Ebook: Modern Management based on Big Data V

With general topics like “big data and modern management” and various hot topics, MMBD2024 has attracted many submission from professors and post-graduate students, especially Ph.D. scholars from different universities worldwide, as well as technicians, policymakers and top managers of organizations and business companies from various industries. The selected accepted papers focus mainly on: Innovation in Online Education Management with Big Data; Green Supply Chain Management; Big Data Analytics in Supply Chains; Decision Making on Sustainable Development; Digital Economy; Digital Innovation; Social Strategy to Managing Human Relationships.

All the papers were reviewed thoroughly and with dedication by international Technical Program Committee (TPC) members and anonymous reviewers, while taking into account the MMBD scope, and the 63 most promising contributions were included in this proceedings, selected from about 180 submissions.

I would like to take this opportunity to thank all the keynote and invited speakers, authors, program committee members and anonymous reviewers whose work made this conference possible. I am also grateful to the members of the TPC and Local Committee for their efforts in fostering a successful MMBD conference. Last but not least, I’d like to thank IOS Press for their joint efforts in publishing this volume in the book series Frontiers in Artificial Intelligence and Applications (FAIA) as the fifth installment of the MMBD conference series.

June 2024

Antonio J. Tallón-Ballesteros

University of Huelva (Spain)

Huelva City, Spain

The concept of partnership between the public and private sectors is considered a new concept in Palestine, as it is a country under Israeli occupation, and previous studies have not focused on examining the impact of knowledge management in achieving the success of partnership projects between the public and private sectors. This study aims to identify the role of organizational culture (OC). in the relationship between knowledge management (KM) and the success of public-private partnership projects (SPPPs) in the construction sector in Palestine. 150 specialists were contacted from different public and private sectors (government, private, and academic employees who have experience in implementing partnership projects), and 130 questionnaires were considered usable. The Smart Pls-4 program was used to analyze the data, and the study concluded that knowledge management has a significant impact on the completion of partnership projects between the public and private sectors. Moreover, knowledge management has an important relationship with the organizational culture of organizations, and the results also showed that OC acts as a mediating influence in the relationship between knowledge management and SPPPs.

This study aims to explore the research situation of recent smart clothing based on summarizing the research hotspots and predicting the research trends in smart clothing through scientific knowledge mapping. The English literature related to smart garments collected in the Web of Science (WOS) core database up to 31 December 2023 was searched by the co-occurrence analysis method, and the visual knowledge mapping analysis was conducted. The study found that China has a high influence in the field of smart clothing, with the highest number of articles accounting for 44.95% (178 articles) of the total number of articles. The study authors are closely linked but do not form a core group of authors. The keywords and emergent words reflect the corresponding research hotspots for design, performance, emi shielding, pressure, thermal management, wearable electronics, composites and fabrics of smart clothing. With social and environmental technology development, smart clothing will be allowed in the coming period; the research prospect is broad and technological.

Cost leadership strategy (CL) enables organizations to earn above-average returns despite intense competition by differentiating their products and services. This study examines (CL) and the moderating influence of general environment (GE) on organizational performance (OP), specifically in Kenyan public universities. For the cross-sectional survey, two hundred (200) top and middle-level managers were purposively sampled from a population of four hundred (400) managers. The measurement model assessed reliability and validity, and bootstrapping yielded structural model path coefficients, standard deviations, and T statistics. The results showed that (CL) had a significant and positive effect on OP, whereas GE had an insignificant influence on OP. Finally, GE had an insignificant moderating influence on CL and OP. Management, policymakers, and the government can use the findings to formulate policy and competitive strategies.

This article proposes a random constrained dual parameter ridge estimator with random constraints for the problem of multicollinearity in linear regression model. Under the mean square error matrix, the superiority of the new estimator over the dual parameter ridge estimator, common mixed estimator and random constrained ridge estimator is discussed. And the theoretical results are demonstrated through a numerical example and a simulation study.

COVID-19 pandemic unexpectedly created many health risks when it appeared at the end of 2019 and beginning of 2020. The aim of this paper is to examine perception of general health risks during the second wave of Pandemic (October 2020 to December 2020). For this purpose, a questionnaire that explores different risks during COVID was created. The study included a survey with a specific target group which was chosen purposefully from members of opposing political parties in N. Macedonia in order to explore potential differences. 100 respondents in total were included in the sample, consisting of 50 respondents from two main political parties (VMRO-DPMNE and SDSM) in the country. The findings show that were no differences between members of opposing political parties when it comes to aspects related to general health risks during COVID. The conclusion stated that results are related to beliefs of members of political parties in the efficacy of well-known measures. The findings provide excellent background for creating strategies for management of public perception in situations with health risks.

Apart from vaccines, communication is the second most effective tool in combating COVID-19 pandemic. The aim of this paper is to examine attitudes towards government communication about COVID-19 during the second wave of Pandemic (October 2020 to December 2020). The attitudes towards government communication were already formed after the initial first wave. The sample consisted of 100 respondents in total, with equal gender representation. Members of two main political parties were included in the sample. Half of the sample were members of VMRO-DPMNE, while the other half were members of SDSM. Significant differences were found in the attitudes towards government communication on all aspects between members of opposing parties. The explanation is related to the political beliefs in a polarized society. The findings provide valuable recommendations for designing government communication related to future pandemic.

Consumers have become increasingly interested in green food as their environmental knowledge has improved since the COVID-19 pandemic. Examining variables that affect green food usage is thus crucial. However, there is a literature gap in this matter, i.e., studies that examine the role of ICTs on consumer’s green knowledge and behavior toward green food remain scarce as prior studies focused on the role of internal factors such as risk perception, motivations, food neophobia, and consumers’ trust. This study seeks to investigate in what way consumers’ green knowledge influence their purchases of green food and how ICT usages moderate this link. This research aims to test the theoretical framework through the construction of a Hidden Markov Framework (HMF). In various usages of information and communication technologies (ICTs), the utilization likelihood of green food with varying green knowledge are calculated using the HMF. Additionally, the shift likelihood of green food buying is computed using a dynamical period cycle. Furthermore, the notions of continuity, reliance, and willingness in green food utilization are explained and calculated in this research. In order to confirm the accurateness of the likelihood computation and the consistency of the HMF, the method is utilized to predict the consumer behaviors of the actual situation. The findings verify that the usage of ICTs has a moderating influence on the positive correlation between consumer’s green knowledge and their behavior toward green food. Future studies can use our framework in different contexts such as another emerging country or another green product, and test the framework using different analytical tools such as Artificial Neural Networks and different approaches such as Multi-criteria Decision Making.

This paper takes the patent data of listed IC companies in Derwent Database from 2011 to 2020 as a sample, and identifies the generic technologies of China’s IC industry based on the analysis methods of technology co-occurrence rate and technology co-class index. Based on the social network analysis method, the current situation of enterprise cooperative innovation in the field of generic technology in China’s IC industry is analyzed from both the whole and individual perspectives, and the relevant research results are obtained, which can provide reference for optimizing the layout of industrial technology and promoting the development of generic technology in China’s IC industry.

The main objective of this study is to examine the relationship between organizational learning and growth of small and medium enterprises (SMEs) in the Republic of North Macedonia. SMEs frequently exhibit accelerated growth trajectories relative to their larger counterparts, a phenomenon ascribed to diverse facets of organizational learning. Given the pivotal role of SMEs in overall economic activity and expansion, this paper scrutinizes the specific aspects of organizational learning influencing the growth of SMEs. Consequently, a quantitative research approach was employed, utilizing structured interviews conducted with 45 Managing Directors of SMEs operating within the Republic of North Macedonia. The findings of the research contribute to the existing literature with the new findings related to the relationship between growth of family business and learning. It was found that there is a positive association between growth and implementation of incentives for staff thus acknowledging their contributions to the organizational learning processes. On the other hand, a negative relationship was identified between the absence of open communication channels and growth. The implications of these findings are important for general managers of SMEs as they endeavor to foster growth through strategic learning initiatives. The specific recommendations are about training related to the development of existing skills or training in new ideas that could potentially bring innovation to the company. The findings emphasize the importance of fostering a learning culture within companies, highlighting the need to create an environment where continuous learning is encouraged and valued across all organizational levels.

The paper aims to explore the link between growth and strategy among small and medium enterprises (SME) in Republic of North Macedonia. SME often have higher growth rates than large enterprises, which can be attributed to different factors. Given the importance of SMEs for the overall economic activity and growth, this paper explores which aspects of strategy affect growth of SMEs. Therefore, quantitative research was conducted with 45 Managing Directors of SMEs in Republic of North Macedonia. The research found that there is a correlation between growth and two aspects of strategy: provision of non-standard service to customers and staying late. The study’s findings are valuable for devising market competition strategies, particularly beneficial for SMEs. They offer essential guidance for making informed tactical and strategic decisions, especially regarding future growth. By focusing on key factors crucial for SME expansion, such as extended service hours and providing unique customer services, managers can tailor their strategies to foster growth effectively.

This study builds a centralized and decentralized decision game model of a two-level green supply chain based on the uncertainty theory, taking into account the uncertainty of the unit production cost of green goods and the pertinent parameters of market demand. The findings demonstrate that, in an uncertain setting, centralized decision-making can provide more environmentally friendly outcomes at a lower cost than decentralized decision-making. Furthermore, there is a positive correlation between product greenness, price, and supply chain profit and the uncertainties of market demand and consumers’ sensitivity to green products, yet there is a negative correlation between the uncertainties of green investment cost coefficient and consumers’ sensitivity coefficient.

In the wake of the digital transformation of foreign language education, there would be inevitable transformation and reconstruction in educational evaluation modality. While the embedding of educational data mining technologies and Learning Analytics have already become the emblem of digital evaluation, very few relevant studies provide workable data processing and analysis models for higher foreign language education. In this context, this research aims to propose a software-aided data processing, analysis and visualization model for the empirical data sets acquired from actual blended teaching practice. This research was conducted in an application-oriented university with a small-scale sample of 20 English major juniors. Theoretically, the research design is framed by learning analytics; Methodologically, this research is designed as a mixed-method and adopts the social network analysis paradigm in data analysis. The contribution of the research is a practical empirical approach to digital evaluation and the development of a whole-network-based mapping model which produces the cognitive ability and performative map of learners for the evaluation of learner’s language and socio-cognitive development. The research findings suggest a whole network analysis paradigm can be integrated with digital evaluation in areas like multidimensional data synthesis, analysis and visualization, and the software-aided whole network analysis can be a surrogate measure for digital evaluation.

In this paper, we investigate the Cournot-Bertrand double oligopoly hybrid competition model proposed by Zhu et al. (2021). By using the central manifold reduction theorem we analyze the structural stability of the model for three fixed points. We show that a subcritical (supercritical) flip bifurcation occurs at first (second and third) fixed point. This reflects that in the market competition, there will be a 2-period cycle between two firms. When subcritical flip bifurcation occurs, the 2-period cycle is unstable and the objective function values of both firms gradually deviates from the cycle. On the contrary, when the supercritical bifurcation occurs, the 2-period cycle is stable, and the objective function values of both firms gradually tend to the stable cycle. We also prove that a transcritical bifurcation will occur at the second fixed point, which indicates that the two firms will present two equilibrium states on both sides of the fixed point in the small neighborhood, but the stability of these two equilibrium states is opposite.

This study aimed to assess students’ acceptance of integrating artificial intelligence (AI) technology into teaching methods by integrating the traditional Chinese medicine constitution identification robot into nursing informatics coursework. This exploration served as a foundation for the potential widespread adoption of AI-assisted teaching practices. Before course commencement, 72.29% of students admitted limited knowledge of AI, whereas 55.42% expressed doubts about adapting to AI-integrated nursing courses. However, 93.37% of students endorsed the introduction of AI technology in the experimental coursework, with 83.13% believing that the widespread AI use in clinics would bolster confidence in the nursing field. Initially, students lacked confidence in learning courses that incorporated AI technology. However, post-course, more than 98% expressed satisfaction with the AI teaching mode. Integrating AI technology into nursing education fostered student engagement, boosted confidence in nursing practice, and mitigated nursing workforce attrition. This approach holds promise for future educational endeavors.

This paper uses stochastic frontier analysis to study the innovation efficiency of 83 leading listed agricultural enterprises from 2016 to 2021 in China. It is found that the innovation efficiency of China’s leading listed agricultural enterprises is not high as a whole, and although there was a slight decline during the period, it showed an overall upward trend and obvious fluctuation characteristics. Further econometric analysis is used to analyze the investment scale of innovation factors has a significant impact on the innovation efficiency of leading agricultural listed enterprises, the size and age of enterprises have a significant positive impact on innovation efficiency, and the impact of leverage level is significantly negative, and the government subsidy and equity concentration are significantly weak. The innovation efficiency of state-owned enterprises is generally higher than that of non-state-owned enterprises, and the innovation efficiency of enterprises in the eastern region is the highest, followed by the central and western regions, and the lowest in the northeast. The marginal contribution of this article may lie in: firstly, compare the innovation efficiency level of agricultural leading listed enterprises in different ownership types and registration places; secondly, construct the model of influencing factors of innovation inefficiency of agricultural leading listed enterprises to provide reference for improving innovation efficiency of agricultural leading listed enterprises.

Drawing from the essence of sustainable agricultural practices, this study upholds the foundational principles of ecological and resourceful stewardship, prioritizing excellence in growth. An evaluative framework has been devised to gauge the eco-friendly progress of agriculture at the county level, encompassing three key areas: the preservation of resources, ecological sustainability, and the caliber of productivity. Utilizing a data set spanning a decade (2012–2021) and encompassing 25 counties within the Ningxia region, the research employed several analytical techniques: (1) applying the entropy approach to ascertain the degree of agricultural sustainability, (2) leveraging the kernel density estimation to examine the progression over time, (3) employing the Gini index to dissect regional disparities in sustainable development, and (4) categorizing the trajectory of eco-progression across the counties. The findings indicate an upward trend in the eco-progressiveness of Ningxia’s counties, with a notable reduction in regional disparities and spatial inequalities. In conclusion, the study advocates for a strategic blend of holistic enhancement and targeted initiatives to steer Ningxia’s agricultural sector towards a greener future.

Agriculture is the foundation of the national economy. The application of digital technology in the field of agriculture can improve agricultural modernization. The theoretical mechanism show that digital technologies play an important role on improving agricultural production efficiency, promoting the integrated development of agricultural industry and other industries, the quality of agricultural products, optimizing the entire agricultural industry chain. By calculating and comparing the location entropy, the correlation degree, and using Data Envelopment Analysis (DEA) of the agricultural industry. The empirical study finds that the overall level of agricultural industry agglomeration in China needs to be improved, and the regional differences in the degree of agricultural industry correlation are obvious, and the agricultural production efficiency is low. Therefore, we suggest that accelerating the application of digital technology in the agricultural product circulation and service industry, developing digital application in key agricultural production; and deepening the integration of digital and agriculture to achieve agricultural modernization faster and better.

COVID-19 shook the global economy, companies, and people. Digitalization helps many companies withstand the pandemic. This study examines how digital transformation (DT) process affect modern technologies like Big Data Analytics (BDA) and blockchain technology (BCT). Using partial least squares structural equation modeling (PLS-SEM), 313 managers from SMEs in Mozambique were surveyed. The findings show that DT boosts BDA. However, DT does not impact BCT. The research suggests that new working patterns will boost talent demand irrespective of location. Incorporating BDA and BCT into manufacturing operations improves business processes and organizational management.

By retrieving information from self-media platforms such as Baidu through crawling techniques, this study focuses on the enhancement of the competency of ideological and political teachers in higher vocational colleges, aiming to distill the key elements that influences the competency of ideological and political teachers in higher vocational colleges with grounded theory, which is in order to strengthen the construction of higher vocational ideological and political teachers. It has been found that political literacy(which consists of political belief and political sensitivity), professional identity(which consists of professional responsibility, professional interest and professional development), theoretical proficiency(which consists of theoretical depth and breadth of knowledge), teaching ability(which consists of educational ideas, teaching methods and language arts), and personal traits(which consists of moral cultivation and adaptability) constitute the primary components of competence among ideological and political teachers. The findings of the study can provide essential insights for the selection, training, and assessment processes of ideological and political teachers in higher vocational colleges.

Big Data (BD) innovations have become the key differentiators in any competitive analyses, and has become/is, a lifestyle. Building on the Diffusion of Innovation theory, Technology Acceptance Models 1, 2, 3, and the International Requirements Engineering Boards’ (IREB) Requirements Engineering framework, this study aims to identify perceptions towards BD innovations, to design agile feature-based and rule-based intelligent systems, adaptable to progressive changes over time in the future. To reduce variable bias, random sampling of two overlapping demographics is carried out, over two time periods. The first case study, involves perceptions towards BD Innovations, blockchain, Augmented Reality/Virtual Reality/Mixed Reality. The second case study relates to perceptions towards intelligent assistants, e.g. Alexa. For the first case study, by triangulating correlation analyses, linear regression analyses, k-means and hierarchical agglomerative clustering (HAC) results, findings reveal different degrees of acceptance/caution among age groups and gender, and the influence of job prospects on perceptions. Furthermore, HAC’s profile means is more explanatory in terms of distribution and number of clusters, while k-means’ profile means is more positive than HAC’s. For the second case study, findings indicate that personality/dispositions, Technology Acceptance Model’s (TAM) adjustment and anchor, as well as interaction styles, may influence perceptions, more than gender or ability. Together, the two case studies provide age-progressive requirements analyses, and an opportunity tree. The fuzzy characterizations can be used in computational thinking design and matrix factorization in (fuzzy) rule-based design for seniors. However, sample size is small and thus, not generalizable.

Green building implementation has become an unavoidable trend in the growth of the construction sector, as China’s philosophy of “innovation, coordination, green, openness and sharing” deepens. Green construction, as the process of creating green structures, is essential to the buildings’ overall greenness. An extensive assessment of the three components of building planning, design, and construction, known as a “green construction evaluation”, so as to establish a set of green construction evaluation systems that meet the times’ development needs, saves resources, protects the environment and people’s better lives, and paves the way forward for improving building greenness and promoting green building development. In order to build a scientific and ideal green construction evaluation system, this paper will establish an index system focused on green buildings and prefabricated buildings. It aims to demonstrate the path for the development of green construction and encouraging the industry’s steady advancement.

With the continuous development of information technology, archives management information has become an important trend in the field of education. As a scientific research method, the paradigm concept emphasizes the integrity, systematization and regularity of scientific development, and provides new ideas and methods for the information construction of educational archives management. Based on the paradigm concept, this paper analyzes the current situation and problems of the information construction of educational archives management, puts forward a reasonable and effective construction path, which helps to improve the efficiency and quality of educational archives management, better serve the development of education, improve the efficiency and quality of educational archives management, and better serve education

High-tech industries such as information technology, big data and artificial intelligence have developed rapidly. New retail has gradually developed from the dual channel mode of mutual independence and competition between online and offline to the multi-channel mode of mutual resource sharing, coordination and cooperation and mutual drainage. And this model has become the current trend of China’s business model development. When online and offline pre-sale strategies are jointly adopted, this paper aims at maximizing the profits of enterprises, introduces consumer functions, solves multi-channel pre-sale strategies, obtains profit maximizing pre-sale discounts and sales prices. Through examples, it is proved that in the stage of production and pre-sale, the profit of new retail enterprises can be increased to a large extent by assisting new retail enterprises in controlling discounts, pricing and inventory through pre-sale discount strategies.

Using a sample of non-financial firms listed on the Shanghai and Shenzhen A-shares in China from 2012 to 2022, this paper empirically examines the effect of the internal compensation gap among executives on firms’ environmental protection investment, and further investigates the moderating role of equity concentration in it. The study finds a significant positive correlation between the internal compensation gap among executives and corporate environmental investment, i.e., increasing the pay gap will promote the level of the firm’s environmental investment. While equity concentration will weaken the positive effect of the executive internal compensation gap on corporate environmental investment. The findings of the study will enrich the research on executive internal compensation gap and corporate environmental investment, and offer new ideas for enterprises to improve the incentive mechanism of executive compensation and promote corporate social responsibility.