Benefits For Companies Research Articles

Digital Transformation Development Strategies to Improve Sustainable Performance

This article examines the intersection of virtual transformation and sustainable overall performance, highlighting strategies corporations can implement to enhance their operational effectiveness while selling sustainability. It begins with a complete know-how of digital transformation, defining its key additives and the technological improvements riding this change. The significance of sustainable performance is mentioned, emphasizing its growing relevance in these days’s commercial enterprise landscape, wherein stakeholders an increasing number of call for environmentally and socially accountable practices. The article explores how integrating digital transformation initiatives with sustainability dreams can lead to synergistic advantages, growing an aggressive benefit for companies. Implementation techniques for virtual transformation are mentioned, focusing on frameworks that facilitate the adoption of innovative technologies at the same time as ensuring alignment with sustainable overall performance targets. Case research and exemplary practices from various industries illustrate successful digital transformation efforts that have undoubtedly impacted sustainability outcomes. In conclusion, the item offers insights into destiny guidelines for studies and practice, urging groups to embrace virtual transformation no longer merely as a technological improvement but as a holistic technique to attaining long-term sustainability. By exploring these issues, this examines objectives to provide a valuable aid for practitioners and researchers looking to navigate the complexities of digital transformation within the context of sustainable overall performance. Keywords : Digital Transformation, Sustainable Performance, Development Strategies

THE DIGITAL GATEAWAY TO EMPLOYMENT: INSIGHTS INTO ONLINE JOB PORTAL USAGE

Abstract – The feelings of WEB users have a great benefits for students , colleges and companies. It is necessary to structure well the unstructured data from various placement platforms for proper and meaningful analyses. For the classification of multilingual data, the analysis of feelings has recognized significant information od student and companies. This is called the Job Portal that may be used to maintain the visible connection between company and colleges and companies and student through the mediator Admin. To solve the problem of old job portal this introduced that it has minimum manual work for minimum error and other problems. These architectures may be used Java based languages. In this research variuos data, we had started this project to give more and opportunities for student placement. Key Words: project, job, management, system, application, online software, deployment, security.

Oil Economy and Society of Nigeria’s Niger Delta Region, 1956-2019

This paper studies the oil economy with a particular focus on the Nigeria’s Niger Delta Region. It argues that since the discovery and exploration of oil in commercial quantities in the Region, it has become both a blessing and a curse. It is a blessing because it has provided wealth to the people and government of the region. Some indigenes of the Nigeria Delta are owners of the oil wells others are employed to work with the oil multi-national companies like Chevron, Texaco, Shell Petroleum Development Company, Agip Oil Company, et cetera. The exploration of oil in the area under review is also a curse because it has negatively affected plants and animals (that is the destruction of flora and fauna); it has destroyed the ecosystem of the area. Using survey and documentary methods of data collection; the paper reveals that despite the discovery and exploration of oil in the said region, Nigeria’s Delta Region has remained one of the underdeveloped regions of the country. This is to say that the impact of the oil industry on the economy and society of the people is marginally felt. Based on the foregoing, these policy options are made. The government should give immediate attention to the indigenes of the region where crude oil is being extracted from. This will reduce the unrest in that region. The government should establish an institution that will ensure that the multinational oil companies are socially responsible to their host communities. Environmental pollution and the adverse effects on the host communities of oil exploration sites in the Niger Delta is an important issue that requires urgent and prompt attention because petroleum production forms the major natural-based resources on which the country depends. Therefore, Policymakers of the various oil exploration companies should realize that there is a need to protect the health, safety, and welfare of these communities. The communities and the inhabitants have to be well protected and some of the health and safety measures, which members of the company staff benefit, should be extended to members of the host communities to improve their standard of living.

Who are the early adopters of alternative fuel technology? A study of Swedish road freight companies

This study investigates the effect of three key firm characteristics (diversification, size, and age) on road freight companies’ early adoption of alternative fuel vehicles (AFVs). While previous studies have identified the determinants of the adoption intention of AFVs, a gap in the literature is research into firm characteristics and the early adopters of AFVs. Because early adopters play an important role in the diffusion of innovation, it is imperative to fill this gap. Based on a survey of 156 Swedish road freight companies and logistic regression analyses, we report that firm size and diversification affect the early adoption of AFVs. In addition, the partial impact of the importance of driver comfort and payload capacity on early adoption of AFVs has been reported. Other factors, including purchase price, fuel cost, and truck refueling efficiency, were not found to discriminate early adopters of AFVs from those who had not yet adopted AFVs. These findings imply to policymakers that the current instruments in use in Sweden, including the greenhouse gas mandate and the relatively high taxation on diesel fuel, have led to the adoption of AFVs by larger road freight companies. For vehicle producers aiming to scale up the production and sales of AFV, the findings suggest the benefit of targeting diversified and larger road freight companies in the first place.

Chemotherapy Care Companion: Enhancing cancer care through digital remote monitoring.

1636 Background: Oncology patients often encounter preventable acute issues prompting the need for proactive monitoring and management. To manage disease and therapy complications, Ochsner Health developed Chemotherapy Care Companion (CCC) for remote monitoring of treatment patients. This abstract highlights the feasibility of digital remote monitoring (DRM) in managing oncologic patient care, while increasing patient satisfaction and reducing patient events and healthcare costs. Methods: Starting in January 2021, patients initiating an oral or intravenous cancer treatment with an active Ochsner portal account and smartphone became eligible. Providers can manually enroll patients via an order set and receive enrollment reminders within the Epic electronic medical record (EMR). Patients receive a digital WiFi-enabled monitoring scale, blood pressure cuff, and ear thermometer, at no cost. Patients are reminded via phone alerts to take vitals at 9am and 3pm, along with a daily questionnaire. The data is transmitted wirelessly to the EMR, where abnormal vital signs or questionnaire responses trigger escalations sent to an Epic in-basket pool. During clinic hours, advanced practice providers (APPs) review and intervene, utilizing embedded urgent care slots for same-day access. In August 2022, a patient satisfaction survey comprising of nine questions was distributed to all enrolled patients. Results: A retrospective analysis was conducted from September 2022 to August 2023 including 722 participants, 7,360 escalations and 668 interventions. Patient compliance reached 62%, defined as submitting at least 50% of daily vitals. The most common interventions were related to hypertension, hypotension, weight changes, and questionnaire responses. Regarding questionnaire responses, diarrhea, pain, fever, and dizziness were the mostly frequently triaged. Data analytics revealed that CCC led to a 5.9% decrease in emergency room visits, a 41.7% decrease in the rate of inpatient hospital admissions, and a 32.3% improvement in the inpatient length of stay compared to non-enrolled patients. Extrapolating this data across 5,500 oncology patients within our hospital system, CCC could prevent 172 ER visits, 914 inpatient hospital admissions and 2,006 hospital days. The survey (131 responses) revealed high satisfaction with CCC: over 80% felt a sense of security, 90% were overall satisfied, and more than 90% would recommend CCC. Conclusions: Findings highlight the value of integrating DRM in cancer care, showcasing its ability to reduce healthcare costs and optimize resource utilization while enhancing patient care and satisfaction. Moreover, the study underscores the high patient satisfaction and engagement with DRM, bolstering its feasibility and acceptance in oncology care. Further investigation is warranted to explore the financial benefits for hospitals, insurance companies, and pharmaceutical companies.

DIGITAL RECRUITMENT REVOLUTION: EVALUATING THE EFFECTIVENESS OF ONLINE JOB PORTALS

Abstract – The feelings of WEB users have a great benefits for students , colleges and companies. It is necessary to structure well the unstructured data from various placement platforms for proper and meaningful analyses. For the classification of multilingual data, the analysis of feelings has recognized significant information od student and companies. This is called the Job Portal that may be used to maintain the visible connection between company and colleges and companies and student through the mediator Admin. To solve the problem of old job portal this introduced that it has minimum manual work for minimum error and other problems. These architectures may be used Java based languages. In this research variuos data, we had started this project to give more and opportunities for student placement. Key Words: project, job, management, system, application, online software, deployment, security.

Analysis of Domestic Component Level (TKDN) and Company Benefit Weight (BMP) in Construction Projects

In the world of construction projects, good project management is required, including the use of domestic products. The government encourages the use of domestic products through the program to increase the use of domestic production (P3DN). The amount of domestic content in commodities, services, and the combination of products and services can be used to measure the use of domestic products. This quantity is called the Domestic Component Level (TKDN). Company Benefit Weight (BMP) is an award given to industrial companies that invest and produce in Indonesia. This research aims to calculate the amount of TKDN and BMP for the Muhammadiyah Ahmad Dahlan Kediri Hospital construction project. With reference to the Ministry of Industry of the Republic of Indonesia's Regulation No. 16 of 2011 regarding Provisions and Procedures for Calculating Domestic Component Levels, the research employs a descriptive quantitative methodology to compute and analyze Domestic Content Levels (TKDN). The results of analytical calculations show that the TKDN percentage is 69.65% and the BMP percentage is 3%. This research concluded that the total TKDN and BMP was 72.65%, thus meeting the minimum limit for the sum of TKDN and BMP of 40%.

Valorization of Spent Mushroom Substrate: Establishing the Foundation for Waste-Free Production

Spent mushroom substrate (SMS), often disregarded as waste despite its abundance in organic matter and mineral micronutrients, has emerged as a valuable resource for diverse applications. While Europe and Asia have witnessed extensive research in this field over the past decade, Ukraine’s exploration remains limited. This study conducts a thorough investigation into SMS recycling and reutilization over a 4-year period. Employing experimental and comparative methods, this research unveils compelling insights into the potential of SMS for reintroduction into the primary production cycle and secondary activities. The main conclusions reveal the success of SMS valorization in the production of additives, fertilizers, and alternative fuels. Furthermore, the application of SMS in agroecosystems significantly enhances the soil biological activity. The integration of these methods into production chains not only yields economic benefits for companies but also fosters environmental stewardship, aligning with waste-free practices and the principles of bioeconomy and sustainability.

Social Media Analysis: Utilizing Information Technology for Market Intelligence and Branding of Toraja Coffe Products

This research discusses the utilization of social media analytics (AMS) to strengthen brand image and gather market information, specifically in the context of Toraja Coffee products. The aim is to understand consumer needs, improve brand image, and support coffee MSMEs in the Salubarani area, Tana Toraja, South Sulawesi. Through this AMS, it is expected that coffee MSMEs can improve their market knowledge, brand image, and contribution to the local economy. This research was conducted in Salubarani Village, located in Gandangbatu Sillanan District, Tana Toraja Regency, South Sulawesi. This research relies on two types of data, namely primary data and secondary data. The use of purposive sampling technique helped in the selection of informants who met the predetermined criteria. The data collection methods applied in this research include observation, interview, and documentation. The results confirmed that social media analysis is crucial in designing marketing strategies and improving the brand image of Toraja coffee. By understanding consumer preferences through social media platforms, companies can evaluate campaign effectiveness, identify market opportunities, and strengthen brand image. Findings also show that social media plays a crucial role in influencing purchasing decisions and strengthening customer loyalty. In the context of Toraja coffee, social media analytics is a critical success factor in marketing and brandingThe use of Social Media Analytics (AMS) provides great benefits for companies in gaining market intelligence and strengthening brand image. AMS enables customization of marketing strategies, competitor mapping, and identification of hidden opportunities. However, effective use requires a robust IT infrastructure and a well-trained team. Privacy and security challenges must also be addressed. In the context of Kopi Toraja, AMS can help MSMEs strengthen brand image

Energy Sector Evolution: Perspectives on Energy Platforms and Energy Transition

Digital platforms are becoming more important in transforming the energy industry and altering the way we produce, distribute, and use energy. This paper explores the role of energy platforms in the transition towards renewable energy. We highlight, through real-life examples, that these platforms foster a participatory approach, convert consumers into proactive participants, democratize energy production, and encourage innovation in areas such as storage, electric mobility, and renewable project investments. Through a comprehensive review of the current literature, technological advancements, and emerging business models, we identify the possible key contributions of digital platforms to the energy sector. These platforms offer personalized user experiences, mutual benefits for users and companies, adaptability to market changes, support for peer-to-peer trade, and a reduction in bureaucracy. We then present a pioneering conceptual model by Liu et al. (2022), which integrates the energy cloud, digital platform, and transaction platform and we explore the business model of energy platforms. This business model is characterized by connectivity, innovative pricing, and revenue strategies independent of physical asset ownership. Advanced technologies like artificial intelligence and blockchain facilitate peer-to-peer energy trading, dynamic pricing, and a focus on transaction and access fees over traditional cost structures. Drawing on the business model and previous analysis we update the conceptual model for energy platforms to present a practical vision through a holistic approach.

Brand Image Terhadap Customer Loyalty melalui Customer Satisfaction pada Pengguna Produk Tupperware di Kota Bandung

This research aims to evaluate the impact of brand image dimensions on customer loyalty through customer satisfaction regarding Tupperware brand food & beverage container products, especially in the city of Bandung. Data collection was carried out through interviews with respondents aged 17-40 years and who had experience using and purchasing Tupperware products. Participation in this research involved 90 respondents using cross-sectional data collection techniques or one shot study. Data analysis used a quantitative descriptive approach, normality test, multiple linear regression, and Sobel test with the help of statistical software program of social science (SPSS) version 26. Of the ten hypotheses proposed, eight of them were strengthened by empirical findings. These results indicate that customer satisfaction can act as a link between the impact of brand image dimensions (brand strength, brand uniqueness, and brand liking) and customer loyalty. In conclusion, this research can provide benefits for companies and management related to Tupperware products and similar food & beverage container industries in developing relevant strategies to improve the quality of these attributes. Keywords: Brand Image, Customer Satisfaction, Customer Loyalty

MCN portfolio: An efficient portfolio prediction and selection model using multiserial cascaded network with hybrid meta-heuristic optimization algorithm

ABSTRACT Generally, financial investments are necessary for portfolio management. However, the prediction of a portfolio becomes complicated in several processing techniques which may cause certain issues while predicting the portfolio. Moreover, the error analysis needs to be validated with efficient performance measures. To solve the problems of portfolio optimization, a new portfolio prediction framework is developed. Initially, a dataset is collected from the standard database which is accumulated with various companies’ portfolios. For forecasting the benefits of companies, a Multi-serial Cascaded Network (MCNet) is employed which constitutes of Autoencoder, 1D Convolutional Neural Network (1DCNN), and Recurrent Neural Network (RNN) is utilized. The prediction output for the different companies is stored using the developed MCNet model for further use. After predicting the benefits, the best company with the highest profit is selected by Integration of Artificial Rabbit and Hummingbird Algorithm (IARHA). The major contribution of our work is to increase the accuracy of prediction and to choose the optimal portfolio. The implementation is conducted in Python platform. The result analysis shows that the developed model achieves 0.89% and 0.56% regarding RMSE and MAE measures. Throughout the analysis, the experimentation of the developed model shows enriched performance.

ANALYSIS OF THE APPLICATION OF ENTITY FINANCIAL ACCOUNTING STANDARDS WITHOUT PUBLIC ACCOUNTABILITY ABOUT EMPLOYEE BENEFITS WITH THE IMPORTANCE PERFORMANCE ANALYSIS METHOD

This research aims to determine the application of SAK ETAP regarding employee benefits and the method for calculating SAK ETAP employee benefits in private companies in Jabodetabek as well as the impact of implementing the Job Creation Law on SAK ETAP calculating employee benefits using the Importance Performance Analysis method. The research methodology used in this research is descriptive quantitative. The population in this research are private companies in Jabodetabek. The sampling technique in this research used simple random sampling with a sample of 100 respondents. Analysis of this research data uses validity tests, reliability tests, and Importance Performance Analysis (IPA). The results of this research indicate that the implementation of SAK ETAP regarding employee benefits in private companies involves the process of recording, measuring and reporting employee benefits given to employees, the method for calculating SAK ETAP employee benefits in private companies is divided into 4 calculations, namely Short-Term Employee Benefits, Post-Employment Benefits, Other Long-Term Employee Benefits, and Severance Pay, as well as the impact of the implementation of the Job Creation Law on SAK ETAP for calculating Employee Benefits using the Importance Performance Analysis method. It can be concluded that company policies regarding employee benefits may change after the implementation of the Job Creation Law.

Transforming equipment management in oil and gas with AI-Driven predictive maintenance

The oil and gas industry faces significant challenges in managing equipment maintenance due to the complexity and criticality of its assets. Traditional maintenance approaches are often reactive and inefficient, leading to costly downtime and safety risks. However, the emergence of artificial intelligence (AI) and predictive maintenance technologies offers a transformative solution to these challenges. This paper explores the role of AI-driven predictive maintenance in revolutionizing equipment management in the oil and gas sector. AI-driven predictive maintenance leverages machine learning algorithms to analyze equipment data and predict when maintenance is required before a breakdown occurs. By monitoring equipment performance in real-time, AI can identify potential issues early, allowing operators to take proactive maintenance actions. This approach helps minimize downtime, reduce maintenance costs, and improve overall equipment reliability and safety. The implementation of AI-driven predictive maintenance requires a comprehensive strategy that includes data collection, analysis, and integration with existing maintenance practices. Successful adoption of AI-driven predictive maintenance can lead to significant benefits for oil and gas companies, including increased equipment uptime, extended asset lifespan, and enhanced operational efficiency. This paper reviews the current landscape of equipment management in the oil and gas industry, highlighting the limitations of traditional maintenance practices and the need for a more proactive approach. It then examines the principles and benefits of AI-driven predictive maintenance, showcasing real-world examples of its successful implementation. Finally, the paper discusses the challenges and considerations for implementing AI-driven predictive maintenance and provides recommendations for oil and gas companies looking to transform their equipment management practices. Keywords: Transforming Equipment; Management; Oil and Gas; AI-Driven; Predictive Maintenance.

Integrated Optimisation Model of Daily Freight Train Scheduling and Dynamic Railcar Routing Based on a Two-Layer Space-Time Network

This paper focuses on daily freight train scheduling and dynamic railcar routing problems for rail freight transportation at the operational level. Two mixed integer linear programming models that adopted different strategies were formulated based on a continuous two-layer time-space network. We simultaneously considered the benefits of railroad company and service quality when setting the objective function. By solving the models, we can distribute the dynamic railcar flows to the train paths in the basic train timetable to obtain the daily train operation plan over a short time horizon (e.g. a day), which will be helpful for dispatchers to make decisions such as the empty railcar distribution and car routing (trip planning). Finally, we compared two models on a part of the Chinese railroad network. The results show that the second model can effectively improve the efficiency of railroad freight transportation.

“It’s Complicated”: How Black and White Women Innovate with Situationships at Midlife

Abstract The sexual and romantic activities of unmarried women at midlife are often invisible in survey research based on normative categories of adult intimacy. However, women at this stage in the life course are structurally positioned to innovate with intimacy. In our interviews with 53 Black and white women between ages 33-58, outside of stable partnerships, and open to sex and intimacy with men, we find that women’s frustration with marriage and marriage-like commitment, negative experiences dating, and lack of interest in celibacy led them to experiment with a new form of intimacy. A majority engaged in ongoing liaisons in a liminal space between casual and committed—what emerging scholarship on the romantic relationships of Black women refer to as “situationships.” Black women, those with higher incomes, and queer-identified women were more likely to use situationships. We argue that women’s use of situationships challenged normative expectations that felt constraining to many at midlife and allowed women to enjoy the benefits of sexual and romantic company. Situationships enabled them to avoid casual sex and maintain autonomy and single identity. Finally, we highlight the disadvantages of situationships, emphasizing the importance of life stage and orientation to normative arrangements for situationship experiences.

512 Length of Stay Prediction Based on an Artificial Neural Network

Abstract Introduction Hospital length of stay (LOS) is difficult to predict in patients with burn injuries due to the complexity of the injuries and the wide variability in patient outcomes. Predicting hospital LOS in patients with burn injuries can have numerous benefits for patients, physicians, and insurance companies. Artificial neural networks may offer insight into more accurate LOS predictions. Methods We obtained electronic health records (EHR) for burn patients from July 01, 2011 - July 01, 2021. An artificial neural network was used to model the relationship between the input features and LOS. The input features were preprocessed by normalizing each feature to the range [0, 1] and transformed using log normal. The preprocessed data was split into training (70%), validation (15%), and testing (15%) sets. The neural network consisted of one hidden layer with 13 neurons and a linear output layer. Results The neural network achieved an R-squared (R2) value of 0.72 on the training data, indicating that 72% of the variance in the data (n=1347). The validation and testing R2 values were 0.66 and 0.68, respectively. The overall R2 value, computed by combining the predictions on the training, validation, and testing data, was 0.70. The best performance, validation performance, and testing performance achieved by the neural network during the training process were 0.28, 0.27, and 0.30, respectively. These values indicate the average squared difference between the predicted output and the true output for each set, with lower values indicating better performance. Conclusions The results suggest that the neural network can model the relationship between the input features and LOS with reasonable accuracy. The R2 values indicate that the model explains a substantial amount of the variability in the data. Further testing and validation may be needed to assess the robustness and reliability of the model. Applicability of Research to Practice Patient outcomes are largely variable and determining LOS to a closer degree helps planning more robust treatment plans. Additionally, these models have the potential to serve as a more accurate gauge of whether they are following closely to their expected treatment timeline. As survival rates continue to improve, the improvement focus has and will continue to shift towards patient outcomes.

ADVERTISING ON EARNED MEDIA IN SOCIAL MEDIA: SYSTEMATIC LITERATURE REVIEW

Earned media is a marketing strategy that gets results naturally without the need to spend money to attract users through paid advertising or branding of owned media. This research method uses Systematic Analysis (SLR) which is a specialized research method to collect and evaluate research relevant to a particular focus and topic. The purpose of SLR is to identify various perspectives related to the subject under study and determine the strategies that will be used to help overcome the problems that arise. Researchers use various library sources and their variations to obtain the necessary data or information. By utilizing existing reference sources, writing this scientific article can be done smoothly. Data collection is done by documenting all articles that have similar research to the research report. There are 10 articles from reputable journals used in this research. Thus, this research not only provides academic contributions in the field of marketing, but also provides practical benefits for companies that want to utilize earned media as part of their marketing strategy.

Does internal audit matter? Audit committee, its attributes, and corporate social responsibility reporting quality

This study explores the nexus between internal audit, audit committee attributes, and Corporate Social Responsibility (CSR) disclosure quality in A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2010 to 2019. Utilizing refined samples and robust datasets, this investigation reveals critical insights that a robust internal control system significantly correlates with higher-quality CSR disclosure, underscoring its pivotal role in safeguarding non-financial reporting integrity and enhancing transparency in CSR disclosures. Larger audit committees are positively associated with improved CSR disclosure quality. This highlights the strategic advantage of a diverse and expansive audit committee in navigating the complexities of CSR reporting. Contrary to expectations, the proportion of independent directors on the audit committee and the frequency of audit committee meetings do not show a significant positive relationship with CSR disclosure. Companies benefit from strategic investments in internal control systems, crucial for non-financial reporting integrity and fortified CSR disclosure practices. In conclusion, this study provides concise insights into critical factors influencing CSR disclosure quality in Chinese companies, offering actionable implications for corporate practices and regulatory frameworks. AcknowledgmentThis paper is co-funded by the European Union through the European Education and Culture Executive Agency (EACEA) within the project “EU BEST PRACTICE OF LIFE CYCLE ASSESSMENT, SOCIAL, ENVIRONMENTAL ACCOUNTING AND SUSTAINABILITY REPORTING” – 101047667-ERASMUS-JMO-2021-MODULE https://jm.snau.edu.ua/en/eu-best-practice-of-life-cycle-assessment-social-envi­ron­mental-accounting-and-sustainability-reporting/ Oleh Pasko expresses sincere gratitude for the support from the Kirkland Research Program, generously provided by the Leaders of Change Foundation established by the Polish-American Freedom Foundation.

Meningkatkan Kinerja Karyawan Melalui Green Human Resource Management: Peran Mediasi Green OCB Dan Green Behavior

Research aim: This study explores how Green HRM and Green OCB mediate organizational performance at Blue Pearl Company in Singapore Methods: This study uses quantitative methods. Data analysis uses Partial Least Square (PLS) with Smart-PLS3 software. Finding: The study confirmed that Green Human Resource Management (GHRM) significantly influences green behavior and organizational citizenship behaviors (OCB) related to sustainability, which in turn positively impacts employee performance. Specifically, GHRM indirectly enhances performance through both green behavior and green OCB. However, it was found that GHRM does not directly lead to an improvement in employee performance Theoretical contribution/Originality: These results contribute theoretically by providing empirical evidence of the influence of GHRM on improving employee performance through mediation played by green behavior and green OCB Practitioner implication: This research contributes as encouragement for companies operating in the manufacturing sector to implement GHRM as a way to improve individual employee performance Research limitation: The review of sustainability values in the future needs to be reviewed because concern for environmental sustainability in green parks will provide benefits for companies in increasing their sustainability values