distinct DRO formulations: mixture ambiguity sets with discrete scenarios, box ambiguity sets of discrete distribution functions, and Wasserstein metric ambiguity sets. Utilizing empirical data from the Canada Pension Plan (CPP), we conduct a comparative analysis of these models against traditional stochastic programming approaches. Our results demonstrate that DRO formulations, specifically those utilizing Wasserstein and box ambiguity sets, consistently outperform both mixture-based DRO and stochastic programming in terms of funding ratios and overall fund returns. These findings suggest that incorporating distributional robustness significantly enhances the resilience and performance of pension fund management strategies.
This paper develops a dynamic equilibrium model of the insurance market that jointly characterizes insurers' underwriting, investment, recapitalization, and dividend policies under model uncertainty and financial frictions. Competitive insurers maximize shareholder value under a subjective worst-case probability measure, giving rise to liquidity-driven underwriting cycles and flight-to-quality behavior. While an equilibrium typically fails to exist in such dynamic liquidity management framework with external financial investment, we show that incorporating model uncertainty restores equilibrium existence under plausible parameter conditions. Moreover, the model uncovers a novel relationship between the correlation of insurance and financial market risks and the equilibrium insurance price: negative loadings may emerge when insurance gains and financial returns are positively correlated, contrary to conventional intuition.
Fatemeh Boomeh, Mohammad Hosein Mokhtari, Ali Talebi
et al.
Climate change, a phenomenon that has been occurring since ancient times, has accelerated in recent years. This study investigates the impact of climate change on groundwater resources using the MODFLOW model. To achieve this, the water balance was first calculated, and then temperature and precipitation data for the near future (2031–2050), mid-term (2051–2070), and long-term (2071–2090) periods were estimated using global climate data. These estimated temperature and precipitation values were input into the MODFLOW 2005 model. The results showed that, under two climate change scenarios—shared socioeconomic pathways (SSPs) SSP2-4.5 and SSP5-8.5—the monthly averages of both minimum and maximum temperatures are expected to increase across all months of the year. In the optimistic scenario (SSP2-4.5), precipitation and aquifer recharge are projected to remain at current levels on average; however, groundwater levels are anticipated to decline by approximately 22 meters by 2089, with annual and seasonal fluctuations persisting in the long term. In contrast, the pessimistic scenario (SSP5-8.5) predicts a significant reduction in both precipitation and aquifer recharge, leading to a more pronounced decrease in groundwater levels. In this scenario, groundwater levels are expected to drop by about 30 cm per year in the long term, largely due to changes in precipitation patterns and aquifer recharge rates.
This paper explores the applications of the 20/60/20 rule-a heuristic method that segments data into top-performing, average-performing, and underperforming groups-in mathematical finance. We review the statistical foundations of this rule and demonstrate its usefulness in risk management and portfolio optimization. Our study highlights three key applications. First, we apply the rule to stock market data, showing that it enables effective population clustering. Second, we introduce a novel, easy-to-implement method for extracting heavy-tail characteristics in risk management. Third, we integrate spatial reasoning based on the 20/60/20 rule into portfolio optimization, enhancing robustness and improving performance. To support our findings, we develop a new measure for quantifying tail heaviness and employ conditional statistics to reconstruct the unconditional distribution from the core data segment. This reconstructed distribution is tested on real financial data to evaluate whether the 20/60/20 segmentation effectively balances capturing extreme risks with maintaining the stability of central returns. Our results offer insights into financial data behavior under heavy-tailed conditions and demonstrate the potential of the 20/60/20 rule as a complementary tool for decision-making in finance.
This article tries to examine the financial performance of the informal enterprises in the clusters and factors determining their financial performance. It is based on primary data collected through a customised sample survey in four districts of Assam, namely Dhubri, Nalbari, Lakhimpur and Majuli. Three indicators of financial performance of the enterprises were taken, namely gross value added, income accruing to the entrepreneur’s household from the enterprise and profit. It was found that the financial performance of the sample enterprises was not satisfactory. Most of the enterprises were providing subsistence income to the entrepreneurs. Although only a few of the enterprises were earning profit, those were providing employment opportunities to the owners and their family members. In other words, the enterprises were the sources of their livelihood. Further, the financial performance of the enterprises was not linked to their access to credit and level of education. As these enterprises were the sources of livelihood of the sample entrepreneurs, policies should be there for providing social security to those entrepreneurs’ households.
Akash V. Maharaj, Kun Qian, Uttaran Bhattacharya
et al.
The development of conversational AI assistants is an iterative process with multiple components. As such, the evaluation and continual improvement of these assistants is a complex and multifaceted problem. This paper introduces the challenges in evaluating and improving a generative AI assistant for enterprises, which is under active development, and how we address these challenges. We also share preliminary results and discuss lessons learned.
Neighborhood characteristics have been broadly studied with different firm behaviors, e.g. birth, entry, expansion, and survival, except for firm exit. Using a novel dataset of foreign-invested enterprises operating in Shenzhen's electronics manufacturing industry from 2017 to 2021, I investigate the spillover effects of firm exits on other firms in the vicinity, from both the industry group and the industry class level. Significant neighborhood effects are identified for the industry group level, but not the industry class level.
Smaraki Pattanayak, Biswajeet Pattanayak, Phalgu Niranjana
et al.
MSMEs are micro, small and medium enterprises which are contributing significantly to India’s total GDP. In fact, it is the growth engine of Indian economy which generates highest employments. This study attempts (a) to understand the importance of psychological contract (PC) in small and medium enterprises (SMEs), (b) to assess the extent to which organisational culture dimensions and happiness contribute in determining PC in SMEs. Three standardised questionnaires namely Organisational Culture: OCTAPACE Profile, Psychological Contract Scale and The Oxford Happiness Scale have been used to collect the data. Four hundred samples have been drawn from different SMEs. The statistics used is multiple regression analysis to analyse the data and interpret the results. The study has thrown many interesting results. The present research findings show that PC is the function of happiness and organisational culture dimensions. It is found that the dimensions of culture namely trust, collaboration and pro-action have come out to be the most promising influencers to PC along with happiness. Numerous studies have identified a strong linkage between PCs, organisational performance and productivity. Based on the findings organisation development (OD) and behavioural intervention strategies are suggested to enhance PC in SMEs.
IntroductionThe growth of plants is affected by environmental stresses, particularly drought and salinity, which are the main problems of arid and semi-arid lands. Germination is a crucial stage in the life of most plants. Plant establishment in arid and semi-arid regions requires special tolerance to stresses like salinity and drought during the germination stage. In most plants, increasing salinity and drought stress during the germination stage prevents the plant from germinate. Therefore, knowing the resistance to salinity and drought in different plants can be used in the management of natural environments. Considering the increase in global temperature and the decrease in rainfall in Iran, as well as the soil salinization, it is very important to choose plants with high tolerance to salinity and drought in rangeland. In the southern rangeland of Kohgiluyeh Va Boyer Ahmad province, which are located in arid and semi-arid climates, non-native species such as Atriplex spp. and Prosopis spp. have been used for improvement and restoration in the past decades. The soil and native vegetation of the region are negatively impacted by non-native plants, which have problems like lack of natural regeneration. Identifying suitable native plants that can grow in specific ecological conditions of arid and semi-arid areas, such as drought and salinity, is necessary. The current research aims to identify native resistant species to the mentioned stresses for vegetation restoration in biological and bio-mechanical projects. Material and MethodsIn order to identify the species tolerant to environmental stress in the rangeland of Kohgiluyeh Va Boyer Ahmad province, three native species including Zygophyllum eurypterum Boiss. & Buhse, Sanguisorba minor L. and Salsola orientalis S. G. Gmelin (Salsola rigida) were selected. The habitats of the species were identified through field surveys and the cooperation of experts from the General Department of Natural Resources and Watershed Management of Kohgiluyeh Va Boyer Ahmad province. Sampling of plant seeds for experiments was done in range habitats. Seed germination reaction of three species Z. eurypterum, S. minor. and S. orientalis were studied in the laboratory with respect to different levels of salinity and drought stress. The drought stress test included six levels (0, -0.3, -0.6, -0.9, -1.2, and -1.5 MP) which were prepared using polyethylene glycol 6000. The second experiment included 6 salinity levels (0, 50, 100, 150, 200, 250 mM). Sodium chloride was used to create salinity stress. Before conducting the salinity and drought tests, treatments were applied to break the seed dormancy of different species, and after identifying the best treatment for each species, dormancy tests were performed. Germination was done as a factorial experiment in a completely randomized design with 4 replications (20 seeds per replication) in a germinator at a temperature of 25°C. During a period of 20 days, every day the germinated seeds whose root length was more than 2 mm were counted and their germination percentage, germination rate, length of root, stem and seedling and their seed germination index were measured. Using SPSSVer.23 software, analysis of variance and comparison of average data was done. Results and DiscussionVariance analysis shows that there is a significant difference between drought and salinity levels in the traits measured in plants (p<0.01). There is a significant difference between plant species and drought-salinity interaction and species(p<0.01). With the increase of dryness, a significant difference was observed in terms of germination percentage in all three species. In this condition, the highest amount of measured traits including, germination percentage and seed germination index was observed in Z. eurypterum. with increasing salinity, the germination rate of all three species decreases significantly. In the condition without salt stress (control treatment), the highest percentage of germination (77%) was obtained in S. minor. But with increasing salinity levels, the highest germination percentage is observed in S. orientalis, and also with increasing salinity levels, the lowest germination percentage is related to S. minor species. Plants responded differently to environmental stresses, as shown by the results in general. The restoration and improvement of rangelands requires knowledge of plants that are resistant to existing stresses in order to manage natural areas. According to the current research, the rate of germination and growth of seedlings decreases as salinity and drought levels increase. Among the studied species, Z. eurypterum is the most resistant to drought and S. minor is the most sensitive. It can be concluded that the highest germination is observed in S. orientalis, when salinity levels increase, and the lowest germination is observed in S. minor species. Therefore, S. orientalis can be considered as a salt resistant. As the species studied are indigenous and native in the south of Kohgiluyeh Va Boyer Ahmad provinces, the results of this research are suggested for use in biological projects.
Portfolio optimization is a task that investors use to determine the best allocations for their investments, and fund managers implement computational models to help guide their decisions. While one of the most common portfolio optimization models in the industry is the Markowitz Model, practitioners recognize limitations in its framework that lead to suboptimal out-of-sample performance and unrealistic allocations. In this study, I refine the Markowitz Model by incorporating machine learning to improve portfolio performance. By using a hierarchical clustering-based approach, I am able to enhance portfolio performance on a risk-adjusted basis compared to the Markowitz Model, across various market factors.
Traditional risk-adjusted returns, such as the Treynor, Sharpe, Sortino, and Information ratios, have been pivotal in portfolio asset allocation, focusing on minimizing risk while maximizing profit. Nevertheless, these metrics often fail to account for the distinct characteristics of bull and bear markets, leading to sub-optimal investment decisions. This paper introduces a novel approach called the Market-adaptive Ratio, which was designed to adjust risk preferences dynamically in response to market conditions. By integrating the $ρ$ parameter, which differentiates between bull and bear markets, this new ratio enables a more adaptive portfolio management strategy. The $ρ$ parameter is derived from historical data and implemented within a reinforcement learning framework, allowing the method to learn and optimize portfolio allocations based on prevailing market trends. Empirical analysis showed that the Market-adaptive Ratio outperformed the Sharpe Ratio by providing more robust risk-adjusted returns tailored to the specific market environment. This advance enhances portfolio performance by aligning investment strategies with the inherent dynamics of bull and bear markets, optimizing risk and return outcomes.
Lauren Arthur, Jason Costello, Jonathan Hardy
et al.
Generative AI technologies are gaining unprecedented popularity, causing a mix of excitement and apprehension through their remarkable capabilities. In this paper, we study the challenges associated with deploying synthetic data, a subfield of Generative AI. Our focus centers on enterprise deployment, with an emphasis on privacy concerns caused by the vast amount of personal and highly sensitive data. We identify 40+ challenges and systematize them into five main groups -- i) generation, ii) infrastructure & architecture, iii) governance, iv) compliance & regulation, and v) adoption. Additionally, we discuss a strategic and systematic approach that enterprises can employ to effectively address the challenges and achieve their goals by establishing trust in the implemented solutions.
Purpose: the purpose of the article is to substantiate the ecosystem approach to managing the interaction of an enterprise with educational and other organizations to provide it with the necessary human capital.Methods: this article is based on an ecosystem approach. A resource approach was used to substantiate the advantages of the professional and educational ecosystem. The method of situational analysis is used. The questionnaire method made it possible to evaluate the results of the ecosystem of a particular enterprise based on the expert`s opinion. The assessment of the structural model of management of the professional and educational ecosystem was carried out using correlation analysis.Results: the possibilities of an ecosystem approach to the formation of new organizational forms of interaction between subjects of the real sector of the economy and the education system in a dynamically changing external environment are shown. The content of the vocational education ecosystem is revealed as a kind of socio-economic, the key features of which are the specific composition of subjects and a special goal (creation of joint value) – reproduction of the enterprise human capital. The key objects of management of the vocational education ecosystem are highlighted: resources, processes, results and interaction of participants. An algorithm for evaluating the management system of the vocational education ecosystem of the enterprise is presented. The experience of the vocational education ecosystem of a knowledge-intensive enterprise is analyzed and practical recommendations for its development are given.Conclusions and Relevance: the approach to the management of the vocational education ecosystem through the analysis of key objects considered in the article has practical significance and allows us to give concrete practical recommendations for its improvement. Based on the results of the analysis of the objects of management of the vocational education ecosystem of the machine-building enterprise, the need to strengthen the relationship of enterprises with educational organizations that form the basis of human capital has been established. The key advantage of the vocational education ecosystem of the enterprise is the unhindered accessibility for employees of the enterprise in advanced training, the implementation of the principle of lifelong learning.
Bahram Choubin, Farzaneh Sajedi Hosseini, Omid Rahmati
et al.
In addition to the increase in prone areas to wind erosion processes in western Azarbaijan province due to the drying of Lake Urmia, there is a growing concern regarding the intensification of dust storms. Considering the impacts of this phenomenon on the environment, public health, agriculture, and transportation sections, more detailed studies on its source, severity, and frequency is necessary. Therefore, this study was designed to assess the temporal and spatial changes of dust storm events using satellite data, to detect the dust source, and to analyze the factors affecting the occurrence of dust storms in western Azarbaijan province. Analysis of the number of dusty days using the MODIS-AOD product indicated that the years 2003, and 2008 to 2012 were the dust storm peaks during the period 2000-2020 at western Azarbaijan province. Most dust storm events have occurred in summer and spring seasons, and monthly changes indicate the maximum dust storm between March and October. Trend analysis indicated that there was no significant trend in AOD and dust storm events. Among vegetation and climate variables, there is a significant relationship between AOD and wind speed (i.e., the correlation is about 64%). Spatially, dust storms occur more frequently along the shores of Urmia Lake (mostly in the east and south and slightly in the west). Southern areas of the province reported a higher frequency of dust event than the central and northern parts of the province. Due to the direction of the prevailing wind, it seems to be most affected by dust storms coming from the neighboring country of Iraq, however, the areas around the Lake Urmia are the inner source of dust storms.
This study aims to determine the behavior of religiosity on the consumption behavior of cosmetic packaging products. The object of this research is the women community in Lili Riawang Village, Bengo District, South Sulawesi, Indonesia. The type of research used is field research using a quantitative approach method. The data collection technique used is descriptive statistical analysis. The results of this study indicate that the behavior of religiosity affects the consumption behavior of cosmetic packaging products in the female community in Lili Riawang Village, Bengo District, South Sulawesi Indonesia. R Square value of 70.3% indicates that the behavioral factor of religiosity is very influential on consumption behavior, while the remaining 29.7% is influenced by other factors.
Economics as a science, Management of special enterprises
Mohammadjavad Abbasi, Jilla Sajjadi, Ali Abdollahi
Abstract Introduction The existence of appropriate tourism facilities and services and the high quality of tourism infrastructure and services certainly affect the demand for tourist attractions. Therefore, Tarom township is located in the north of Zanjan province; In the land management plan of Zanjan province, it has been proposed as a "privileged regional tourism axis." However, with the construction and operation of a new road along the route of this tourism axis, Great changes have taken place in the establishment of transportation connections and the entry of tourists to this area. Therefore; this study aimed to investigate the role of strengthening transportation infrastructure(road construction) and its impact on the development of tourism activities in the study area. Also, Seek answers the following questions: - Is there a significant relationship between the construction of Zanjan-Tahm-Chavarzeq road and the sustainable development of tourism in the study area?- Which dimension and Component of tourism development have received the most impact from the construction of Zanjan-Taham-Chavarzeq road? Materials and Methods The present research is of an applied type. The statistical population of the present study is the tourist settlements of Shit-Walidar and Shirinsoo tourist areas in Tarom city. By purposive non-probability sampling method, 277 households were selected for sampling. The method of collecting field-library information and analyzing the data using inferential statistics such as the Wilcoxon test, T is a single sample in SPSS software. Representation and mapping of spatial flows of tourism in the study area have been done using UCINET software, and structural equation modeling (SEM) is in AMOS software. Discussion and Results The investment situation for launching tourism-related activities was 28.46%. The training courses' status in connection with tourism activities indicates that about 28% of the training courses were directly related to tourism activities, and 72% of the training were non-tourism related. Therefore, the flow of tourists entering the study area from the city of Zanjan is stronger, but the flow of Rasht and Khalkhal is weaker. Investigating the effects and consequences of the construction of Zanjan-Tahm-Chavarzeq road on tourism development indicators in the studied areas (local communities' point of view) with non-parametric Wilcoxon test; Shows that the construction of this road has the most significant difference in the components of improving job opportunities in tourism activities, respectively, Component of increasing the number of passengers and tourists, Component of reducing migration of local communities, Improving infrastructure. The road has had tourism facilities and services. Still, investment in tourism development has the least significant difference in the period before and after the construction of Zanjan-Tahm-Chavarzeq road. Also; To investigate the contribution of the effective factors of the consequences of the construction of Zanjan-Tahm-Chavarzeq road in the sustainable development of tourism from the perspective of local communities, structural modeling of second-order factor analysis was used. The development of tourism under the influence of 4 hidden factors (economic, socio-cultural, environmental, and physical) has been studied. It shows the effects of tourism development in the physical dimensions 97, Economic 96, Environment 94, and socio-cultural 79 percent. Conclusions The research findings show that before the construction of Zanjan-Tahm-Chavarzeq road, the study area was isolated in terms of communication and especially with the center of the province. Therefore, the construction and operation of the new Zanjan-Taham-Abbar road, while reducing the distance and time interval of access to Zanjan, has left numerous socio-economic effects on tourism development in the study area. Also, the main indicators of model fit show that the research data, Conceptual model of research in terms of the effectiveness of strengthening the transport infrastructure in tourism's sustainable development, has given a meaningful explanation. However, the transport network infrastructure position is still not suitable, and they have weaknesses and shortcomings.
Management. Industrial management, Management of special enterprises
In this paper, we investigate the optimal management of defined contribution (abbr. DC) pension plan under relative performance ratio and Value-at-Risk (abbr. VaR) constraint. Inflation risk is introduced in this paper and the financial market consists of cash, inflation-indexed zero coupon bond and a stock. The goal of the pension manager is to maximize the performance ratio of the real terminal wealth under VaR constraint. An auxiliary process is introduced to transform the original problem into a self-financing problem first. Combining linearization method, Lagrange dual method, martingale method and concavification method, we obtain the optimal terminal wealth under different cases. For convex penalty function, there are fourteen cases while for concave penalty function, there are six cases. Besides, when the penalty function and reward function are both power functions, the explicit forms of the optimal investment strategies are obtained. Numerical examples are shown in the end of this paper to illustrate the impacts of the performance ratio and VaR constraint.