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This paper applies the decomposition method proposed by Wang et al. (2013), together with the multi-national input-output tables from World Input-Output Database (WIOD) to estimate the value-chain transition in East Asian production network. Specifically, we calculate and examine the domestic value-added absorbed abroad, foreign value-added embodied in country’s gross exports, and vertical specialization measures to explore the relative positions of major East Asian countries in the global production chain over the period of 1995-2011. The analyses are at country-aggregate, country-sector, bilateral-aggregate and bilateral-sector levels. Based on our results, we answer the important question of whether Taiwan and South Korea have used China’s production chains as an intermediary to re-export their products to other countries in the world. Furthermore, we answer the question that over the 1995-2011 periods, have Taiwan and South Korea exploited cheap labor from China to add value to their products before re-exported them to the rest of the world?

The way to measure the value of an enterprise’s R&D investments remains elusive for theoretical and empirical study on innovation economics. The paper aims to discuss this issue.

This paper expands the asset-value model pioneered by Griliches (1981) and applies it for the first time to the Chinese stock market to calculate the value of R&D investment instilled by Chinese manufacturing listed companies (CMLCs) from 2003 to 2014.

The authors find that: the assets-value model can better explain the enterprise value composition of CMLCs; with equal input, the value of R&D is higher than that of tangible assets, and lower than that of organizational assets; compared with the developed countries, the R&D value of CMLCs is lower; and the R&D value of CMLCs saw a downward trend from 2007 to 2014.

Furthermore, by rationally estimating the value of organizational assets and non-tradable shares, and innovatively introducing semi-annual momentum indicators from the perspective of behavioral finance to control the influence of investor sentiment on enterprise value, this paper tries to develop the asset-value model and provides a feasible solution to the problem of measuring the value of Chinese enterprises’ R&D investment.

Organizations across industries are increasingly using Artificial Intelligence (AI) systems to support their innovation processes, supply chains, marketing and sales and other business functions. Implementing AI, firms report efficiency gains from automation and enhanced decision-making thanks to more relevant, accurate and timely predictions. By exposing the benefits of digitizing everything, COVID-19 has only accelerated these processes. Recognizing the growing importance of AI and its pervasive impact, this chapter defines the “social value of AI” as the combined value derived from AI adoption by multiple stakeholders of an organization. To this end, we discuss the benefits and costs of AI for a business-to-business (B2B) firm and its internal, external and societal stakeholders. Being mindful of legal and ethical concerns, we expect the social value of AI to increase over time as the barriers for adoption go down, technology costs decrease, and more stakeholders capture the value from AI. We identify the contributions to the social value of AI, by highlighting the benefits of AI for different actors in the organization, business consumers, supply chain partners and society at large. This chapter also offers future research opportunities, as well as practical implications of the AI adoption by a variety of stakeholders.

In this study, researchers applied blended learning program to investigate the success of a blended learning program on satisfaction of the psychological needs, and academic achievement of chemistry students of O-Levels, following curriculum prescribed by University of Cambridge.

Research pattern is quantitative aligned with the quasi-experimental and pre-post experimental design which aimed at examining the efficiency of a motivational strategies adopted with the use of blended learning program on psychological needs satisfaction (competence, autonomy, and relatedness) and achievement in chemistry O-Levels Syllabus, at the end of the research program.

Hypothesis testing represented that use of blended learning program has significant and positive impact on academic achievements through the mediation of autonomy. Results also revealed the substantial association of blended learning on other psychological needs (i.e., competence and relatedness); however, the competence and relatedness have no effect on academic achievements in this study. Thus, research concludes that providing an autonomous environment in substitution of the controlled environment promotes learning and produces positive outcomes.

Blended learning or use of Learning Management Systems is being commonly used mostly in the tertiary level of studies; however, blended learning with secondary classes especially in the field of chemistry is yet not studied in detail. Similarly, the usefulness of the motivational strategies to learn chemistry is observed with university-level students, but very rare data about encouraging students at the secondary level have been gathered. Therefore, the researcher designed this blended learning program to enhance students’ motivation towards achievements in secondary chemistry.

In recent years, both academics and institutions have acknowledged the crucial role multinational enterprises (MNEs) can play in addressing the sustainability challenges, as formalized by the sustainable development goals (SDGs). Nevertheless, because of their extensiveness and their design as country-level targets, SDGs have proven challenging to operationalize at a firm level. This problem opens new and relevant avenues for research in international business (IB). This chapter attempts to frame the topic of extended value chain sustainability in the IB literature. In particular, it addresses a specific topic, that is, how sustainability and resilience-building practices interact in global value chains (GVCs). To do so, the present study develops the case of STMicroelectronics (ST), one of the biggest semiconductor companies worldwide.

Based on theories related to coopetition, the purpose of this paper is to examine the patterns of business-to-business digital referrals inscribed in businesses’ digital content.

A complete industry-wise digital data set is formed by extracting digital referrals in all the content pages. The authors outline how digital referrals are strategically used among peer businesses in the peer-to-peer digital network and in the augmented digital network, taking into consideration geographical framing and physical distance.

The authors reveal how geographical framing and physical distance influence peer-to-peer referral patterns in the digital space. Quite counter-intuitively, businesses are more likely to give digital referrals for peers residing in the same region, as well as for peers located in closer proximity. Further, results from the augmented digital network show that peer businesses in closer proximity exhibit greater strategic similarity in their digital referring strategy.

The findings extend the understanding of business-to-business coopetition to the digital space and suggest that geographical framing and physical distance can induce reciprocated relationships between peers by offering each other digital referrals.

The findings shed light on the formation of a business-to-business digital coopetition strategy using digital referral marketing.

This study highlights the impact of digital referrals in business-to-business relationship management, especially in the digital coopetition context.

Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations.

The authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches.

The results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect.

The findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity.

The paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.

Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

An examination is made of developments in port dynamics since 1965. Initially, this task is addressed by studying changes in past port patterns using a simple descriptive model to accommodate shifts induced by containerization. Over time these changes have led to the reversal of the concentration and centralization of port activities. Then consideration is given to the behavior of stakeholders active in the contemporary port scene by elaborating a bipolar global-local analytical framework through an invocation of the hybrid concepts of glocalization and loglobalization. This analysis leads to an examination of emerging economies to gauge future trends in port dynamics following the dramatic emergence of China. Finally, there is a discussion of the need to go beyond inter-port competition to comprehend global production-distribution networks by exploring synergies between the supply chain and the total transport network to bring out parallels in the hub-and-spoke structure not only underpinning maritime activities but also air transport and telecommunications.