Smart Business: Technology and Data Enabled Innovative Business Models and Practices
18th Workshop on e-Business, WeB 2019, Munich, Germany, December 14, 2019, Revised Selected Papers
- 2020
- Book
- Editors
- Karl R. Lang
- Dr. Jennifer Xu
- Bin Zhu
- Xiao Liu
- Michael J. Shaw
- Han Zhang
- Prof. Ming Fan
- Book Series
- Lecture Notes in Business Information Processing
- Publisher
- Springer International Publishing
About this book
This book constitutes revised selected papers from the 18th Workshop on e-Business, WeB 2019, which took place in Munich, Germany, in December 2019.
The purpose of WeB is to provide a forum for researchers and practitioners to discuss findings, novel ideas, and lessons learned to address major challenges and map out the future directions for e-Business. The WeB 2019 theme was “Smart Business: Technology and Data Enabled Innovative Business Models and Practices.”
The 20 papers included in this volume were carefully reviewed and selected from a total of 42 submissions. The contributions are organized in topical sections as follows: crowdfunding and blockchain; business analytics; digital platforms and social media; managing e-Business projects and processes; and global e-Business.
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Table of Contents
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Frontmatter
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Crowdfunding and Blockchain
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Frontmatter
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How Social Networks Dynamics can Affect Collaborative Decision Making on Crowdfunding Platforms
Yanni Hu, Karl LangThis chapter delves into the influence of social network dynamics on collaborative decision-making within crowdfunding platforms. It examines how various network structures, such as null, weak-tie, star, and mesh networks, affect contributors' behaviors and group performance. The study employs an experimental design on Amazon Mechanical Turk, manipulating social network structures and social information sharing to observe their effects on collaboration and contribution outcomes. The findings indicate that network structures significantly impact group performance, with mesh networks demonstrating the highest efficiency and cooperation. The chapter highlights the importance of social identity and social distance in influencing decision-making and collaboration, providing valuable insights for crowdfunding platform designers and marketers.AI Generated
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AbstractDespite the increasing phenomena that social interactions among contributors by emerging technologies influence crowdfunding decision making, little is known about how social network dynamics formed by these social interactions affect contributors’ decision making. Drawing on a data set collected from an economic experiment conducted on Amazon Mechanical Turk (MTurk), we use a social network approach to investigate the effects of social network structure on collaborative decision making under a crowdfunding setting. Comparing four standard network structures – null, star, weak ties, mesh - Our analysis shows that the mesh network yields the best group collaboration performance, with social information displayed. The result of this research provides a specific and nuanced angle of the importance of social networks in emerging technology – enabled online crowdfunding. -
Go in the Opposite Direction? The Impact of Unavailability on Crowdfunding Success
Wanghongyu Wei, Michael ChauThe chapter 'Go in the Opposite Direction? The Impact of Unavailability on Crowdfunding Success' delves into the intriguing effect of unavailability on the success of reward-based crowdfunding projects. It defines unavailability as explicit constraints that limit backers, categorizing it into two dimensions: quantity-based unavailability (restrictions on the number of backers) and time-based unavailability (limits on the funding period). The study argues that while quantity-based unavailability may be perceived as sales tactics, time-based unavailability signals high project quality. The research also highlights the interactive effect of these dimensions, suggesting that time-based unavailability can enhance the credibility of quantity-based signals. Using data from Kickstarter, the study supports its hypotheses through rigorous analysis, contributing valuable insights into backer decision-making processes and the strategic use of unavailability in crowdfunding campaigns.AI Generated
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AbstractReward-based crowdfunding are increasingly playing an important role in raising financial capital for small projects. The most important goal for creators on the platform is to successfully raise enough capital for their projects. Our study aims to provide a new angle to understand backer’s decision-making process on pledging behavior by uncovering how different dimensions of unavailability influence crowdfunding success. By analyzing more than 400,000 projects on Kickstarter, we find that time-based unavailability can indeed improve the possibility of success while quantity-based unavailability has negative impacts. Besides, each dimension of unavailability can influence how individuals interpret other dimension of unavailability by changing the way how individuals receive and process persuasive information. -
The Impact of Blockchain on Medical Tourism
Abderahman Rejeb, John G. Keogh, Horst TreiblmaierThis chapter delves into the transformative potential of blockchain technology in the medical tourism industry. It discusses how blockchain can address key challenges such as information asymmetry, lack of trust, and data fragmentation. By enabling disintermediation, enhancing transparency, and ensuring privacy, blockchain has the potential to revolutionize the way medical tourists access and experience healthcare services. The chapter also highlights the importance of blockchain in facilitating seamless information exchange and improving the overall patient experience. Through its detailed analysis, the chapter offers valuable insights into the future of medical tourism in the digital age.AI Generated
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AbstractMedical tourism has witnessed significant growth over the last decade. This nascent sector creates a new tourist class with access to affordable healthcare services by combining healthcare services with tourism and hospitality. Information technology is an essential factor, which can enable the growth of medical tourism. Technology enables the search process for information about the available services, costs, hospitality, tourism and post-treatment options. However, these technologies are primarily legacy systems and lack interoperability. Several questions arise, including the potential patient-tourist ability to verify crucial factors such as the quality of care and the credentials of the medical professionals and medical facilities. Moreover, questions arise regarding patient-doctor trust, procedure and risk transparency‚ medical record privacy and other health-related hazards in specific procedures. In this conceptual paper, we investigate the potential benefits of Blockchain technology to address some of the open questions in medical tourism. We conclude that Blockchain technology can benefit medical tourism, and we lay the foundation for future research.
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Business Analytics
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Frontmatter
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Creating a Data Factory for Data Products
Chris Schlueter Langdon, Riyaz SikoraThe chapter 'Creating a Data Factory for Data Products' delves into the burgeoning business of data, emphasizing its potential as the 'next big business.' It explores the challenges in data monetization and the overwhelming time spent on data wrangling, highlighting the need for a more automated approach. The solution proposed is the creation of a 'data factory,' drawing parallels with Henry Ford's industrialization of auto manufacturing. This data factory framework aims to standardize and automate data refinement processes, ensuring data is 'AI-ready' and compliant with regulations like GDPR. The chapter also discusses the emerging trends in data governance and the importance of data sovereignty, providing a holistic view of the data ecosystem. The proposed framework, backed by case studies and systematic literature reviews, offers a practical guide to transforming raw data into valuable products, paving the way for more efficient and scalable data analytics.AI Generated
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AbstractData is seen as the next big business opportunity. From a demand side, the popularity of artificial intelligence (AI) is growing and particularly deep learning requires large amounts of data. From a supply side, new technology, such as Internet of Things (IoT) sensors and 5G mobile communications, will greatly expand data generation. However, data has remained a challenge. In data analytics companies are struggling with too much time spent on data preparation. As of today, data preparation for analytics has largely remained handmade and made-to-order like cars before Henry Ford industrialized the auto business through productization of cars and parts, and factory automation. Similarly, for data analytics to become a bigger business, data has to be productized. First “data factories” are emerging to create such data products economically. This article introduces a framework to guide construction of a data factory: What are the key modules, why are they important, how is best practice evolving? The article is building on (a) a foundation and in-depth case studies in the literature, (b) current meta research and systematic literature reviews (SLRs), and (c) our own observations building a data factory. This real-world application uncovered the important additional steps of data rights management and data governance that may be less obvious from a computer science perspective but critically important from a business and information systems view. -
An Empirical Investigation of Analytics Capabilities in the Supply Chain
Thiagarajan Ramakrishnan, Abhishek Kathuria, Jiban KhuntiaThe chapter delves into the empirical investigation of analytics capabilities within the supply chain, focusing on the strategic alignment of these capabilities with business strategies and value-chain activities. It introduces a conceptual model that links supply chain analytics modularity and governance to analytical capabilities, emphasizing the importance of a standardized and loosely coupled modular analytics architecture. The study, based on primary survey data from over 100 firms in India, supports the hypotheses that modularity and governance significantly influence supply chain analytics capabilities. The research methodology includes a cross-sectional matched-pair field survey, highlighting the relevance of the Indian manufacturing sector as a growing and under-researched domain. The chapter concludes with a detailed assessment of the measurement and structural models, providing valuable insights into the practical implementation of supply chain analytics.AI Generated
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AbstractThis study conceptually develops the construct of Supply Chain Analytics Capability. Preliminary analysis of survey data collected from more than 100 firms in India supports several hypotheses relating supply chain analytics architecture modularity and decentralized governance, in a moderating manner, with Supply Chain Analytics Capability. The capability creation path model suggested in this study establishes the antecedents of Supply Chain Analytics Capability and is helpful to firms seeking to develop such a capability. -
Finding Real-Life Doppelgangers on Campus with MTCNN and CNN-Based Face Recognition
Jingjing Ye, Yilu ZhouThe chapter delves into the use of MTCNN and CNN-based face recognition to identify doppelgangers on a university campus, drawing inspiration from photographer François Brunelle's work. The study highlights the potential of technology in creative art and presents an exhibition to inspire cross-disciplinary research. The methodology involves a four-phase framework: face detection, face alignment, face recognition, and similarity computation. The experiments validate the face recognition model using a labeled dataset and demonstrate the effectiveness of the doppelganger mining algorithm on an unlabeled dataset of over 3,000 student photos. The chapter concludes with the identification of true doppelgangers and plans for an exhibition to mimic Brunelle's photography.AI Generated
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AbstractFace recognition has been widely used in areas such as security informatics, forensic investigation, customer tracking and mobile payment. This project is inspired by a photography artwork by Francois Brunelle, where he spent 12 years tracking people who are completely strangers but lookalikes, or doppelgangers. We aim to use face recognition techniques to mine doppelgangers on a school campus. We developed a face processing system which includes four steps, face detection, image processing (alignment and cropping), feature extraction and classification. We trained Multi-task Cascaded Convolutional Networks (MTCNN) and traditional CNNs with joined softmax loss and Center Loss on the Caffe framework. Finally, cosine similarity is used to detect similar faces. By exhibiting the results, we demonstrate the potential to adopt CV technology in art-related domains, in this case mimicking a photographer’s human eyes. This project provides an example for cross-disciplinary study between art and technology and will inspire researchers from both domains to establish further collaboration channels. -
Time Series Analysis of Open Source Projects Popularity
Shahab Bayati, Marzieh HeidaryThis chapter delves into the time series analysis of open source projects' popularity, leveraging data from GitHub to identify the most effective socio-technical attributes that influence project success. By focusing on the 'Watching' event as a measure of popularity, the study applies dynamic time wrapping clustering and random forest analysis to uncover the key factors driving project trends. Notably, the study highlights the importance of forking, commits, and issue comments in determining project popularity. Additionally, the chapter employs various machine learning techniques to predict project popularity trends, with C4.5 demonstrating the highest accuracy. This comprehensive analysis provides valuable insights into the dynamics of open source project success, making it a must-read for professionals interested in open source software development and data-driven decision-making.AI Generated
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AbstractOpen source software (OSS) community relies on volunteers and developers contributions for its survival. However, only a few projects reach success and popularity in open source community. Then, it is important to know the success factors of OSS projects. In this paper, we have applied time series clustering on open source projects hosted on a social coding platform to understand the main effective attributes of an OSS project on its popularity trends. We have applied exploratory data analysis on each cluster to see the effect of projects’ performance and attributes on projects’ reputation inside the OSS community. Finally, we have applied machine learning techniques to predict the popularity trend of OSS projects. Having access to the social coding data expands our view on project popularity on both social and technical factors. Results of this empirical study can help project owners and members to manage and promote the project reputation.
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Digital Platforms and Social Media
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Frontmatter
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Social Media or Website? Research on Online Advertising Type Based on Evolutionary Game
Xiang He, Li Li, Hua Zhang, Xingzhen ZhuThe chapter delves into the effectiveness of online advertising through website and social media channels, highlighting the challenges advertisers face in balancing consumer acceptance and rejection. By employing evolutionary game theory, the study develops a model that incorporates persuasive knowledge and attention cost, providing a comprehensive analysis of consumer and advertiser behaviors. The research fills gaps in existing literature by focusing on the dynamic interplay between channels and consumer actions, offering valuable insights for marketing managers and advertising specialists.AI Generated
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AbstractChoosing an online advertising channel to maximize the benefit of advertisement has become a main topic for advertisers. This paper constructs a model to describe an evolution process, which includes attention cost and persuasive knowledge of consumers. The results show that attention cost paid by consumers and the persuasive knowledge activated by advertisements may have an important impact on the evolutionary results. Specifically speaking, the model will eventually restrain to social media channel because of the higher attention cost paid by consumers and lower persuasive knowledge activated by advertisement; on the contrary, the model will eventually restrain to website channel because of the lower attention cost paid by consumers and higher persuasive knowledge activated by advertising. Furthermore, the model also suggests that the browsing probability of channel would adjust the evolutionary results. The reliability of conclusions is further verified by an example. -
Platform Discount Deciding, Seller Pricing and Advertising Investment in the Shopping Festival Based on Two-Sided Market Theory
Hua Zhang, Li Li, Xiang He, Xingzhen ZhuThe chapter delves into the complexities of online shopping platforms' strategies during Shopping Festivals, such as Amazon’s 'Black Friday' and Taobao’s 'Double 11'. It examines how platforms use discounts to attract both sellers and buyers, leveraging two-sided market theory. The study models the interactions between platforms and sellers, considering factors like seller pricing, advertising investment, and consumer behavior. It offers valuable insights into how platforms can optimize their discounts and seller strategies to maximize profits and transaction volumes during these high-stakes events. The analysis also highlights the importance of understanding consumer utility and the impact of logistical challenges during these festivals. By presenting a detailed game-theoretic model, the chapter provides actionable recommendations for platforms to enhance their market efficiency and profitability.AI Generated
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AbstractThe online shopping platform, known as a two-sided market with buyers and sellers, always sponsor a Shopping Festival, such as Amazon “Black Friday”, Taobao “Double 11”. In this paper, a Stackelberg game model is constructed to study the platform discount deciding, seller pricing and advertising investment in the Shopping Festival. The research results show that (1) the optimal discount of the platform is related to the product buyer utility and unit cost. The higher the buyer utility of the product is, the larger the optimal discount coefficient of the platform is. The higher the unit cost of the product is, the larger the optimal discount coefficient for the platform is. (2) The platform profit increases in the number of buyers and the buyer utility of the product, and the profit increases in the platform transaction rate and the advertising cost coefficient firstly and then remains unchanged. (3) When the discount is more, seller’s optimal pricing remains unchanged, and the advertising investment level reduce with the decrease of the platform discount coefficient. When discount is less, seller’s optimal product pricing decreases in the decrease of the discount coefficient, but the advertising investment level remains unchanged. -
Who Picks Cherries? Understanding Consumers’ Cherry Picking Behavior in Online Music Streaming Services
Changkeun Kim, Byungjoon Yoo, Jaehwan LeeThe chapter delves into the phenomenon of 'cherry picking' in online music streaming services, where customers exploit promotional deals and then switch services. It examines the characteristics of cherry pickers, who use these services more actively but invest less time and effort compared to non-cherry pickers. The study is based on data from a music streaming service in South Korea, testing hypotheses about usage and investment behaviors. The chapter also introduces a prediction model to identify cherry pickers, offering valuable insights for marketing strategies in the subscription economy. By understanding cherry picking behavior, service providers can better manage promotional strategies and customer retention.AI Generated
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AbstractSubscription business model is common in many online services. It is crucial to service providers to acquire and retain more customers. Because customers can switch one service to another easily, price promotion may cause economic loss of the providers. The aim of this paper is to investigate the characteristics of cherry pickers in subscription-based online services. We find that cherry pickers use online music streaming services more actively and apply their investment to the service more readily than non-cherry pickers. -
The Value of Free Content on Social Media: Evidence from Equity Research Platforms
Tianyou Hu, Arvind Tripathi, Henk BerkmanThis chapter delves into the significance of free content on equity research platforms, specifically Seeking Alpha, in predicting market returns. It analyzes the impact of sentiments expressed in free articles on stock abnormal returns, with a particular focus on how the market cap of the stocks influences this relationship. The study finds that free articles are more valuable for predicting returns of small-cap stocks compared to large-cap stocks. Additionally, it highlights the slower pace at which the abnormal performance predicted by these articles is reflected in the market. The research contributes to the understanding of how social media sentiments affect stock returns, offering insights that could be valuable for investors and financial analysts.AI Generated
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AbstractThe effect of social media sentiments on stock market returns is well-established. However, the quality of content and expertise of content creators vary on social media platforms, and the stocks vary in characteristics. In this research, we examine the effect of sentiment expressed in free content from a social media platform on stock abnormal returns. We also examine the moderating effect of the market capitalisation of stocks on the strength of this relationship. Using data collected from a well-known equity research platform, we demonstrate that the size of the market cap plays an important role in this relationship. The smaller the market cap, the higher the predicting power of the social media sentiment on stock abnormal returns. Considering different holding periods from 1 month to 1 year, we show that sentiments from social media have a long wear in effect on stock abnormal returns. Our results shed light on the importance of market cap and holding period when studying the effect of social media sentiments on stock market returns.
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Managing e-Business Projects and Processes
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Frontmatter
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Managing Cloud Computing Across the Product Lifecycle: Development of a Conceptual Model
Timo Puschkasch, David WagnerThe chapter 'Managing Cloud Computing Across the Product Lifecycle: Development of a Conceptual Model' delves into the strategic importance of cloud computing in digital product development. It introduces a novel conceptual model that maps the benefits of cloud computing to the different stages of the product lifecycle, addressing challenges such as uncertainty, competition, and market saturation. By analyzing the applicability of various cloud deployment models—private, community, public, and hybrid—the chapter offers a comprehensive framework for IT managers and product developers to optimize resource allocation and reduce costs. The model is designed to guide decision-making throughout the product lifecycle, from introduction to decline, ensuring that digital products are effectively supported by the most suitable cloud infrastructure. This innovative approach not only contributes to academic discourse but also provides practical value for professionals seeking to leverage cloud computing strategically.AI Generated
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AbstractCloud computing has become an important part of IT infrastructure for both small companies and large enterprises over the last years. More organizations than ever consider it an enabler for their efforts in making IT more agile, reducing operating costs and gaining access to new technologies that will give them an edge over their competitors. In this paper we develop a conceptual model to explain the benefits of using cloud computing for delivering a digital product across several stages of its product lifecycle, emphasizing the importance of the four delivery models: public, private, community and hybrid cloud. While this distinction is theoretically novel and helps IS scholars to gain a more nuanced understanding of cloud computing in the enterprise, it provides practitioners with a decision frame to select the most effective mode of cloud computing given the specific lifecycle stage of their digital product. Ultimately, we discuss limitations of this approach and provide directions for future research. -
Antecedents of Different Social Network Structures on Open Source Projects Popularity
Shahab Bayati, Arvind TripathiThe chapter investigates the antecedents of different social network structures on the popularity of open source projects. It introduces the concept of following networks as a more realistic measure of developers' interactions compared to traditional affiliation networks. The study compares the effects of both network types on project popularity and examines how changes in these networks influence project success over time. By applying social network theory, the research provides new insights into the dynamics of open source project communities and the factors that drive project popularity.AI Generated
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AbstractAs Open source software (OSS) phenomenon become popular, it attracts millions of developers and plays a key role in success of small and large businesses. However, OSS ecosystem is very competitive and so only a few OSS projects, among millions hosted on social coding platforms such as GitHub, become successful. Since popular projects attract more developers, a key success ingredient, this research examines the antecedents of popularity of OSS projects hosted on a social coding platform. We have investigated the effect of the social structure of an OSS project on project popularity among community members. Data from GitHub is used to construct two different types of social networks for each project. The affiliation network represents the developers’ inter-project relationships and following network reveals intra-project relationship. Applying the lenses of social network theory, we examine the effect of embeddedness and cohesion of the project’s contributors on project popularity. Our results show that both affiliation and following networks are different in how they evolve and affect project popularity. Our findings can help OSS project leaders to understand developers’ interactions and its effect on popularity of the project. -
Language Alternation in Online Communication with Misinformation
Lina Zhou, Jaewan Lim, Hamad Alsaleh, Jieyu Wang, Dongsong ZhangThe chapter delves into the intricate relationship between language alternation and online misinformation, focusing on the behaviors of English as a second language speakers. It examines the motivations behind language alternation in misinformation communication, such as power of persuasion and self-protection. The study also reveals that speakers of English as a second language are more likely to be targeted by misinformation involving language alternation compared to native English speakers. The findings offer valuable insights into the detection and understanding of online misinformation, highlighting the importance of language alternation in the digital age.AI Generated
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AbstractMisinformation has attracted widespread research attention owing to the importance and challenges of addressing the problem. Despite the progress in developing computational methods for misinformation detection and identifying psycholinguistic factors and network properties of misinformation, there is a lack of understanding of language alternation in online misinformation communication. This research aims to address the literature gap by answering several key questions regarding language alternation in communicating misinformation online. Based on the analysis of structured and un-structured survey responses, the results of this study show that it is fairly common for speakers of English as a second language to alternate languages in communicating misinformation online. In addition, it identifies the motives and impacts of such behavior. The findings of this study point to a new avenue for addressing the challenges of detecting online misinformation. -
A Taxonomy of User-Generated Content (UGC) Applications
Tien T. T. Nguyen, Arvind TripathiThe chapter introduces a taxonomy of user-generated content (UGC) applications, focusing on their usage and effectiveness. It defines UGC applications as the means by which UGC is utilized in various contexts, such as improving product search, estimating trading risk, and seeking support in critical situations. The taxonomy is developed through a systematic literature review, identifying 109 applications across 96 peer-reviewed journals. The methodology follows a validated process for taxonomy development in information systems, involving iterative steps to determine meta-characteristics, ending conditions, and characteristics of UGC applications. The resulting taxonomy includes dimensions such as beneficiary, UGC source, multiplicity, gratification, data approach, operating complexity, and false information existence. The chapter evaluates the taxonomy's efficacy and discusses its implications for researchers, managers, and practitioners, highlighting its potential to serve as a descriptive and predictive instrument for future studies and projects.AI Generated
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AbstractUser-generated content (UGC) has become well-known in the online context. Previous scholars have investigated UGC in terms of its helpfulness and utilization. Through the study of UGC and its applications, various practical implications including consumer behavior learning, IT system innovation, product search enhancement, user’s value extraction, economic performance evaluation, and other applications have been ascertained and discussed. Until today, the applications of UGC are rapidly evolving. However, there has been little research into how UGC differently applied and operated. Also, little guidance is available for managers and researchers to recognize and compare the applications of UGC between and among the others. This study strives to fulfill the needs of further investigation on UGC applications regarding theory and conceptualization by developing a well-structured taxonomy of UGC applications. Because a taxonomy of UGC applications potentially enables the understanding of the science behind UGC. Eventually, understanding the insight of UGC provides the potential identification of the embedded UGC theories.
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Global e-Business
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Influence of Ownership and Management on IT Investment in Indian Family Firms
Xue Ning, Prasanna Karhade, Abhishek Kathuria, Jiban KhuntiaThe chapter examines the influence of ownership and management on IT investment in Indian family firms, a significant segment of the global economy. It introduces the socioemotional wealth perspective to explain the strategic behavior of family-owned firms, emphasizing the preservation of noneconomic endowments. The study also integrates organizational control theory to understand how management control influences IT investment decisions. The authors propose three hypotheses: family ownership negatively impacts IT investment, family management worsens this negative effect, and professional management weakens it. The preliminary analysis, conducted on a sample of 2,148 Indian family firms, supports these hypotheses, offering valuable insights into the complex dynamics of IT investment in family businesses.AI Generated
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AbstractSeveral questions relevant to IT investments by family firms remain unanswered, such as, how family ownership influences a firm’s IT investment and how the management type, including family management and professional management, further influences the family ownership and IT investment relationship. This study proposes several testable hypotheses, that can be investigated with data. A set of preliminary analysis using family firms’ data from India suggest that family ownership is negatively related to IT investment. Furthermore, family management and professional management controls have different moderating effects on family ownership and IT investment relationship. -
Controlling Risk from Design Changes in Chinese Prefabricated Construction Projects: An Empirical Investigation
Juan Du, Jiajun Zhang, Yifei Gu, Vijayan SugumaranThe chapter delves into the complexities of design change risks in Chinese prefabricated construction projects, highlighting the advantages of prefabricated construction over traditional methods. It identifies key risk events and influencing factors through a comprehensive survey and structural equation model analysis. The research then proposes targeted management strategies based on the priority of these factors and project characteristics. The empirical methodology and detailed risk factor analysis make this chapter a valuable resource for professionals seeking to optimize risk management in prefabricated construction projects.AI Generated
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AbstractIndustrialization and standardization of prefabricated construction has brought reform and improvements to the construction industry and has changed the traditional construction mode. Prefabricated construction reduces labor demand and environmental pollution, which is in response to the government’s “low-carbon environmental protection, green industry” call. Prefabricated projects, while improving engineering quality and work efficiency, also entail complexity and uncertainty. The development of industrialization projects in China still lags behind, and many risks restrict the development of successful prefabricated projects. This paper focuses on the specific problem of design change risk, and uses an empirical study to study the impact of design change risk factors, identify and prioritize them for different design change risk events. We also propose specific management strategies accordingly. -
AHP-FCE Evaluation of Cross-Border e-Commerce Supply Chain Performance for Xi’an International Inland Port
Guo-Ling JiaThis chapter delves into the evaluation of Xi’an International Inland Port’s cross-border e-commerce supply chain performance using the AHP-FCE method. It begins by contextualizing the growth and significance of China’s CBEC industry, with a particular focus on Xi’an International Inland Port’s role as a key player. The chapter then outlines the methodology, combining Analytic Hierarchy Process (AHP) for indicator weight allocation and Fuzzy Comprehensive Evaluation (FCE) for evaluation. The AHP-FCE method is chosen for its ability to handle the complex and uncertain nature of the CBEC supply chain. The chapter also provides a detailed comparison of common evaluation methods and explains the construction of the bipartite judgment matrix and consistency check process. The findings of the evaluation offer practical implications for improving the port’s CBEC supply chain service, making this chapter a valuable resource for professionals seeking to optimize cross-border e-commerce operations.AI Generated
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AbstractCross-border E-commerce has gained great development with the support of Xi’an international inland port. It is significant to evaluate the supply chain performance to promote the better development. The combination of Analytical Hierarchy Process and Fuzzy Comprehensive Evaluation is introduced to carry out the evaluation. Results show that the satisfaction is relatively high and there still is some room for the Xi’an international inland port to improve the supply chain performance, mainly concentrating on supply chain responsiveness and logistics service. -
Knowledge Domain and Emerging Trends in Cross-Border E-commerce Coordination Mechanism Based on CiteSpace Analysis
Shan Du, Hua LiThis chapter delves into the knowledge domain and emerging trends in cross-border e-commerce coordination mechanisms, leveraging CiteSpace analysis to uncover key insights. It examines the rapid growth of cross-border e-commerce, which has reached 6.4 trillion USD and accounts for 18.5% of China’s import and export trade. The study identifies potential improvements in logistics, storage, payment systems, policy, and talent management within the industry. The Belt and Road Initiative (BRI) is highlighted as a significant factor influencing the complexity of cross-border trade, with firms responding in ways that could define future winners and losers. The chapter presents a systematic review of the literature, using CiteSpace to visualize trends and identify critical turning points. It maps out the most productive authors, countries, institutions, keywords, and references, revealing that cross-border logistics and consumer behavior are hot research topics. The analysis also uncovers constraints such as technical problems and the need for more artificial intelligence integration. The chapter concludes by outlining future research directions, emphasizing the importance of infrastructure improvement and comprehensive supply chain supervision in the context of the BRI.AI Generated
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AbstractWith the advance of One Belt and One Road initiative (BRI), cross-border e-commerce has experienced rapid growth and needs urgent attention from researchers. We analyze the literature from the SCI-EXPANDED, SSCI, CPCI-S, CPCI-SSH database on cross-border e-commerce coordination mechanism to find the knowledge domain and emerging trends in the new background. In order to help researchers and practitioners grasp the research frontier in this field quickly. We develop a framework of cross-border e-commerce coordination mechanism by analyzing the most influential authors, institutions, countries, keywords and references. We apply knowledge mapping cluster view to our study. Frequency statistics, clustering coefficient as well as centrality calculation are employed to analyze by CiteSpace. We use the strength of citation bursts to analyze keywords and present the major clusters to reveal their associated intellectual bases. In this study, we explore the knowledge structure, development and the future trend of cross-border e-commerce coordination mechanism for researchers. We identify the main technology and models to improve cross-border e-commerce participant satisfaction.
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Backmatter
- Title
- Smart Business: Technology and Data Enabled Innovative Business Models and Practices
- Editors
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Karl R. Lang
Dr. Jennifer Xu
Bin Zhu
Xiao Liu
Michael J. Shaw
Han Zhang
Prof. Ming Fan
- Copyright Year
- 2020
- Publisher
- Springer International Publishing
- Electronic ISBN
- 978-3-030-67781-7
- Print ISBN
- 978-3-030-67780-0
- DOI
- https://doi.org/10.1007/978-3-030-67781-7
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