Investment In Industry Research Articles

Investing in green, sustaining the planet: The role of fintech in promoting corporate green investment in the Chinese energy industry

In recent years, fintech has rapidly developed on a global scale, bringing about significant transformations across various industries. Particularly in the energy sector, the potential of fintech to promote corporate green investment has increasingly become a focus. As the energy industry accounts for a significant proportion of global greenhouse gas emissions, guiding companies in implementing green investment has become an important issue for environmental protection and sustainable development. However, previous studies have rarely systematically investigated the influence of fintech on corporate green investment in the energy industry and the mechanisms involved. Hence, this study aims to bridge this research gap within the context of China. By utilizing valid survey data from 466 corporations in the Chinese energy industry and the method of structural equation modeling, the results indicate that: (1) Fintech can promote corporate green investment in the energy industry. (2) Fintech can promote corporate data-driven decision-making capability, information transparency, and sustainable development strategy. (3) Data-driven decision-making capability, information transparency, and sustainable development strategy can also promote corporate green investment in the energy industry. (4) Mediation analysis reveals that data-driven decision-making capability, information transparency, and sustainable development strategy each play a mediating role in the impact of fintech on corporate green investment. (5) Comparative analysis of the mediation effects indicates that there is a certain degree of difference among these three variables’ mediating effects, but it did not reach a statistically significant level. This study provides rich insights for business practices, encouraging companies to strengthen their focus on green investment in the fintech era and offer guidance and recommendations to relevant stakeholders, thereby providing practical guidance for corporate green transformation and sustainable development. Finally, this research also contributes to policy development and optimization.

Evaluating the Role of GCC Nations in Sustainable Energy Investment Using an Enhanced Low-Carbon Economy Index

In the past decade, environmental, social and country governance (ESG) aspects as well as economy have become key factors for decisions in the investment and future development of renewable energy industry. The abundancy of renewable resources and widely accessible technology are the key drivers for the renewable energy business in the GCC. However, lack of effective policies and regulations, along with subsidized fuel prices, are slowing down the implementation of renewable resource options. This study will illustrate the potential, the challenges, and the barriers of implementing renewable energy technologies in the GCC region. In addition, this research empirically examines the impact of renewable energy sources and other factors in the GCC countries. This study can be used as a screening tool, decision making tool, benchmarking tool and guidance of sustainable development.

Describing the Framework for AI Tool Assessment in Mental Health and Applying It to a Generative AI Obsessive-Compulsive Disorder Platform: Tutorial.

As artificial intelligence (AI) technologies occupy a bigger role in psychiatric and psychological care and become the object of increased research attention, industry investment, and public scrutiny, tools for evaluating their clinical, ethical, and user-centricity standards have become essential. In this paper, we first review the history of rating systems used to evaluate AI mental health interventions. We then describe the recently introduced Framework for AI Tool Assessment in Mental Health (FAITA-Mental Health), whose scoring system allows users to grade AI mental health platforms on key domains, including credibility, user experience, crisis management, user agency, health equity, and transparency. Finally, we demonstrate the use of FAITA-Mental Health scale by systematically applying it to OCD Coach, a generative AI tool readily available on the ChatGPT store and designed to help manage the symptoms of obsessive-compulsive disorder. The results offer insights into the utility and limitations of FAITA-Mental Health when applied to "real-world" generative AI platforms in the mental health space, suggesting that the framework effectively identifies key strengths and gaps in AI-driven mental health tools, particularly in areas such as credibility, user experience, and acute crisis management. The results also highlight the need for stringent standards to guide AI integration into mental health care in a manner that is not only effective but also safe and protective of the users' rights and welfare.

Conflicts of Interest in Bronchoscopy Research - Is Self-Reporting Sufficient?

Robotic assisted bronchoscopy has been enthusiastically adopted in the U.S. and transformed the management of patients with indeterminate pulmonary nodules. Unprecedented industry investments in research, development, and marketing have profoundly affected the bronchoscopy landscape, leading to concerns that conflicts of interest could influence the validity of bronchoscopy studies. Disclosures of conflicts of interest in research are predicated on open and transparent self-reporting. Are self-reported relevant conflicts of interest in articles pertaining to robotic assisted bronchoscopy accurate when compared to publicly available payments on the Centers of Medicare & Medicaid Services' Open Payments Database? All articles pertaining to robotic assisted bronchoscopy indexed on PubMed between 2016 and 2022 were screened for relevance. Articles appearing in the five journals with the most relevant publications were selected. General, research, and associated research payments reported in the Open Payments Database were recorded for each US physician-author with available data. "Relevant payments" refer to transactions made to authors by bronchoscopy-related companies. Documentation of all payments involving these companies during the three years prior to an article's submission date was obtained. These payments were compared to the self-reported conflicts of interest for each author, per article, and the number and value of payments were categorized and totaled. Twenty-seven articles were included, accounting for 75 U.S. physicians with data reported in the Open Payments Database. Of the $17 million in relevant payments reported, $9.9 million were not disclosed (57%). Sixty-eight of 75 (91%) of authors had incomplete physician disclosures. Excluding food and beverage payments, sixty authors had incomplete disclosures (80%). Relevant conflicts of interest appear to be inconsistently disclosed in publications on robotic assisted bronchoscopy, suggesting self-reporting may be an insufficient strategy. A centralized disclosure process that is automated or easier to use should be considered.

Talent Retention and Competitive Advantage of Star Rated Hotels in Rift Valley and Western Region, Kenya

The demand for both local and international visitors has seen local investors in the hospitality industry in Kenya jostle for market share. The arrival of the international hotel brands such as Best Western, Pullman and Park-In among others has increased competition as hotels scramble to provide quality products and services to their customers. Consequently, this sought to explore the influence of talent retention on competitive advantage of star rated hotels in Rift Valley and Western region, Kenya. The study was anchored on human capital theory. The study used simple random sampling to select a sample size of 62 respondents. The study adopted a correlational research design and data was collected using a questionnaire and analyzed quantitatively using both descriptive and inferential statistics. Prior to the actual data collection exercise, the study conducted pilot testing which involved both validity and reliability testing. The findings were presented in tables. The findings revealed that talent retention had a positive and significant influence on competitive advantage of star rated hotels in Rift Valley and Western Region, Kenya (P=0.000). The study concluded that hotel's talent retention strategies are generally effective especially enhancing a minimal employee turnover, a positive corporate image, and the use of succession planning and growth opportunities to retain talent. In view of the findings, the study recommends for the strengthening of the internal talent pool by investing in employee development programs. Encourage internal mobility and provide clear career progression paths to retain and motivate top talent. Keywords: Talent Retention, Competitive Advantage, Star-Rated Hotels, Rift Valley, Western Kenya

Talent Retention and Competitive Advantage of Star Rated Hotels in Rift Valley and Western Region, Kenya

The demand for both local and international visitors has seen local investors in the hospitality industry in Kenya jostle for market share. The arrival of the international hotel brands such as Best Western, Pullman and Park-In among others has increased competition as hotels scramble to provide quality products and services to their customers. Consequently, this sought to explore the influence of talent retention on competitive advantage of star rated hotels in Rift Valley and Western region, Kenya. The study was anchored on human capital theory. The study used simple random sampling to select a sample size of 62 respondents. The study adopted a correlational research design and data was collected using a questionnaire and analyzed quantitatively using both descriptive and inferential statistics. Prior to the actual data collection exercise, the study conducted pilot testing which involved both validity and reliability testing. The findings were presented in tables. The findings revealed that talent retention had a positive and significant influence on competitive advantage of star rated hotels in Rift Valley and Western Region, Kenya (P=0.000). The study concluded that hotel's talent retention strategies are generally effective especially enhancing a minimal employee turnover, a positive corporate image, and the use of succession planning and growth opportunities to retain talent. In view of the findings, the study recommends for the strengthening of the internal talent pool by investing in employee development programs. Encourage internal mobility and provide clear career progression paths to retain and motivate top talent. Keywords: Talent Retention, Competitive Advantage, Star-Rated Hotels, Rift Valley, Western Kenya

Organizing planning knowledge for automated vehicles and intelligent transportation systems

AbstractIntelligent Transportation Systems (ITS) are crucial for developing fully automated vehicles. While significant progress has been made with advanced driver assistance systems and automation technology, challenges remain, such as improving traffic information, enhancing planning and control systems, and developing better decision‐making capabilities. Despite these hurdles, the potential benefits of ITS are so many that its challenges have attracted substantial industrial investment and research groups interested in the automated driving field. In this work, a methodology based on state space search for planning knowledge integration is proposed. The main goal of the proposal is to provide a planning system with the necessary information to perform properly any task related to lateral and longitudinal control, path following, trajectory generation, arbitration and behavior execution by localizing the vehicle with respect to a high‐level road plan. To this end, this research compares cutting‐edge methods for rapidly finding the K nearest neighbor in relatively high dimensional road plans constructed from the traffic information stored in a high definition map. During the experimentation phase, promising real‐time results have been obtained for fast KNN algorithms, leading to a robust tree index‐based methodology for decision making in self‐driving vehicles combining path planning, trajectory tracking, trajectory creation, knowledge aggregation and precise vehicle control.

Case Analysis About Demand Changes of New Energy Vehicles and Its Stock Returns

The industry for new energy vehicles (NEVs) has experienced giant growth which draws interest from investors, decision-makers, and scholars. This research examines the relationship between changes in market demand and the stock returns of NEV firms. The method we use is to take into account a number of variables including international relations, governmental regulations, and developments in related industries. This article investigates the cases of Tesla Inc. and NIO Inc. on the performance of NEV stocks by the following ideas: the impact of foreign relations, government policies, and shifts in associated industries. For investors in the NEV industry, the results highlight how crucial it is to understand market dynamics as well as possible dangers and possibilities. Also, the article suggests topics for further investigation, such as the effects of NIO's global initiatives like growing product lines and Tesla's growing product range. Stakeholders hoping to properly manage the changing NEV ecosystem will find great insights from this thorough investigation.

Institutional investment in addictive industries: an important commercial determinant of health.

The production of addictive commodities is subject to a range of commercial determinants. There has nevertheless been a gap in understanding how investments into addictive commodities may function as commercial determinants. Institutional investors can yield important financial power with their investment decisions. Many investors apply responsible investment (RI) policies to address environmental, social, and governance concerns. Negative screening is used to exclude certain sectors or companies from investment portfolios, mainly for ethical concerns. Negative screening also affects investment into tobacco and other addictive industries. This article investigates RI policies toward addictive industries among institutional investors that are signatories of the Tobacco-Free Finance Pledge (TFFP; N = 161). The TFFP is an initiative created in 2021 to de-normalize tobacco-related investments. The mixed-method study uses descriptive statistics to quantify the extent and scope of exclusion policies as well as institutional and geographical profiles of investors, and a qualitative analysis of the justifications for these exclusion policies. Some TFFP signatories apply negative screening to other addictive industries (gambling: 35%; alcohol: 24%; cannabis 12% of signatories). There are important differences in the applied exclusion thresholds, with only 47% of TFFP signatories applying a zero-tolerance policy to tobacco. Thresholds are higher for other addictive industries. Signatories also differ in terms of their geographical and investor profiles. Justifications pertaining to compliance with international standards and reputational risks were the most common. Addictive industries, such as tobacco, alcohol, gambling, and recreational cannabis, are increasingly excluded by investors. However, different understandings of RI influence how sector exclusions are implemented. Divesting from tobacco and other addictive industries is a crucial step toward a public health approach that prioritizes population health over financial profits. Prominent institutional investors are influential opinion leaders who can change the behavior of other investors and de-normalize controversial industries and reduce or prevent harm.

Research on Quantitative Investment Strategies of Securities Investment Funds

This paper investigates the quantitative investment strategies of securities investment funds, aiming to explore their applications in financial markets and their impact on investment decision-making. Through a review of relevant literature and empirical data, the paper first outlines the basic concepts of quantitative investing and its importance in securities investment funds. Then, it discusses various quantitative strategies, including multi-factor models and machine learning algorithms, and validates their effectiveness through case studies. The research finds that quantitative investing can enhance the scientific and accurate nature of investment decisions while effectively reducing investment risks. Finally, the paper provides suggestions for optimizing quantitative strategies and discusses future trends, offering practical references for the investment industry.

An approach for urban agglomerations integration evaluation based on multivariate big data: case of the Central Plains Urban Agglomeration

ABSTRACT The Central Plains Urban Agglomeration (CPUA) is a link of economic development to connect the eastern part and western part in China. Current research on urban agglomeration integration mainly uses urban properties’ data. This paper conducts an evaluation method for urban agglomeration integration based on multivariate big data. This method mainly applies eigenvector centrality to assess the integrated situation of the CPUA from four dimensions (internet connection, industrial economy, public service and coordinated governance). The data of this research mainly includes cell phone signaling data, Baidu index, industrial investment data and statistical data for planning. The main innovations and contributions of this research is that (i) on the theoretical aspect, this research proposed an index indicator evaluation system for integration of urban agglomerations based on Analytic Hierarchy Process (AHP) and expert rating. It contributes for the further development of regional integration and other related theories; (ii) on the practical aspect, this study, taking the CPUA as example, presents an assessment approach that uses multivariate big data to measure the current integrated situation of urban agglomeration. This method provides decision-making support for the development of urban agglomeration integration.

The Long-Run Impacts of Public Industrial Investment on Local Development and Economic Mobility: Evidence from World War II

Abstract This paper studies the long-run effects of government-led construction of manufacturing plants on the regions where they were built and on individuals from those regions. Specifically, we examine publicly financed plants built in dispersed locations outside of major urban centers for security reasons during the United States’ industrial mobilization for World War II. Wartime plant construction had large and persistent impacts on local development, characterized by an expansion of relatively high-wage manufacturing employment throughout the postwar era. These benefits were shared by incumbent residents; we find men born before WWII in counties where plants were built earned ${\$}$1,200 (in 2020 dollars) or 2.5 percent more per year in adulthood relative to those born in counterfactual comparison regions, with larger benefits accruing to children of lower-income parents. The balance of evidence suggests that these individuals benefited primarily from the local expansion of higher-wage jobs to which they had access as adults, rather than because of developmental effects from exposure to better environments during childhood.

Trends and factors influencing the development of international tourism

The purpose of the article is to determine the return on investment produced by identifying modern trends in the development of international tourism and identifying factors affecting the development of tourism in the Republic of Kazakhstan. In order to achieve the objectives a certain number of regions and places of visitor accommodation were considered, investment in the tourism industry was analysed, and the results of a dynamic model with a distributed lag were obtained for the selected regions. Tourism development is an urgent topic, tourism is a source of income for millions of people working in this field, therefore, increasing the pace of development of the tourism sector is discussed in the Agendas of international organizations and in the annual Messages of the Head of State to the people of Kazakhstan. To determine the strategy for the development of the tourism services market, the factors influencing it were identified and a statistical analysis was carried out. Multiple correlation and regression analysis is one of the methods by which one can investigate the dependence of one variable on several variable factors. And for this purpose, significant factors were selected, and a multiple linear regression equation was constructed. The authors carried out a correlation and regression analysis using the example of regions, and also analyzed the obtained parameters of the multiple linear regression equation. In conclusion, the obtained regression equations in general and the coefficients are statistically significant and reliable at an appropriate level of significance. It allows us to draw conclusions based on the analysis of the obtained parameters of the multiple linear regression equation for the republic.

The impact of big fund on the operational efficiency of semiconductor companies: Corporate social responsibility as a non-economic output

This study contributes to research on the total factor operational efficiency of the semiconductor company considering corporate social responsibility (CSR) by proposing a novel integer-valued nonparametric frontier method. This method adopts an endogenous directional distance function, which first selects the benchmark and then endogenously determines the directional vector. Avoiding the issue of non-integer slack adjustment increases the convenience of formulating incentive plans and calculating efficiency. We apply this method to the input–output data of 185 listed Chinese semiconductor companies from 2010 to 2022, considering integer-valued CSR as non-economic output. Global Malmquist productivity index analysis shows that the average total factor operational efficiency of companies that received investment from the National Integrated Circuit Industry Investment Fund (Big Fund) increased by 6.9%. Using the econometric technique, we verify that the total factor operational efficiency of semiconductor companies receiving Big Fund investment increased by 0.084 compared to those without Big Fund investment. Heterogeneity analysis showed that the effect of Big Fund was more significant in improving the total factor operational efficiency of state-owned, new, and non-integrated circuit semiconductor companies, implying the necessity of purposeful investment policies for the Big Fund.

Financial subsidies, digital finance, and corporate industrial investment level

This study examined the impact of digital finance and financial subsidies on enterprises’ industrial investment based on data from China A-share listed companies in Shanghai and Shenzhen from 2011 to 2020. Results show that the development of financial subsidies and digital finance positively impact industrial investment, further easing the financial constraints of enterprises. Based on results, suggestions such as rational resource usage and a clear investment direction are made.

Analysis of registered clinical trials in Italy regarding dermatology (2003-2022): a cross-sectional study on historical trend and prospects for industry investments.

This cross-sectional analysis intends to evaluate trend and outlook of industry clinical research in Italy regarding dermatology and its prospects for the next few years. A computerized search of ClinicalTrial.gov database was carried out considering the 20-year period 2003-2022 using the following string: "Skin Diseases OR Skin cancer OR Skin Neoplasms OR Skin Infection OR Skin Lesion OR Skin Ulcer OR Skin Laxity OR Skin toxicity OR Dermatologic Complication OR Skin abnormalities". During the last 20 years 690 Industry Clinical Trials (IndCTs) were conducted in Italy regarding dermatological investigations, almost entirely funded by non-Italian pharmaceutical companies, involving 4497 centers, and recruiting an average of 13.0 subjects per site. The number of controlled and randomized studies has grown quite regularly and in the last 5 years they represented 79.6% of IndCTs initiated. Countries most frequently sharing with Italy international protocols were Spain (75.0%), Germany (71.8%), France (68.5%), the USA (67.4%), and the UK (54.8%). These data point to a historical involvement of Italy in dermatology IndCTs lower than in the major European countries. However, the war in Ukraine has deprived IndCTs of the contribution of Russia, Ukraine, and Belarus, meaning a mean of about 40 new IndCTs per year in a population of 200 million inhabitants. In contrast, many indicators point to Italy as a country with potential in dermatology wider than used in the past: an efficient health care system accessible to any citizen or resident, 4.6 million dermatological interventions per year, low density of IndCTs concerning dermatology, good production of scientific papers in indexed medical journals, relatively low cost of services and labour and geopolitical stability. The European Clinical Trials Information System's (CTIS), mandatory for the EU member states since early 2023 allows common, simplified, and harmonized regulatory procedures over the life cycle of clinical trials in Europe (EMA, 2023) and plays in favor of Italy's greater competitiveness in clinical research.

Issues of efficiency of financing the agricultural sector

In many economically developed countries, state support, financial investments in the agricultural industry, increasing productivity and profitability, ensuring the availability of food are the main factors of economic growth, first of all, employment of the population. Purpose - the main problems of financing the agro-industrial complex of the republic and scientific approaches to their solution are considered. Methods - comparative analysis, synthesis, monographic, logical evaluation to determine the mechanisms affecting the effectiveness of state aid and investment. Results - the article analyzes the sources of budgetary allocation of the agrarian sector. The significance of the implementation of targeted programs aimed at improving the quality of life of rural residents through price, tax, leasing mechanisms, soft loans and subsidies is shown. The study presents information for 2018-2022, supplemented by the data of the National Project on the development of agro-industrial complex of the Republic of Kazakhstan for 2021-2025, including the total volume of agro-industrial production and the size of capital investments. The study notes the need to increase the volume of domestic processing industry, allowing agricultural producers to expand the market for products, create conditions for new jobs, attract investment, and contribute to economic and social stability. Conclusions - specialization of rural areas, development of technical map and related organization of production in promising villages and district centers, increase in exports, distribution of online services are strategic directions of development of food complex, economic activity of agroformations. The use of external resources gives an opportunity to improve financial results, and farms - to increase income from core activities. When planning large investments in agricultural projects, one of the key criteria is the choice of capital structure to support the investment process.

Understanding EU Funding of Anti-Trafficking Initiatives: Where is the money (not) going?

Critical trafficking scholars have questioned the staggering and ever-rising scale of financial investments in the anti-trafficking industry. While many analyses have focused on the United States, considerably less attention has been devoted to anti-trafficking funding provided by the European Union (EU). This paper draws on an analysis of the results of several EU programmes funding anti-trafficking actions during the 2014–2020 programming period. It describes the type of projects and organisations funded, the countries involved, the amounts awarded, and the potential reoccurrence of funding toward specific organisations. It also presents the findings of a survey of European NGOs working in the field of anti-trafficking to investigate approved and rejected projects, the reasons for rejection, and the key challenges faced in accessing EU funding. The overarching aim is to better understand funding trends against the backdrop of EU anti-trafficking policy priorities.

A landscape analysis of investors in the global breast milk substitute industry to target for advocacy.

The International Code of Marketing of Breast-milk Substitutes and subsequent resolutions (the Code) was adopted to address increases in mortality and morbidity resulting from the practices of the breast-milk substitute (BMS) industry. The lack of success in ensuring company compliance with the Code has prompted advocates to consider engaging with investors to shape the governance of BMS companies. To support these efforts, this paper aimed to identify prominent investors in the global BMS industry and explore their Code-related policies and practices. Using multiple methods and data sources, we developed a novel approach to identify and rank investors in the world's leading publicly listed BMS companies. We also examined the policies and voting behaviour of a sample of investors using publicly accessible materials from 2020 to 2022. We found that a small number of large investors, led by BlackRock and Vanguard, hold a substantial share in the global BMS industry. Of the top-10 ranked investors, only Norway's Government Pension Fund (NBIM) reported policy information relating specifically to BMS marketing. Most of these large investors also opposed the sample of public health-related shareholder proposals analysed. In addition, we identified several investors that have reported engaging with BMS companies on Code-related issues, including NBIM, Pictet, and UBS, along with several potential investor targets for future advocacy efforts, including some North American public pension funds. The inclusion of Code-related issues as part of broader policies, disclosures and regulations related to environmental, social and governance oriented investment warrants increased attention.

Private benefit of β-lactamase dictates selection dynamics of combination antibiotic treatment

β-lactam antibiotics have been prescribed for most bacterial infections since their discovery. However, resistance to β-lactams, mediated by β-lactamase (Bla) enzymes such as extended spectrum β-lactamases (ESBLs), has become widespread. Bla inhibitors can restore the efficacy of β-lactams against resistant bacteria, an approach which preserves existing antibiotics despite declining industry investment. However, the effects of combination treatment on selection for β-lactam resistance are not well understood. Bla production confers both private benefits for resistant cells and public benefits which faster-growing sensitive cells can also exploit. These benefits may be differentially impacted by Bla inhibitors, leading to non-intuitive selection dynamics. In this study, we demonstrate strain-to-strain variation in effective combination doses, with complex growth dynamics in mixed populations. Using modeling, we derive a criterion for the selection outcome of combination treatment, dependent on the burden and effective private benefit of Bla production. We then use engineered strains and natural isolates to show that strong private benefits of Bla are associated with increased selection for resistance. Finally, we demonstrate that this parameter can be coarsely estimated using high-throughput phenotyping of clonal populations. Our analysis shows that quantifying the phenotypic responses of bacteria to combination treatment can facilitate resistance-minimizing optimization of treatment.