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Online video advertisement is a wide-ranging phenomenon on the internet that provides huge opportunities for business enterprises. The revenues of website service providers come primarily from advertisement. However, it is rare to find research focusing on consumer attitudes toward online video advertisement. This study aims to investigate consumer attitudes toward advertisement while they are watching online videos on YouTube.

The paper followed Brackett and Carr’s (2001) Web Advertising Attitudes Model and combined it with the theory of reasoned action (TRA) and the flow theory. This study investigates consideration of the factors affecting attitudes toward advertisement and the influence on shopping intention and purchase behavior.

The findings indicate that entertainment, informativeness, irritation and credibility have a shopping influence on purchase attitudes. Flow, on the other hand, does have an influence on shopping intention and purchase behavior. The discussion and conclusion have been further discussed.

This study provides a comprehensive model for online video advertisement. This model was based on Brackett and Carr’s model, combining the users and gratifications theory, TRA and flow theory to develop an online video advertisement model. Researchers can consider this model as a framework and use it to capture a more complete picture of the relevant phenomena in their works.

The purpose of this paper is to learn more about logistics innovation processes and their implications for the focal organization as well as the supply chain, especially suppliers.

The empirical basis of the study is a longitudinal action research project that was triggered by the practical needs of new ways of handling material flows of a hospital. This approach made it possible to revisit theory on logistics innovation process.

Apart from the tangible benefits reported to the case hospital, five findings can be extracted from this study: the logistics innovation process model may include not just customers but also suppliers; logistics innovation in buyer‐supplier relations may serve as an alternative to outsourcing; logistics innovation processes are dynamic and may improve supplier partnerships; logistics innovations in the supply chain are as dependent on internal stakeholders as on external relationships; and logistics innovation process may start out as a dialectic, conflict ridden process and end up in a well‐ordered goal‐oriented teleological process.

In general, the study contributes to the knowledge base of innovation process in logistics that is still sparse although literature on innovation in many other disciplines is well‐developed. As this research is only one study highlighting a special context of a hospital, further studies on the dynamic logistics innovation processes and their implications for the relevant parties as well as the supply chain are needed. This study does not claim statistical generalizability of the findings but provides insight into complex organizational processes that, for example, surveys cannot.

The findings of the study have provided valuable insights into the process of a logistics innovation in an oriental healthcare supply chain context. The study is, however, still limited in disclosing end‐to‐end supply chain benefits including concrete performance improvements at the suppliers. Examining logistics innovation processes should result not only in the implementation of innovative processes, but also in improved supplier relations leading to improved financial results in the supply chain.

The paper adds to the knowledge of the dynamic processes of logistics innovation both downstream and upstream in a supply chain. It elaborates on an existing model by methodological triangulation in order to learn more about the qualities of actual processes and their implications for theory and practice.

This paper proposes a recommendation method that mines the semantic relationship between resources and combine it with collaborative filtering (CF) algorithm for crowdsourcing knowledge-sharing communities.

First, structured tag trees are constructed based on tag co-occurrence to overcome the tags' lack of semantic structure. Then, the semantic similarity between tags is determined based on tag co-occurrence and the tag-tree structure, and the semantic similarity between resources is calculated based on the semantic similarity of the tags. Finally, the user-resource evaluation matrix is filled based on the resource semantic similarity, and the user-based CF is used to predict the user's evaluation of the resources.

Folksonomy is a knowledge classification method that is suitable for crowdsourcing knowledge-sharing communities. The semantic similarity between resources can be obtained according to the tags in the folksonomy system, which can be used to alleviate the data sparsity and cold-start problems of CF. Experimental results show that compared with other algorithms, the algorithm in this paper performs better in mean absolute error (MAE) and F1, which indicates that the proposed algorithm yields better performance.

The proposed folksonomy-based CF method can help users in crowdsourcing knowledge-sharing communities to better find the resources they need.

This chapter develops a set of two-step identification methods for social interactions models with unknown networks, and discusses how the proposed methods are connected to the identification methods for models with known networks. The first step uses linear regression to identify the reduced forms. The second step decomposes the reduced forms to identify the primitive parameters. The proposed methods use panel data to identify networks. Two cases are considered: the sample exogenous vectors span Rn (long panels), and the sample exogenous vectors span a proper subspace of Rⁿ (short panels). For the short panel case, in order to solve the sample covariance matrices’ non-invertibility problem, this chapter proposes to represent the sample vectors with respect to a basis of a lower-dimensional space so that we have fewer regression coefficients in the first step. This allows us to identify some reduced form submatrices, which provide equations for identifying the primitive parameters.

The COVID-19 pandemic outbreak has created disruptions across the supply chain that are beyond the resources of small and medium-sized enterprises (SMEs) to effectively deal with. This study aims to examine the idea that top managers' business and political ties can play direct roles in enhancing SCR in SMEs during COVID-19 by providing access to valuable resources. The study further investigates integrative capability as an underlying mechanism through which the effects of business and political ties can be transformed into enhanced SCR.

Responses from 217 SMEs in the country of Jordan were received via an online survey. The measurement and structural models were tested using the partial least squares structural equation modelling (PLS-SEM) technique.

The study found that business and political ties are positively related to SCR. However, integrative capability fully mediates the relationship between business ties and SCR, whereas it partially mediates the relationship between political ties and SCR.

The study examined only the direct and indirect impacts of business and political ties on SCR. It could be extended by exploring the conditions under which they influence SCR.

The study explicates the role of top managers' business and political ties on improving SCR in a developing country context. It further examines the mediating role of integrative capability in the relationships between business and political ties and SCR.

The study aims to draw on the self-congruity theory to investigate the relationship among destination personality (DP), self-congruity and tourists’ pro-environmental behavioral intention (BI) among Guangzhou citizens who have experienced nature-based tourism (NBT).

The survey-based quantitative research was divided into two rounds, namely, a preliminary study exploring the dimensions of DP and the verification of whether the DP dimensions that significantly affect pro-environmental BI in step one would be selected for the main research to validate the conceptual model.

The results suggest that wholesome, one of the destination personalities, strongly predicts tourists’ pro-environmental BI, while actual self-congruity plays a mediating role between sincere, another DP, and tourists’ pro-environmental BI.

In practice, it offers multidimensional knowledge and robust evidence-based recommendations for the sustainable development and destination branding of NBT destinations in the post-epidemic era.

The study presents pioneering work that reveals previously underestimated factors influencing pro-environmental BI.

The purpose of this study is to examine the factors that are influential on outward foreign direct investment (OFDI). A sample of four Association of Southeast Asian Nations (ASEAN) countries is compared with dominant Asian economies during 1981-2013.

The authors used time series data for analysis. An econometric model using ordinary least squares, with a series of complementary tests, was estimated for every country to determine the variables affecting OFDI.

The results depict that exchange rates, income and human capital affect the OFDI of most of the countries in the sample. For comparatively advanced and dominant economies (i.e. China, Japan, South Korea and India), openness is the most influential variable, whereas income levels and exchange rates are dominant factors in case of ASEAN economies. Overall, different types of endowments have a different impact for every country.

Previous studies have primarily examined advanced countries’ OFDI. This work adds to the literature by focusing on ASEAN economies and by making a comparison with the dominant Asian economies. Furthermore, the validity and stability of the model is tested with a series of specification tests. In this way, this work is a useful source of information for every stakeholder.

The idea of implementing supply chain management (SCM) principles for the construction industry was embraced by construction stakeholders to enhance the sector's performance. The analysis from the literature revealed that the implementation of SCM in the construction industry enhances the industry's value in terms of cost-saving, time savings, material management, risk management and others. The construction supply chain (CSC) can be managed using the pull or push system. This chapter also discusses the origin and proliferation of SCM into the construction industry. The chapter revealed that the concept of SCM has passed through five different eras: the creation era, the use of ERP, globalisation stage, specialisation stage and electronic stage. The findings from the literature revealed that we are presently in the fourth industrial revolution (4IR) era. At this stage, the SCM witnesses the adoption of technologies and principles driven by the 4IR. This chapter also revealed that the practice of SCM in the construction industry is centred around integration, collaboration, communication and the structure of the supply chain (SC). The forms and challenges hindering the adoption of these practices were also discussed extensively in this chapter.

This study aims to examine the effects of outward foreign direct investment (OFDI) on the home country exports for selected ASEAN countries during 1981-2013.

The authors have used OLS regression based on the unit root analysis, correlation technique and a series of specification tests applied to annual time series data.

The results reveal that the complementary effects of OFDI on exports of the home country outweigh the substitution effects for four ASEAN countries. Furthermore, trade openness, currency fluctuations and inward foreign direct investment (FDI) are also important factors for progressive home country exports.

This study provides a thorough analysis of the links between OFDI and exports of the home country on a macro level. With a data set of more than three decades from the ASEAN region, this study is the first attempt of its kind to analyze the relationship of these two variables on the aggregate level.