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A number of literature contributions have underlined the importance of developing value-added logistics activities or VALS in order to help improve customers’ satisfaction. However, there is usually very little attention given regarding where to perform these VALS. This study aims to: (1) identify a comprehensive set of factors which may influence the location of VALS, (2) to analyze to what extent those factors influence location decisions, and (3) to distinguish the determinants behind the location choices for distribution centers and for the kind of VALS that will be developed in these distribution centers.

In this paper, we will present a conceptual framework on the locations of VALS in view of the identifying determinants for assigning VALS to logistical centers. We argue that the optimal location of VALS is determined by complex interactions between the determinants at the level of the choice of a distribution system, distribution center location factors, and different logistical characteristics regarding products.

Gifting is a typical monetization strategy for live streaming platforms to motivate providers’ live content contribution. However, research regarding the factors that affect individuals’ gifting intention is still at an infant stage. Therefore, this study aims to investigate the factors that affect individuals’ gifting intention during live streaming.

The authors build a model to uncover the factors that affect individuals’ gifting intention from a streamer–content perspective, and the hypotheses are largely validated by online survey data through structural equation model analysis.

Individuals’ perceived attractiveness of the streamers is significantly and positively associated with gifting intention for leisure-related live streaming, whereas individuals’ perceived similarity with the streamers is significantly and positively associated with gifting intention for leisure-related and non-leisure-related live streaming. For live content-related factors, the individuals’ perceived utilitarian value of content is significantly and positively associated with gifting intention for non-leisure-related live streaming, whereas the individuals’ perceived hedonic value is significantly positively associated with gifting intention for leisure-related live streaming. Perceived symbolic value is insignificantly associated with gifting intention for neither type of live streaming.

The research is an original work and significantly contributes to live streaming and PWYW literature, and the findings derived from this study can guide live streaming platforms to regulate individuals’ gifting intentions/behaviors better.

Social shopping website (SSW) introduce the social side into the shopping process, thus making “window” shopping or browsing more interesting for customers. The purpose of this paper is to investigate customer online browsing experience and its antecedents (i.e. information quality and social interaction) and consequences (i.e. urge to buy impulsively and continuous browsing intention) in the context of SSW.

A survey questionnaire was distributed to visitors of online SSW to collect data, and partial least squares technology was used to test the research model.

The results of this study reveal that three types of web browsing, namely, utilitarian browsing, hedonic browsing and social browsing, take place in a SSW. The unique factors of SSW, namely, the quality of user generated contents and social interaction are critical for facilitating customers’ browsing experiences. Furthermore, the findings reveal that hedonic browsing experience is found to be the most salient factor influencing customers’ urge to buy impulsively and continuance intention.

The findings suggest that practitioners, such as designers and managers of SSW should give special attention to the benefits of browsing activity to convert web browsers into impulse purchasers and increase customers’ loyalty. Moreover, they should focus on improving the quality of user generated content and pay more attention to support and encourage social interaction to enhance browsing experiences on a SSW.

Existing studies about browsing behavior mostly focus on traditional online e-commerce website. This study represents the first step toward understanding browsing activity on SSW. Moreover, prior studies mainly focused on utilitarian and hedonic browsing experience; however, there is a lack of research on social browsing experience. The current study attempts to fill this research gap.

The main purpose of this study is to reveal how the China factor influences Taiwan voters' evaluations of the two major parties across elections and generations. We contend that 1) elderly Taiwan voters may take the China factor more seriously than younger cohorts, and 2) China factor may be weighted differently depending on the levels of elections. More importantly, we argue that the China factor is tangled with voters' partisanship.

Data gathered from 2008 to 2014 Taiwan's Election and Democratization Study (TEDS) enable in investigating the influence of the China factor on Taiwan people's vote choices in the two local and two presidential elections. To answer the research question, this study applies issue voting theory and the seemingly unrelated regression (SUR) employed for empirical investigations.

The findings of this study provide empirical evidence on how political generations have changed their reactions to China in Taiwan's elections. The fundamental variables, party identification and the China issue are still very important and cannot be disregarded. Specifically, the China factor played a quite influential role in the Democratic Progressive Party (DPP) supporters' voting decisions regardless of their generations, whereas its effect on the Kuomintang (KMT) supporters' voting decisions varies depending on electoral contexts and generations.

While some scholars might suspect that the single item is not sufficient to be an effective predictor of vote choice, we contend that the China factor is definitely the most significant component in Taiwan's elections, especially when it is tangled with partisanship. The SUR approach in this study confirms that partisanship and the China factor cannot be viewed separately.

Online social networks are increasingly important venues for businesses to promote their products and image. However, information propagation in online social networks is significantly more complicated compared to traditional transmission media such as newspaper, radio, and television. In this chapter, we will discuss research on modeling and forecasting diffusion of virally marketed content in social networks. Important aspects include the content and its presentation, the network topology, and transmission dynamics. Theoretical models, algorithms, and case studies of viral marketing will be explored.

This study aims to investigate the factors driving viewers' purchase intention in live-streaming by incorporating stimuli–organism–response (S–O–R) framework and extroversion–introversion personality perspectives.

Data collected from 228 users on live-streaming platforms in Taiwan were used to test the proposed model. The partial least squares method was used to test the measurement and the structural models.

Product attractiveness and trust in streamer significantly impacts purchase intention. The results also reveal that interactivity, breadth of information and uniqueness of information significantly impact product attractiveness, whereas social presence, breadth of information and uniqueness of information positively affect trust in streamer. Furthermore, streamer attractiveness has a greater effect on the purchase intention of extroverts.

This study investigates how the features of media, message and streamer impact purchase intention through their reactions to live-streaming. This research is also one of the earliest studies to examine the moderating role of extroversion–introversion personality on purchase intention and its antecedents in live-streaming commerce.

The purpose of this paper is to propose a fault diagnosis method for rolling bearings, in which the fault feature extraction is realized in a two-dimensional domain using scale invariant feature transform (SIFT) algorithm. This method is different from those methods extracting fault feature directly from the traditional one-dimensional domain.

The vibration signal of rolling bearings is first transformed into a two-dimensional image. Then, the SIFT algorithm is applied to the image to extract the scale invariant feature vector which is highly distinctive and insensitive to noises and working condition variation. As the extracted feature vector is high-dimensional, kernel principal component analysis (KPCA) algorithm is utilized to reduce the dimension of the feature vector, and singular value decomposition technique is used to extract the singular values of the reduced feature vector. Finally, these singular values are introduced into a support vector machine (SVM) classifier to realize fault classification.

The experiment results show a high fault classification accuracy based on the proposed method.

The proposed approach for rolling bearing fault diagnosis based on SIFT-KPCA and SVM is highly effective in the experiment. The practical value in engineering application of this method can be researched in the future.

This paper examines the impact of residents’ human capital investment inequality on the urban–rural income gap, using China’s provincial panel data from 1997 to 2013. The results show that, at the national level as well as at the regional level, residents’ overall human capital investment inequality has a positive significant impact on the urban–rural income gap. In addition, the impact of overall human capital investment inequality increased monotonically from the eastern region inward to the western region. In terms of the relative impact of each component of human capital investment inequality on the urban–rural income gap, migration investment inequality appears to have the greatest impact at the national level, whereas health investment inequality has the greatest impact on the urban–rural income gap in the eastern region, and education investment inequality exhibits the greatest impact in the central and western regions. We also investigate the impact of human capital investment inequality on the urban–rural income gap over different periods. The results show that residents’ overall human capital investment inequality had a positive impact on the urban–rural income gap in the period 1997–2008, but the impact rapidly shrunk in 2009–2013. Furthermore, the impact of residents’ health investment inequality on the urban–rural income gap shows a downward trend, and the impact of residents’ education investment inequality trended slightly upward from 1997 to 2008, and then rapidly shrunk in 2009–2013. Finally, the impact of residents’ migration investment inequality was only significant in 1997–2002.

This chapter explores the significance of blockchain technology in protecting data for intelligent applications across various industries. Blockchain is a distributed ledger that ensures the immutability and security of transactions. Given the increasing need for security measures in industries, understanding blockchain technology is crucial for preparing for its future applications.

This chapter aims to examine the use of blockchain technology across industries and presents a compilation of existing and upcoming blockchain technologies for intelligent applications. The methodology involves reviewing research to understand the security needs of different industries and providing an overview of methods used to enhance multi-institutional and multidisciplinary research in areas like the financial system, smart grid, and transportation system.

The findings highlight the benefits of blockchain networks in providing transparency, trust, and security for industries. The Responsible Sourcing Blockchain Network (RSBN) is an example that utilizes blockchain's decentralized ledger to track sustainable sourcing from mine to final product. This information can be shared with auditors, corporate governance organizations, and customers.

The practical implications of this chapter are significant, serving as a valuable resource for industries concerned with identity privacy, traceability, immutability, transparency, auditability, and security. Understanding and implementing blockchain technology can address the growing need for secure and intelligent applications, ensuring data protection and enhancing trust in various sectors.

How to make an effective use of building information modeling (BIM) for information management (IM) is a challenging question in the field of construction project and asset management. Chen et al. (2015) answered this question by developing a conceptual framework of “bridging BIM and building (BBB).” However, the underlying mechanism through which BBB can truly impact IM remains unclear. The purpose of this paper is thus to demystify the mechanism linking BBB and IM.

Drawing upon the IM literature, this paper proposes three IM requirements, namely, requirements on information quantity, quality and accessibility, as the significant mediators between BBB and IM. To verify this proposition, a two-year, participatory case study was conducted based on a real-life construction project in which a BBB system was implemented.

The results of the case study supported the proposition that by enhancing the information quantity, quality and accessibility BBB could favorably contribute to IM in construction.

This paper provides knowledge about system architecture, components and their linkage in an operable BBB system. It also provides empirical experience about BBB implementation.

This study is among the first attempts to streamline the theoretical discourses relating to BBB for IM in a construction context. It contributes to the construction IM by directing attention to key IM requirements and processes rooted in the IM literature.