Research on the Impact of Digital Technology and Servitization on the Performance of Manufacturing Enterprises

This article mainly discusses the impact of digital technology and service-oriented on the performance of manufacturing enterprises.It first elaborates on the background of the trend of service-oriented manufacturing and the significance of its enterprises.Then,based on the impact of digital technology on the performance of manufacturing enterprises,several practical and feasible measures are proposed,mainly focusing on the long-term layout of service-oriented,shortening the low period,enhancing the competitive awareness of state-owned manufacturing enterprises,improving the driving force transformation,achieving simultaneous progress digitally,configuring digital and service-oriented elements,and eliminating the monopoly of digital resources.Followed by lowering the threshold for private enterprise resource acquisition,promoting financial digital development,breaking the financial dilemma of service-oriented manufacturing,continuously improving the performance level of manufacturing enterprises,and promoting the development of manufacturing enterprises.

Research on the Impact of Digital Transformation on the Performance of Manufacturing Enterprises

To address the challenges faced by manufacturing enterprises in digital transformation,this paper analyzes the relationship between digital transformation and enterprise performance.Using panel data from domestic A-share-listed manufacturing enterprises from 2012 to 2022,two hypotheses were proposed.The analysis and verification revealed that digital transformation in manufacturing enterprises can enhance performance and reduce costs.Based on the impact of digital transformation on manufacturing enterprise performance,optimization suggestions are proposed to guide future digital transformation and performance improvement efforts in these enterprises.

The Impact of E-Commerce Live Broadcasts on Consumers’Purchase Intention

E-commerce live broadcast has an important influence on consumers’purchase intention.The three dimensions of live broadcast content in the broadcast room are the number of comments,product quality,and live content as independent variables.A theoretical model is constructed with perceived value and risk as intermediaries and the consumers’purchase intention as the dependent variable,and corresponding hypotheses are put forward.We designed the scale,collected relevant data,and tested the model hypothesis using Statistical Package for Social Sciences(SPSS)and Analysis of Moment Structure(AMOS)software.The study found that the number of comments and product quality had a significant impact on perceived value,perceived risk,and consumers’purchase intention.From this conclusion,it is suggested that businesses should control the number of comments,strengthen the product quality of comments,and distinguish the repetition degree of the content of live broadcasts.

Marketing Strategy Analysis of Migu Video App Based on 4I Theory

With the increasing maturity of 5G technology and the comprehensive development of video apps on the Internet,the landscape of video app downloads shows that Migu Video lags behind giants like iQiyi,Tencent Video,Youku,and Mango TV.However,during the Tokyo Olympics and the Beijing Winter Olympics,Migu Video’s focus on sports coverage and commentary led to increased public use and app downloads.This study analyzes the marketing status and strategy of the Migu Video App.It conducts a detailed analysis using the 4I theory-interest,interaction,individuality,and initiative-and proposes a brand marketing strategy tailored for Migu Video.This aims to provide insights into the marketing strategies of other mobile Internet companies.

The Current Context and Future Trends of the Photovoltaic Business Models in Central and Eastern Europe:Case Study—Romania

The evolution of the PV industry has represented one of the main focus points of economic and political debates and research of the last ten years in Europe. However, these discussions have only presented general aspects of the industry development and accomplishments with little information about the companies’ actual practices. The present study aims to inquire the PV field in Romania further, by researching the currently implemented and the future business models of firms producing solar energy. Using the Delphi method based on questionnaires and interviews with experts of this field, this paper shows the key elements of business models in the PV field that reflect the companies’ practices and future trends and expectations regarding the internal activity of the firm and the environmental changes from the external environment of the company, which influence the directions of the PV domain. The relevance of this study is based on the importance of the applied PV business model elements in order to ensure the survival and expansion of the company in a dynamic field that faces continuous legal, economic and technological changes and challenges. The results of this study have some directions that could be applied in most of the European countries where the PV industry is developing.

Implementation of Business Game Activity Support System

Business game can be used not only as an educational tool for the development of decision making ability, but also can be used for supporting the knowledge creation activity in organizations. In this paper, some conceptual considerations to meanings of the business game in the knowledge creation activity by using the knowledge creation theory and other related theories are given, and business game activity concept which refers to game play and development is proposed. Then focusing on the business game activity as an instantiation of the knowledge creation activity, and a Web based gaming activity support system based on the former system called YBG that enables us to play and develop many business games through the standard web browser is proposed. This system also provides us a lot of opportunities to play and develop the business games over business game communities.

Socio-Psychological Factors of Rising Trend of Suicidal Ideation among Indigenous Workforce: Evidence from Himalayan Range

Apart from socio-economic disparities,indigenous people of the Himalayan range in Asia face an increasing trend of suicides.The tragic suicidal events usually go unaddressed,and no strategies are presently in place to mitigate suicides in the future.This study aims to explain the prevailing causes of suicidal ideation to come up with some policy recommendations.Through a preliminary survey,we identified social stigma,social isolation,lack of healthcare facilities,and domestic violence as the potential reasons for suicidal ideation.We identified individuals with suicide ideation for further data collection to test the relationships between the identified variables and suicidal ideation.A quantitative,explanatory and cross-sectional design was used to test the hypotheses.Inferential statistics were applied to the data containing 314 responses,and the results revealed that all the predictive variables influence the formation of suicidal ideation.The study uncovered some new dimensions of social stigma and social isolation that are common among the indigenous people.The results also indicate that some domestic violence is socially acceptable and considered a normal familial matter.Thefindings have theoretical and practical implications.We have identified new dimensions of social stigma,social isolation,and domestic violence that are new additions to the existing bank of literature.It provides insights to encourage public authorities,healthcare providers,and NGO managers to play their role in the right direction to mitigate the problem.This study opens further venues for researchers to investigate the complex issue of suicide more deeply.

Bayesian and Non-Bayesian Analysis for the Sine Generalized Linear Exponential Model under Progressively Censored Data

This article introduces a novel variant of the generalized linear exponential(GLE)distribution,known as the sine generalized linear exponential(SGLE)distribution.The SGLE distribution utilizes the sine transformation to enhance its capabilities.The updated distribution is very adaptable and may be efficiently used in the modeling of survival data and dependability issues.The suggested model incorporates a hazard rate function(HRF)that may display a rising,J-shaped,or bathtub form,depending on its unique characteristics.This model includes many well-known lifespan distributions as separate sub-models.The suggested model is accompanied with a range of statistical features.The model parameters are examined using the techniques of maximum likelihood and Bayesian estimation using progressively censored data.In order to evaluate the effectiveness of these techniques,we provide a set of simulated data for testing purposes.The relevance of the newly presented model is shown via two real-world dataset applications,highlighting its superiority over other respected similar models.

Pricing,management and decision‑making of financial markets with artificial intelligence:introduction to the issue

While the advancement of Internet Technology generates massive amounts of data that can facilitate decision makings of financial markets,it also arouses new challenges to financial activities,such as the acquisition,processing and analysis of multiple information resources.In addition,the external environment of the financial market is full of uncertainties,such as the occurrence of COVID-19 pandemic and government intervention,which makes the asset pricing and management much more challenging.In recent years,artificial intelligence technology has developed rapidly and has been widely used in various fields,including the financial markets.Due to its capability of mining patterns from big data,artificial intelligence is regarded as an efficient tool to address the abovementioned challenges.

Cost effectiveness of routine duodenal biopsies in iron deficiency anemia

AIM To investigate the cost effectiveness of routine small bowel biopsies(SBBs) in patients with iron deficiency anemia(IDA) independent of their celiac disease(CD) serology test results.METHODS We used a state transition Markov model. Two strategies were compared: routine SBBs during esophagogastroduodenoscopy(EGD) in all patients with IDA regardless their celiac serology status(strategy A) vs SBBs only in IDA patients with positive serology(strategy B). The main outcomes were quality adjusted life years(QALY),average cost and the incremental cost effectiveness ratio(ICER). One way sensitivity analysis was performed on all variables and two way sensitivity analysis on selected variables were done. In order to validate the results,a Monte Carlo simulation of 100 sample trials with 10,and an acceptability curve were performed.RESULTS Strategy A of routine SBBs yielded 19.888 QALYs with a cost of $218.10 compared to 19.887 QALYs and $234.17 in strategy B. In terms of cost-effectiveness,strategy A was the dominant strategy,as long as the cost of SBBs stayed less than $67. In addition,the ICER of strategy A was preferable,providing the cost of biopsy stays under $77. Monte Carlo simulation demonstrated that strategy A yielded the same QALY but with lower costs than strategy B. CONCLUSION Our model suggests that EGD with routine SBBs is a cost-effective approach with improved QALYs in patients with IDA when the prevalence of CD is 5% or greater. SBBs should be a routine screening tool for CD among patients with IDA,regardless of their celiac antibody status.

Assessing the Performance of Some Ranked Set Sampling Designs Using Hybrid Approach

In this paper,a joint analysis consisting of goodness-of-fit tests and Markov chain Monte Carlo simulations are used to assess the performance of some ranked set sampling designs.The Markov chain Monte Carlo simulations are conducted when Bayesian methods with Jeffery’s priors of the unknown parameters of Weibull distribution are used,while the goodness of fit analysis is conducted when the likelihood estimators are used and the corresponding empirical distributions are obtained.The ranked set sampling designs considered in this research are the usual ranked set sampling,extreme ranked set sampling,median ranked set sampling,and neoteric ranked set sampling designs.An intensive Monte Carlo simulation study is conducted using Lindley’s approximation algorithm to compute the different designs’-based estimators.The study showed that the dependent design“neoteric ranked set sampling design”is superior to other ranked set designs and the total relative efficiency is higher than the other designs’total relative efficiency.

Biological Clogging of Sand Columns

Increased microbial activity leads to biological clogging (or bioclogging), i.e., the pore space is clogged by microbes and saturated hydraulic conductivity of porous media decreases. A series of column experiments were carried out to study the bioclogging of sand columns. Hydraulic conductivity remained unchanged when a sterilizing agent was applied;however, it decreased when a glucose solution was applied. In most cases, bioclogging proceeded from the inlet of the solution;but, in some cases, it started from the bottom or outlet of the column. In this experiment, the reduction of hydraulic conductivity was better explained by microcolony models compared to biofilm models.

7G＇s Environmental Initiative through the Lens of the Technology-Organization-Environment （TOE） Framework

This qualitative research study addresses the research question of how the environmental sustainability initiative of 7G （Seventh Generation）, a product design, marketing, and distribution company in the household and personal care products, could be understood within its supply chain context using Tornatzky and Fleischer＇s TOE （Technology-Organization-Environment） framework. Content analysis, a research technique for making valid inferences from text following a set of procedures, was used and applied to secondary data materials on 7G. The findings reveal that the environmental, organizational, and technological contexts, which are key elements of the TOE framework, are useful in analyzing and comprehending the business practices and business processes adopted by 7G to pursue its sustainability initiative. Of particular interest are those business processes that were included by 7G＇s EMS （Environment Management System） and enabled by green IS （Information Systems）. Both the strengths and weaknesses of 7G＇s efforts are discussed and suggestions are presented for modifying certain phases of the systems development life cycle methodology when implementing green IS.

The impact of financial sector development on the economic growth of emerging countries： An empirical study for E-7 countries

Globalization, financial liberalization, financial integration, financial sector, and economic growth have been significant issues for many researchers. The studies have investigated the effects of the above issues to the economic growth of countries both theoretically and empirically. Since there has been conducted an enormous body of work, each of them may be grouped and studied separately. This paper focuses on the impact of financial sector development to economic growth and empirically studies the potential effect on the emerging E-7 countries, consisting of Brazil, China, India, Indonesia, Mexico, the Russian Federation, and Turkey. The study employs panel regression methodology and the data set for modeling Gross Domestic Product （GDP） comprises annual data over 2001-2007, using basic variables which resemble financial sector development, namely market capitalization of listed companies （stock market capitalization）, bank capital to asset ratio, stocks traded, total debt service, foreign direct investments, portfolio investments, real interest rates, and claims on private sector. The analysis indicates that the GDP may be modeled using the above stated macroeconomic variables with considerably high explanatory power, except for the real interest rates and bank capital to asset ratios.

Survey of Sustainable Logistics Services via Text Mining

Environmental sustainability has recently become more and more of a concern in logistics service industry. Although studies on sustainable initiatives among logistics service providers (LSP) have been increasing in the extant literature, still little investigation has been performed between LSPs and shippers. The present paper aims to demonstrate award-gained sustainable logistics service initiatives implemented during the period 2006-2017 in Japan. Different with questionnaire- and interview-based studies employed in literature, we use text mining technique to explore the co-occurring links of data, i.e. connections of the practices, to present the collaborative sustainability actions carried out through providing and requiring logistics services. In contrast to the research regarding green supply chain management focused on manufacturing perspective, this study is positioned in the dual sides of consignors and logistics business operators, to depict their combined effort in achieving sustainability goals. The results of the study showed that text mining technique is useful for summarizing and presenting data in this research area. However, much remains to be learned about how to deal with the data more means-end logically for revealing more indirect associations between the data.

The Impact of Information Technology on Admission Decisions

Information systems have been adopted in many fields including the health industry. Indeed, keeping abreast of the advances of the technological age, many medical organizations have invested heavily in information technologies （IT）, aiming at improving medical decision-making and increasing its efficiency. Despite their obvious advantages, the systems do not always immediately provide the vital medical information required for critical decision-making, and the decisions that are based on this partial information may result in a decreased level of quality of care and unnecessary costs. The objective of this research is to evaluate the contribution of IT to decision-makers （physicians） at the point of care of emergency departments （EDs） by investigating whether the information systems （IS） have improved the medical outcomes, in the complex and highly stressful environment of the ED, with time constraints and overcrowding. The authors evaluated the contribution of the medical information to admission decisions by using the track log-file analysis method. The results were obtained using a unique database containing referrals to the ED from seven main hospitals in Israel. The authors＇ results lead to the major conclusion that viewing medical history contributes to admission decisions and clearly reduces the number of avoidable admissions.

CRISE: Toward Better Understanding of COVID-19 Psychological Impact during Lockdown

Recently, the COVID-19 emerged in China and propagated around all the world has threatened millions of people and affected most countries and governments at several sides such as economical, educational, tourism, healthcare, etc. Indeed, one of the most important challenges that directly affect the people is the psychological side due to the harsh policies imposed by public authorities in most countries. In this paper, we propose a framework called CRISE that allows studying and understanding the psychological effect of COVID-19 during the lockdown period. Mainly, CRISE consists of four data stages: Collection, tRansformation, reductIon, and cluStEring. The first stage collects data from more than 2000 participants through a questionnaire containing attributes related to psychological effect before and during the lockdown. The second stage aims to preprocess the data before performing the study stage. The third stage proposes a model that finds the similarities among the attributes, based on the correlation matrix, to reduce its number. Finally, the fourth stage introduces a new version of Kmeans algorithm, called as Jaccard-based Kmeans (JKmeans), that allows to group participants having similar psychological situation in the same cluster for a later analysis. We show the effectiveness of CRISE in terms of clustering accuracy and understanding the psychological effect of COVID-19.

Triple Differential Cross-Sections for Ionization of H(3d) by Incident Electron

Triple differential cross sections (TDCS) are estimated for the ionization of metastable 3d-state hydrogen atoms by electron at 250 eV for various kinematic conditions pursuing a multiple scattering theory. The present new results are compared with the theoretical results of hydrogenic different metastable states as well as the hydrogenic ground state experimental data. Obtained new finding results are in good qualitative agreement with those of compared theories. The present results give an immense opportunity for experimental trial in the field of ionization problems.