Ebook: Modern Management based on Big Data I
The management of any modern organisation involves data, but the volume of information has become almost impossible for even the most up-to-date computer system to handle. Fortunately, big-data technologies are now enabling new ways of dealing with the flood of information, making an approximate solution possible in a reasonable time-frame, as an alternative to waiting for an exact result taking much longer.
This book contains the 17 papers presented at the inaugural conference of the new series: Modern Management based on Big Data (MMBD 2020). The conference was originally scheduled to be held in Beijing, China, but due to measures to prevent the spread of the COVID-19 pandemic, the conference was held online from 18-21 October 2020. As its name suggests, the conference covers the connected aspects of Big Data and Modern Management, and the 17 papers included here, accepted from a total of 68 submissions, cover topics including data capture and storage; search, sharing and analytics; data visualization; machine learning algorithms for big data; distributed file systems and databases; management strategy and decision making; manufacturing and logistics systems; total quality management; management information systems; human factor engineering; and human resources.
Providing an overview of current developments in modern management based on Big Data, the book will be of interest to all those working in the field.
The management of any modern organisation involves data. The volume of information is becoming almost prohibitive for even the most up-to-date computer system. But big data technologies are enabling new paths to deal with the information and get an approximate solution in a reasonable time-frame instead of an exact result taking much longer.
This year, 2020, sees the launch of the conference series: Modern Management based on Big Data (MMBD). MMBD deals with two main branches: Big Data and Modern Management. The former includes, among other things: data capture and storage; search, sharing and analytics; big data search, mining and visualization; big data technologies; data visualization; architectures for massive parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; scalable storage systems; big data for business; and government and society. The latter encompasses: modern management; management strategy; management decision making; manufacturing systems; logistic systems; facilities planning; cost analysis; engineering economy; total quality management; management information systems; human factor engineering; and human resources.
This book contains papers accepted for and presented at MMBD 2020. The conference was originally scheduled to be held from 18–21 October 2020 in Beijing, the capital city of China, to provide a high-level platform for experts and scholars from all over the world to share the latest ideas on big data and management and foster the prosperity of the discipline. However, due to the outbreak of COVID-19 around the world and for the safety of our participants, MMBD 2020 has been changed from an on-site conference in Beijing to a virtual conference with no physical participation, although with a high interaction, and the conference will be held online from 18–21 October 2020.
All papers have been conscientiously reviewed by programme committee members bearing in mind the breadth and depth of the research topics that fall within the scope of MMBD. From 68 submissions, 17 most promising and FAIA mainstream-relevant contributions have been included in this volume. These present original ideas or results of general significance supported by clear reasoning and compelling evidence and methods.
I would like to thank all the keynote and invited speakers, authors and anonymous reviewers for their efforts in making MMBD a conference of the highest standard. We are also very grateful to all those people who devoted their time to assessing the papers; especially the programme committee members and reviewers. It is an honour to be involved from the beginning with the publication of these proceedings as part of the prestigious series Frontiers in Artificial Intelligence and Applications (FAIA) from IOS Press. Our particular thanks also go to J. Breuker, N. Guarino, J.N. Kok, R. López de Mántaras, J. Liu, R. Mizoguchi, M. Musen, S.K. Pal and N. Zhong, the FAIA series editors, for supporting this conference.
Last but not least, any inconvenience caused by the format change from face-to-face to virtual is sincerely regretted. Hopefully we will all meet face-to-face at the MMBD2021 conference next year, which is scheduled to be held in Xiamen, China, with the support of the Business School of Huaqiao University.
Antonio J. Tallón-Ballesteros
University of Huelva (Spain)
Seville City, Spain
This paper mainly discusses the current situation of the internationalization developmentï£¡ the issues and challenges faced of enterprise standards in China in recent years, and the countermeasures and suggestions to be taken in the future. The research methods of qualitative analysis and case studies are mainly adopted. Both primary and secondary information resources are collected for an analysis and recognition of the progress of internationalization of Chinese enterprise standards. The key issues in the internationalization process of Chinese enterprise standards are put forward through analysis of the lessons learned such as lack of consistency in technology standards and real needs in the process of internationalization of Chinese enterprise standards in the last two decades, especially in the practice of participating in foreign infrastructure construction. Under China’s “One Belt and One Road (B&R) Initiative”, the high quality Chinese enterprise standards and internationalization are the prerequisite for the realization of international cooperation in science and technology. The novelty of this paper is mainly reflected in the countermeasures and suggestions how to enhance the internationalization level of Chinese enterprise standards in accordance with the initiatives of the “B&R” construction and the countries concerned actual needs. These include to further improve the technology level and quality of enterprise standards, improve the applicability of Chinese enterprise standards, strengthen international exchanges and cooperation in the field of standardization, establish and improve standard information resource sharing in big data environment, enhance the competitiveness of enterprises, and realize mutual benefit and win-win situation in “B&R” international cooperation.
The purpose of this study is to explore the mechanism of employee’s voice behavior from the perspective of “leader-employee” power distance orientation. The study found that: (1) employee’s power distance orientation significantly negatively affects employee’s psychological security and employee’s voice behavior; (2) employee’s psychological security significantly positively affects employee’s voice behavior, and it plays a partial intermediary role between employee’s power distance orientation and employee’s voice behavior; (3) leader’s power distance orientation significantly positively affects the employee power distance orientation, and significantly negatively affects the employee’s psychological security and employee’s voice behavior.
An extensive inquisition on service quality has been a significant subject matter for centuries and has now developed in a manner of self-service technology (SSTs). SSTs service quality has a complex influence on the behaviour of customers in terms of interaction with banking organisations that involve activities of M-banking to establish and develop more significant customer satisfaction, loyalty, and service results. This study would like to examine technological based services impact based on SSTs service quality, goal framing theory, and customer loyalty in the M-banking service of a developing country. 698 M-banking’s users have been collected through the online survey. Structural Equation Modelling was applied, and the results indicate positive and significant relationships among proposed indicators, including SSTs service quality, goal framing theory, and customer loyalty. The findings can help the banking industry to improve and provide necessary insights for the Banking industry, especially in the developing country like Thailand.
Small- and medium-sized enterprises (SMEs) face limited resource capability to implement open innovation. Understanding a robust mechanism of knowledge management, organisational structure, and networks can benefit managerial and organisational drivers to achieve open innovation in general. The paper sheds the new light in developing the open innovation implementation as a latent endogenous variable influence inbound OI and outbound OI. We used structural equation modelling (SEM) on a data set of 636 Thai SMEs. The results reveal that open innovation implementation reflected by managerial and organisational dimensions has a positive impact on contributing to both inbound and outbound OI. A key finding is that open innovation’s diffusion helps SMEs to overcome their technological capabilities to implement OI.
The identification is the sole carrier of the whole-process information of the pig traceability system. The front identification is the first component, an indispensible part of the proper traceability of the product. This paper conducts in-depth study on company B, company S and company Z from Beijing, Shandong and Zhejiang to understand their specific management process, cooperation model and interest allocation, identification method, willingness to implement, the cost and benefit before and after the implementation as well as the effect of the implementation. The Cannikin Law is also employed to conduct the comparison analysis on the implementation of the system, so as to set an example for the pig traceability system in other relevant companies of the sort. The results show that, the organization model plays the most important part in the front identification management, with “company + bases + farmers” as the most conducive mode for the implementation of front identification yet not prone to be promoted; “company + cooperative + farmers” is more apt to promotion. Other important impact factors of the implementation level of front identification in pig traceability system include the education level of the implementation subject, the scale and the location of the company.
This article elaborates briefly development of entering and reporting registration system platform according to the requirements of the CAU Library to prevent and control the epidemic COVID-19. The development of the system are extremely significant in supporting the teaching progress of the university and protecting the users on the campus. It has clarified the system development principles and implement methods used in developing the system for facilitating the prevention and control of the epidemic COVID-19 on the campus including good compatibility, comprehensive user management permissions, perfect business processes, multi-mode login, and custom entering record data output. Based on the B/S model, various open source technologies such as LAMP architecture, Bootstrap and LayUI framework, AJAX technology, JSON data exchange format, combined with QR code technology are mainly adopted in developing the system after literature review. The major system functions are realized by five functional modules: user login, application management, QR code management, entering library record management and system management. Each module carries out strict operation control according to different use-permission of users. Compared with the traditional manual record management mode, the research result shows that compared with the traditional manual record management mode, the platform management mode of the library entering and reporting registration system has the advantages of high efficiency, convenience, accuracy and reliability which achieved 100% of the library entrance registration. Because of its strong practicability and high expansibility, it has been widely adopted by other colleges of the university and achieved very good expected results.
The theoretical and practical achievements in domestic studies on data literacy are summarized by bibliometric analysis and network investigation in aspects of the connotation of data literacy, requirements of data literacy, assessment of data literacy and education of data literacy with suggestions proposed for working out the policies of data management and data literacy education, implementing the embedded data literacy education, designing the data literacy teaching contents and constructing the data culture.
Social media data (SMD) is a new data source in disaster research, which can be used in hazard identification, disaster analysis, risk assessment and emergency rescue. This data-driven disaster research needs to find an appropriate method considering the aspect of data sensitivity. So far, the research in this area is focused on the types of hazard, but rarely considers the relationship between the technical methods and applicable tasks. By emphasizing data and method dependencies, we have attempted to summarize the characteristics of SMD in disaster research, viz., “sociality, rapidity, subjectivity, and un-authenticity”, and explore the processing methods in the applications of disaster management. Our work provides ideas and reference to the researchers working in this area from the perspectives of data and research goals.
Weather index insurance plays an important role in helping farmers avoid their economic loss from weather risk. There is increasing numbers of pilot areas of weather index insurance in China while the studies show its take-up has been disappointing low in many other developing countries. This study aims to explore the status of weather index insurance and its processing problems in China through the factors influencing farmers’ willingness to pay for Low-Temperature Index-based Mandarin Orange Insurance in Nangfeng County. The Fuzzy-Set Qualitative Comparative Analysis is conducted for the influencing factors, including strike level, premium, pay-out, planting cost, effect of low temperature, insurance claim process, trust in insurance and government subsidy. The result shows the combination of expensive premium, low payout, high planting cost, low government subsidy and distrust in insurance company causes farmers’ unwillingness to pay for Low Temperature Index-based Mandarin Orange Insurance, among which distrust is core factor. Expensive premium, low payout, high planting cost and low subsidy from government are main influencing factors.
The high global vulnerability revealed by the current pandemic confirms the existence of a very threatening and disruptive environment. The development of new strategies is needed in response to the new shocking global disruptive crisis, analysing the use of new methodologies and digital tools for their early detection and prospective planning. This will allow the development of more proactive, effective, and efficient response plans, with minimal risks. The work considers the convenience of standardized use and optimisation of social welfare functions that integrate social, economic, and ecological variables and indicators, around the achievement of 17 Sustainable Development Goals of the UN 2030 Agenda, and 169 objectives associated with them.
This paper aims to build a conceptual framework for the innovative application in big data in healthcare. Method: Diamond Model and PEST Model were used to analyze the key driving factors of big data in healthcare through external and endogenous driving factors. Based on this, the operation mechanism and possible development model of big data in healthcare were analyzed by using the diffusion theory of policy innovation. Results: The key factors of innovation and application of big data in healthcare are divided into external and endogenous driving factors. The driving mechanism is defined as “learning, compulsion, competition, imitation and inducement”. The conceivable development model is based on big data value innovation and the motivation of different stakeholders. Conclusion: Through the logical analysis of value innovation, the internal relationship among the relevant factors, driving forces and interaction of big data in healthcare application is established, and finally a theoretical analysis framework for innovative application of big data in healthcare is presented.
This paper goal is to present the results the use of patent valuation indicators as alternative data which can generate a value factor which is suitable to design financial products. Based on different patent value indicators which address the areas “assignee”, “technology” and “market” an “IP portfolio index” was designed and backtested with real market data. The outperformance of the IP portfolio index is shown in the current paper.
The sudden emergence of ‘COVID-19’ in 2020 has tightened traffic control in various places, which has posed a huge challenge to the agricultural product supply chain. This research introduces the perspective of supply chain finance, uses in-depth case study methods, and takes Suning’s agricultural supply chain finance as an example to discuss how e-commerce companies relying on big data adopt agricultural supply chain finance practices to promote accurate poverty alleviation. By analyzing Suning’s four agricultural supply chain financial operation models, we find that the internal and external stakeholders of the enterprise are the driving factors for enterprises to adopt agricultural supply chain finance, and the adoption of agricultural supply chain finance measures has brought economic benefits and social benefits to enterprises benefit. Advanced big data tools, fintech and cooperation with other partners are necessary to adopt agricultural supply chain financial measures.
The internalization of family businesses – i.e. of the companies that implement it – can be stimulated by numerous reasons: one of these is linked to the target markets, not in terms of market development, but of resource to be used / exploited. What makes the oil companies distinguishing is that: they follow the territory and the exploitation of the underground resources, wherever they are in the world. In the Italian context, this characteristic of oilfield companies is very noticeable due to the scarcity of underground resources, which characterize our territory. We propose an empirical approach. It has been considered the case of a specific Italian Oil&Gas family firm. The study consists of: a first part, in which an analysis of the main economic and managerial literature, both national and international, was made (on internationalization, SMEs and family businesses, industrial districts, oilfield environment); a second part, in which an empirical analysis was developed: interviews have been conducted with the owners and top management of the company, in order to study and analyze the firm development strategies.
The world is being heavily polluted, which is contributing to many natural disasters. Attempts are being made to come up with innovations that lessen the impact of pollution. Electric cars are one such innovation. Here we investigate the awareness of and decision making about buying electric vehicles among 204 young adults. We propose that consumer decisions related to several factors, which include global warming, air pollution, electric cars, travel and socialization, green self-identity of young adults, and intentions on the use of electric cars. This research was able to show that independent variables can affect consumer awareness and decision making towards the purchase or adoption of electric cars.
Information technology profoundly affects both the teaching and the scientific research activities of the universities and determines their core competitiveness. In recent years, the academic atmosphere construction in universities has increasingly resulted in exposing large number of management problems. Therefore, the application of IT governance is perhaps the only way for the development of informationization in the universities. This paper attempts to integrate IT governance theory into academic atmosphere construction, in a controlled state, by avoiding various risks in the construction process and finally, accomplishes the purpose of informationization construction leading to the reforms in university education system.
E-commerce is an emerging industry. It has brought new opportunities for global economic development. The update of e-commerce technology and the improvement of e-commerce profit models promote the profitability of e-commerce enterprises. Nowadays too much emphasis was placed on theoretical teaching in the e-commerce courses. The courses lack case analysis for learners to better understand the actual situation of e-commerce. This study analyzed the profit model of existing e-commerce companies, and used case analysis methods to find the profit dilemma and effective breakthrough methods for the profitability of two typical B2C e-commerce companies. With disassembling specific e-commerce cases, this study completed the conversion of e-commerce courses from theoretical teaching to case teaching.