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This study aims to investigate the impact of supply chain concentration (SCC) on corporate research and development (R&D) investment and determine the moderating roles of industry concentration and financing constraints on the relationship between SCC and R&D investment.

The study collected data from Chinese listed companies, used the fixed effects model to test the research hypotheses and further used the two-stage Heckman test and propensity score matching (PSM) to address potential endogeneity issues.

The result reveals a negative impact of SCC on corporate R&D investment. In addition, industry concentration mitigates the negative impact of SCC on corporate R&D investment, but financing constraints strengthen the negative impact.

This study introduces the concept of SCC and empirically tests its effect on R&D investment, further explaining the lack of corporate innovation. This study inspires companies to strengthen SC management and weigh the level of SCC with environmental factors.

A recent global pandemic, known as coronavirus disease 2019 (COVID-19), affects the manufacturing supply chains most significantly. This effect becomes more challenging for the manufacturers of high-demand and most essential items, such as toilet paper and hand sanitizer. In a pandemic situation, the demand of the essential products increases expressively; on the other hand, the supply of the raw materials decreases considerably with a constraint of production capacity. These dual disruptions impact the production process suddenly, and the process can collapse without immediate and necessary actions. To minimize the impacts of these dual disruptions, we aim to develop a recovery model for making a decision on the revised production plan.

In this paper, the authors use a mathematical modeling approach to develop a production recovery model for a high-demand and essential item during the COVID-19. The authors also analyze the properties of the recovery plan, and optimize the recovery plan to maximize the profit in the recovery window.

The authors analyze the results using a numerical example. The result shows that the developed recovery model is capable of revising the production plan in the situations of both demand and supply disruptions, and improves the profit for the manufacturers. The authors also discuss the managerial implications, including the roles of digital technologies in the recovery process.

This model, which is a novel contribution to the literature, will help decision-makers of high-demand and essential items to make an accurate and prompt decision in designing the revised production plan to recover during a pandemic, like COVID-19.

Among natural disasters, drought affected the most people worldwide during the past few decades (Obasi, 1994). Since the late 1970s, there has been a shift in El Niño-Southern Oscillation toward more warm events, closely related to a worldwide trend for intensified drought (Dai, Trenberth, & Karl, 1998). In particular, this trend was manifested as widespread droughts during 1999–2002 in the northern hemisphere (Lotsch, Friedl, Anderson, & Tucker, 2005), including Asia, and notably in Mongolia (Nandintsetseg, Shinoda, Kimura, & Ibaraki, 2010; Shinoda, Ito, Nachinshonhor, & Erdenetsetseg, 2007). The decade of 2000s has experienced increased vegetation degradation and wind erosion that resulted from decreased summer precipitation in wide areas of East Asia (Kurosaki, Shinoda, & Mikami, 2011a; Kurosaki, Shinoda, Mikami, & Nandintsetseg, 2011b). Furthermore, in general, projections of climate models have suggested that the frequency and intensity of extreme weathers will likely increase in the future (IPCC WG I, 2007). Given this background, it is vital to make an assessment of socioeconomic impacts of the extreme weathers and to develop proactive approaches to mitigating such impacts.

The purpose of this paper is to investigate the effects of cultural beliefs on governance in a business network without a legal institutional framework. Particular emphasis is placed on the cross-country remittance mail operating network in Chaoshan, China, during the period 1860-1949. This investigation builds on Greif’s business governance theory and develops an analytical framework that considers cultural beliefs, agency relationships and multilateral punishment mechanisms. Furthermore, it uses the institutional analysis method to identify the institutional factors that sustained the remittance mail operating networks and their underlying mechanisms.

This paper adopts the qualitative research method. First, it investigates the history of the remittance mail operating network and agency relationships by searching through the contents of the relevant historical documents preserved in the official archives and information found in other records. Thereafter, it summarizes and demonstrates the cultural beliefs inferred from that research. The archival materials permit analysis of the interactions between cultural beliefs, agency relationships and multilateral punishment mechanisms by the institutional analysis method.

Due to the lack of legal institutions in China during the period under review, cultural beliefs played a central institutional role in cross-country business relations. Network governance was coupled with clan cultural beliefs in the remittance mail operating network. This relationship was the key to sustain the efficient operation of the remittance mail network.

In the West, corporate governance has been influenced by and has become an integral feature of Western culture and values. This is not necessarily so for the corporate governance in terms of Chinese culture and values. Thus, instead of mimicking the modes of developed countries, it is important for Chinese enterprises to seek a mode of corporate governance that is in accord with their local cultures. This may be an important focus for enterprise development.

The materials and energy density of current electric vehicles (EV) battery technology means that the vehicles are heavier and have a shorter range in comparison to internal combustion engine vehicles (ICEV). Battery cost also means EVs are relatively expensive for the consumer, even with government incentives, and dependent on sometimes-rare resources being available. These factors also limit the applicability of battery-electric technologies to heavy-duty vehicles. However, a number of next generation technologies are under laboratory development which could radically change this situation. Using a follow-the-money methodology, the strategic innovations of companies and public institutions are examined. The chapter will review the potential for changes in resource inputs, higher-density batteries and cost reductions, considering options such as lithium-air, metal-air and solid-state technologies. The innovations outlined in these technologies are considered from an economic perspective, identifying their advantages and disadvantages in commercialisation. At the same time, innovations, and investments in infrastructure electrification (Electric Road Service) and battery exchange point with swapping technology will be also considered due their implications and contribution to solving battery-related challenges and shortcomings. It is concluded that only a joint investment in effort on technologies would allow the use of EVs to be extended to a broad public in terms both of users and geography.

With the holistic approaches of Industry 4.0, products, services, standards, and application techniques have been improved. This digitalization era has not only impacted the production and service dynamics, but also added advanced dimensions to logistics and supply chain management. According to the current world standards, consumer behavior makes the logistics and supply chain processes more challenging. Especially during the COVID-19 outbreak, logistics and supply chain operations became more crucial for the firms, as most consumers have tended toward online shopping while they are in lockdown. Therefore, the competitive environment today enables firms to adapt the technologies and approaches of Logistics 4.0 and smart/digital supply chain, as they must respond to consumers' demands quickly. Moreover, firms need to have strong relations with their supply chain partners via these technologies. The technologies such as the Internet of Things (IOT), cyber-physical system, Big Data, and cloud computing help to change the fundamentals of logistics and supply chain and improve processes for all industries. This study aims to analyze the transformation of traditional logistics and supply chain activities into Logistics 4.0 and smart/digital supply chain. Primarily, we hope to analyze the existing studies by investigating the concept of Logistics 4.0 within Industry 4.0 dynamics. As firms develop their logistics operations, their supply chain processes will be shaped by the technologies and applications, and this situation also leads us to find out the importance of smart or digital supply chain operations. Discussing the potentials of smart or digital supply chain also lets us to reveal how companies handle their logistics operations during the COVID-19 period.

The ability to detect disturbances quickly as they arise in a supply chain helps to manage them efficiently and effectively. The purpose of this paper is to demonstrate the feasibility of automatically and therefore quickly detecting a specific disturbance, which is constrained capacity at a supply chain echelon.

Different supply chain echelons of a simulated four echelon supply chain were individually capacity constrained to assess their impacts on the profiles of system variables, and to develop a signature that related the profiles to the echelon location of the capacity constraint. A review of disturbance detection techniques across various domains formed the basis for considering the signature-based technique.

The signature for detecting a capacity constrained echelon was found to be based on cluster profiles of shipping and net inventory variables for that echelon as well as other echelons in a supply chain, where the variables are represented as spectra.

Detection of disturbances in a supply chain including that of constrained capacity at an echelon has seen limited research where this study makes a contribution.

This study aims to conduct socio-technical analysis of the rapidly evolving Internet of Things (IoT) ecosystem and industry, including such factors as market growth and user experiences, policy and the impact of IoT on various areas.

By applying a multi-level socio-technical framework to IoT in South Korea, this study seeks an ecological understanding of how IoT will evolve and stabilize in a smart environment.

The study shows the values influencing potential users’ adoption of IoT by integrating cognitive motivations and user values as primary determining factors. Along with user modeling, the findings reveal the challenges of designing, deploying and sustaining the diverse components of IoT, and provides a snapshot of Korea’s current approach to meeting these challenges.

The study’s findings offer a contextualized socio-technical analysis of IoT, providing insight into its challenges and opportunities. This insight helps to conceptualize how IoT can be designed and situated within human-centered contexts.

This study aims to empirically examine the relationship between Internet use and personal privacy risk perceptions, the mediating effect of trust and the moderating effect of satisfaction on that relationship, which is exactly conducive to the practice of personal information protection.

A moderated mediation model will be employed to test the hypothesized relationships using the 2017 Chinese Society Survey data.

The authors find that Internet use positively relates to citizens' risk perceptions toward privacy security, and trust partially mediates the relationship between Internet use and privacy risk perception. In addition, the analysis of moderating effects showed that satisfaction with social life significantly enhances the negative impact on individuals' privacy risk perceptions of interpersonal trust. The positively moderating effect of satisfaction with local governments' work mainly reveals the relationship between interpersonal trust (or institutional trust) and citizens' privacy risk perception. Moreover, satisfaction with Internet platforms positively moderates the relationship between consumer trust and privacy risk perception.

This article contributes to the social risk amplification framework by applying it to the personal privacy information protection field, which was rarely discussed before. It also enriches privacy research by identifying the internal mechanism of how Internet use influences citizens' risk perceptions towards privacy information leakage.