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This study examines the impact of China’s mixed-ownership reform on the innovation of non-state-owned acquirers, with a particular focus on the impact on firms with high financing constraints, low-quality accounting information or less tangible assets.

We use a proprietary dataset of firms listed on the Shanghai and Shenzhen Stock Exchanges to investigate the impact of mixed ownership reform on non-state-owned enterprise (non-SOE) innovation. We employ regression analysis to examine the association between mixed ownership reform and firm innovation.

The study finds that non-state-owned firms can improve innovation by acquiring equity in state-owned enterprises (SOEs) under the reform. Eased financing constraints, lowered financing costs, better access to tax incentives or government subsidies, lowered agency costs, better accounting information quality and more credit loans are underlying the impact. Additionally, cross-ownership connections amongst non-SOE executives and government intervention strengthen the impact, whilst regional marketisation weakens it.

This study adds to the literature on the association between mixed ownership reform and firm innovation by focussing on the conditions under which this impact is stronger. It also sheds light on the policy implications for SOE reforms in emerging economies.

The Internet of Things (IoT) is expected to have a huge impact on businesses and, especially, the way we think about supply chain management (SCM). However, there is still a paucity of studies on the impact of IoT adoption on supply chains and on different aspects of the business in general. The purpose of this paper is to examine the perception of the academic community of the impact of the IoT adoption in organizational supply chains with a view to verify potential key benefits and challenges existent in the literature. The research presents the impact on an organization along with the impact across its entire supply chain.

Data were collected through the use of an online survey and 87 participants completed the survey. Participants were mainly from the academic community and were university scholars based in different countries located in six continents. Participants were authors, or co-authors, of academic papers published in the Decision Science Institute 2015 and 2016 annual conference proceedings, the 21st International Symposium of Sustainable Transport and Supply Chain Innovations, the Supply Chain Management: An International Journal 2016 issues, and the Operations and Supply Chain Management: An International Journal 2016 issues.

The authors were able to confirm the significance of some of the examined potential benefits to individual organizations and their entire supply chains. However, the study identified other potential benefits that were not seen as a direct impact of IoT adoption. Most of the examined potential benefits were found to contribute to a number of critical success factors for implementing successful SCM. The authors were also able to confirm that some of the examined potential challenges were still perceived as key hinders to IoT adoption but examined potential challenges were not seen as hurdles to IoT adoption.

To the best of the authors’ knowledge, this is the first study of its kind. Although some literature attempted to provide an overview about the IoT management, no study has specifically explored potential benefits and challenges related to the adoption of IoT in supply chains and ranked them based on their significance. The results can be beneficial to academic scholars interested in the researched topic, business professionals, organizations within different sectors, and any other party interested in understanding more about the impact of adopting IoT on SCM.

The purpose of this paper is to analyze the operational decisions of a manufacturer who produces multiple products and the government's selection of cap-and-trade and carbon tax regulations.

This paper explores the production decisions of a multi-product manufacturer under cap-and-trade and carbon tax regulations in a cap-dependent carbon trading price setting and compares carbon emission, the manufacturer's profits and social welfare under the two regulations. Game theory and extreme value theory are used to analyze our models.

First, the authors find that the optimal profit of the manufacturer (the optimal cap) increases and then decreases with the cap (the unit carbon emission of product). Second, if the environmental damage coefficient is moderate, the optimal cap of unit environmental damage coefficient is independent of the product carbon emission or other related product parameters. Ultimately, cap-and-trade regulation always generates more carbon emission than carbon tax regulation. And cap-and-trade regulation (carbon tax regulation) can generate more social welfare if the environmental damage coefficient is low (high), and the social welfare under the two regulations is equal to each other, or otherwise.

This paper contributes the prior literature by considering the inverse relationship of the allocated cap and the carbon trading price and discusses the social welfare under cap-and-trade and carbon tax regulations. Some important and new results are found, which can guide the government's implementation of the two regulations.

The purpose of this paper is to explore a novel measurement approach for wheel-terrain contact angle using laser scanning sensors based on near-terrain perception. Laser scanning sensors have rarely been applied to the measurement of wheel-terrain contact angle for wheeled mobile robots (WMRs) in previous studies; however, it is an effective way to measure wheel-terrain contact angle directly with the advantages of simple, fast and high accuracy.

First, kinematics model for a WMR moving on rough terrain was developed, taking into consideration wheel slip and wheel-terrain contact angle. Second, the measurement principles of wheel-terrain contact angle using laser scanning sensors was presented, including “rigid wheel - rigid terrain” model and “rigid wheel - deformable terrain” model.

In the proposed approach, the measurement of wheel-terrain contact angle using laser scanning sensors was successfully demonstrated. The rationality of the approach was verified by experiments on rigid and sandy terrains with satisfactory results.

This paper proposes a novel, fast and effective wheel-terrain contact angle measurement approach for WMRs moving on both rigid and deformable terrains, using laser scanning sensors.

This chapter proposes a global agenda to eliminate racism in nursing by targeting reform at nursing education administration internationally. First, the history of racism in nursing is reviewed, along with two models – the diversity model and the cultural competence model – that were applied unsuccessfully to counteract racism in nursing. Second, a description of how racism is entrenched in nursing leadership globally is presented. Third, the recalcitrant structures that serve to maintain institutionalized racism (IR) in the international nursing education system are carefully examined. Specifically, the components and constructs involved in IR in nursing education are delineated, and the way in which these negatively impact both ethnic minority (EM) students and faculty are explained. Based on this, a global agenda to eliminate racism in nursing education internationally is proposed. Eliminating racism in higher education in nursing is a mandatory social responsibility if global healthcare is ever to be equitable. Five actionable recommendations are made to eliminate racism in higher education are summarized as follows: (1) components of nursing programs which are designed to eliminate racism in nursing education should be governed at the country level, (2) to design and implement a system of surveillance of the global nursing community to enable standardized measurement to ensure nursing education programs in all countries are meeting anti-racism benchmark targets, (3) nursing education programs should be established worldwide to provide individual pipeline and mentorship programs to ensure the career success of EM nursing students and faculty, (4) nursing education programs should be conducted to reduce barriers to EM participation in these individual support programs, and (5) nursing education programs are required to teach their nursing faculty skills in developing anti-racist curricula that seeks to eliminate implicit bias.

The existing mashup literature paid little attention to the actual adoption and diffusion of mashups in an organizational context. As more and more organizations are engaged in mashup initiatives, more research efforts focussing on the mashup use and adoption issues from the organizational perspective are needed to ensure that organizations can receive the maximum benefits from their mashup initiatives. Two studies are conducted to increase the understanding of the use and adoption issues with social media mashups. The paper aims at discussing these issues.

The paper first used a text mining approach to analyze relevant posts on blogs and messages in a major online mashup forum in order to understand the current status of social media mashup as well as representative themes and issues with social media mashups in general. Subsequently, the paper reviewed a number of social media mashup sites created by higher education institutions (HEIs) in the USA.

The paper identified some representative themes and issues with social media mashups in general. The paper also identified the approaches that were used to design the interface of social media mashup sites by HEIs. Based on the two studies, this paper provides recommendations and insights to guide social media mashup development and adoption in an organizational context.

This is the first article to discuss the use and adoption of social media mashups in organizational environments. This paper can be used as a starting point to motivate other researchers to further explore the diffusion of social media mashups in different industries. This paper also helps organizations improve their social media mashup initiatives.

The aim of this study is to examine the influence of consumer preferences for overseas green products and the implementation of blockchain technology on the performance of a supply chain, which comprises an overseas manufacturer and a domestic e-commerce platform. This research endeavors to identify the optimal pricing decisions and strategies for both the manufacturer and the platform in the context of the expanding e-commerce and globalization of the economy.

The authors propose and analyze four distinct models based on the selection of selling contracts by the manufacturer and the adoption strategy of blockchain by the platform, using game theory to obtain the optimal solutions for these models.

The authors show that consumer migration promotes the manufacturer's green inputs, while the expansion of green consumer proportion is not conducive to it. They also show that blockchain technology has the potential to effectively limit manufacturer cannibalization. Interestingly, the study reveals a cascading effect of advantage where the manufacturer's profit variation trend changes only with the integration of pricing power advantage and blockchain technology inputs. This effect suggests that the equilibrium strategy is achievable under the agency contract with blockchain adoption, while Pareto improvement can be obtained with blockchain technology under both selling contracts.

This research could be extended in several possible directions. First, future work could explore outsourcing strategies for overseas manufacturers. Second, more types of consumer heterogeneity and different risk preferences could be considered. Third, this study can be extended by further exploring the design of mechanisms under asymmetric demand information to make the model more realistic.

The authors examine the impact of market segmentation and consumer preferences on green supply chain decisions, and analyze supply chain members' strategic choices for selling contracts and blockchain adoptions. The research also sheds light on the theoretical underpinnings and practical applications of green supply chain development and blockchain applications.

The confirmation of receipt of orders by consumers means that the online retailer actually receives the payments on many retail platforms (e.g. Taobao). In order to recoup funds as soon as possible, the retailer will take steps (e.g. improving the level of delivery and adopting a rebate policy) to encourage consumers to confirm receipt earlier. It is significant for the retailer to identify an appropriate strategy and determine the optimal product price. To address the above issues, this paper examines and compares the pricing strategies and profits under different strategies to show some managerial insights for the retailer's decision-making.

In this paper, the authors discuss four models, i.e. adopting common delivery and offering consumers no rebates, adopting common delivery and offering rebates, adopting fast delivery and offering no rebates and adopting fast delivery and offering rebates, which the retailer may consider. Under different models, consumer utility and firm's profit structure are disparate. After comparing the retailer's profits under four models, the optimal strategy, profit and product price are obtained.

Some interesting results are as follows. When the cost of fast delivery is not very high, improving the level of delivery would bring more profit to the retailer and create a positive impact on consumers. Interestingly, our results also show that offering proper rebates to stimulate consumers to confirm receipt early only serves to improve the profit only when the motivation of consumers to confirm the receipt is very low. Moreover, the authors find that a higher level of delivery services can promote the implementation of the rebate policy to improve the retailer's earnings.

This paper is the first study on the transaction mode of retail platforms and the problem of confirming receipt by a model-based method.

The purpose of this paper is to investigate the equivalent control authority of the conventional and circulation control (CC) wing of the aircraft and assess the energy expenditure and aerodynamic efficiency of the CC wing.

Four target cases with different flap deflection angles θ are set in advance for the conventional wing, and then a series of cases with different jet momentum coefficients Cμ are set for the CC wing. The lift, drag and momentum coefficient curves of the CC wing are compared to those of the four conventional wing cases. The curves with the best agreement are selected to establish the corresponding relation between θ and Cμ. The energy expenditure of the CC system is analyzed. The concept of equivalent lift-to-drag ratio for the CC wing is introduced to compare the aerodynamic efficiency with the conventional wing

The control authority of the conventional wing at θ = 0º, 10º, 20º, 30º are equivalent to the control authority of the CC wing with Cµ = 0.0, 0.005, 0.009 and 0.012. The CC system is more efficient at small Cµ than large Cµ.

This study could contribute to the application of the CC system on flapless aircrafts.

The corresponding relation between θ and Cµ is established by matching the equivalent control authority between the conventional wing and CC wing.

Current knowledge management (KM) systems cannot be used effectively for decision-making because of the lack of real-time data. This study aims to discuss how KM can benefit by embedding Internet of Things (IoT).

The paper discusses how IoT can help KM to capture data and convert data into knowledge to improve the parking service in transportation using a case study.

This case study related to intelligent parking service supported by IoT devices of vehicles shows that KM can play a role in turning the incoming big data collected from IoT devices into useful knowledge more quickly and effectively.

The literature review shows that there are few papers discussing how KM can benefit by embedding IoT and processing incoming big data collected from IoT devices. The case study developed in this study provides evidence to explain how IoT can help KM to capture big data and convert big data into knowledge to improve the parking service in transportation.