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Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

The expansion of new technologies has induced the digital revolution and paved the way for an innovation-based economy. Digitalization, while blurring real and virtual environments, acts as an incentive for innovation and has been regarded as a tool to tackle the crisis. Its particular acceleration was caused by the lockdown regulations due to the COVID-19 pandemic. Social entrepreneurship searches for innovative methods, tools and models to solve pressing social problems. The concept suggests applying business models for implementing social missions. Revenue generated from commercial activities is spent to solve social challenges caused by market imperfection, government inefficiency, disasters, pandemics, wars and economic crises. Advancing technologies, on the one hand, present opportunities for social enterprises and, on the other hand, involve risks to employment, data protection, transformed business model and strategies and changes in society's lifestyle and impose costly digital technologies to be adopted. Social entrepreneurs can create social value by using digital technologies that allow them to reach remote customers, investors or beneficiaries overcoming geographical boundaries or time differences. Yet digitalization can pose a threat to existing jobs as they become redundant; it transforms them or gives rise to new jobs while demanding technological skills and digital literacy. Moreover, enhanced digitalization and effective governmental actions set the stage for the decline of social business. The chapter explores the influence of digitalization on social entrepreneurship and discusses the potential of digital transformation for social enterprises. It examines the risks and opportunities that bring accelerated digitalization to social entrepreneurship.

Drawing upon the third-person effect (TPE) theory, this study focuses on two types of misinformation countering intentions (i.e. simple correction and correction with justification). Accordingly, it aims to (1) assess the tenability of the third-person perception (TPP) in the face of misinformation on social media, (2) explore the antecedents of TPP and its relationship with individual-level misinformation countering intentions and (3) examine whether the mediating process is contingent on different social media usage conditions.

An online survey was conducted with 1,000 representative respondents recruited in Mainland China in January 2022 using quota sampling. Paired t-test, multiple linear regression and moderated mediation analysis were employed to examine the proposed hypotheses.

Results bolster the fundamental proposition of TPP that individuals perceive others as more susceptible to social media misinformation than they are. The self-other perceptual bias served as a mediator between the perceived consequence of misinformation and misinformation countering (i.e. simple correction and correction with justification) intentions. Furthermore, intensive social media users were likely to be motivated to counter social media misinformation derived from the indirect mechanism.

The findings provide further evidence for the role of TPE in explaining misinformation countering intention as prosocial and altruistic behavior rather than self-serving behavior. Practically, promising ways to combat rampant misinformation on social media include promoting the prosocial aspects and beneficial outcomes of misinformation countering efforts to others, as well as reconfiguring the strategies by impelling intensive social media users to participate in enacting countering actions

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2022-0507.

The purpose of this study is to reveal the underlying mechanism in film formation of oil-in-water (O/W) emulsion.

This study focuses on the film forming characteristics of O/W emulsion between the surface of a steel ball and a glass disc coated with chromium. The lubricant film thicknesses of O/W emulsion with various mechanical stirring strength were discussed, which were observed by technique of relative optical interference intensity.

The authors directly observed the oil pool in the contact area, finding the size of oil pool was closely related to the film-forming ability of emulsion. Enrichment phenomenon occurs in oil pool, which was caused by phase inversion. Further investigations revealed that the emulsion is stable with strong stirring strength, resulting in a smaller oil pool size and worse film forming ability.

With the wide usage of O/W emulsion in both biological and industrial systems, the ability of emulsion film formation is considered as an important factor to evaluate the lubrication effectiveness.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2022-0354/

The purpose of this study is to explore how digital transformation helps enterprises achieve high-quality development, including the mediating mechanism of information transparency, innovation capacity and financial stability, the moderating role of financing constraints and government subsidies, and the heterogeneous effects of property rights, size and growth.

This study conducts two-way fixed-effect model using 780 samples of China's Shanghai-Shenzhen A-share listed companies from 2012 to 2019.

The results show that digital transformation can effectively improve the total factor productivity (TFP) of enterprises through the triple channels of information transparency, innovation capability and financial stability. Meanwhile, financing constraints significantly inhibited the contribution of digital transformation to TFP, while government subsidies significantly increased the contribution of digital transformation to TFP. In addition, state-owned enterprises (SOEs), large enterprises and high-growth enterprises are more able to achieve high-quality development by increasing their digital transformation.

In the process of implementing digital transformation, companies should actively improve information transparency, financial stability and innovation capabilities, and choose differentiated paths based on intrinsic characteristics such as property rights, scale and growth. At the same time, the government should actively improve not only the digital institutional environment but also the financial policy and credit system.

This study enriches the theoretical research framework of digital transformation and high-quality development by identifying the channel mechanisms and boundary conditions through which digital transformation affects high-quality development and expands the consequences of digital transformation and the antecedents of high-quality development.

In recent years, Chinese sentiment analysis has made great progress, but the characteristics of the language itself and downstream task requirements were not explored thoroughly. It is not practical to directly migrate achievements obtained in English sentiment analysis to the analysis of Chinese because of the huge difference between the two languages.

In view of the particularity of Chinese text and the requirement of sentiment analysis, a Chinese sentiment analysis model integrating multi-granularity semantic features is proposed in this paper. This model introduces the radical and part-of-speech features based on the character and word features, with the application of bidirectional long short-term memory, attention mechanism and recurrent convolutional neural network.

The comparative experiments showed that the F1 values of this model reaches 88.28 and 84.80 per cent on the man-made dataset and the NLPECC dataset, respectively. Meanwhile, an ablation experiment was conducted to verify the effectiveness of attention mechanism, part of speech, radical, character and word factors in Chinese sentiment analysis. The performance of the proposed model exceeds that of existing models to some extent.

The academic contribution of this paper is as follows: first, in view of the particularity of Chinese texts and the requirement of sentiment analysis, this paper focuses on solving the deficiency problem of Chinese sentiment analysis under the big data context. Second, this paper borrows ideas from multiple interdisciplinary frontier theories and methods, such as information science, linguistics and artificial intelligence, which makes it innovative and comprehensive. Finally, this paper deeply integrates multi-granularity semantic features such as character, word, radical and part of speech, which further complements the theoretical framework and method system of Chinese sentiment analysis.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

This study has covered many types of solar-powered air-conditioning systems that may be used as an alternative to traditional electrically powered air-conditioning systems in order to reduce energy usage. Solar adsorption air cooling is a great alternative to traditional vapor compression air-conditioning. Solar adsorption has several advantages over traditional vapor-compression systems, including being a green cooling technology which uses solar energy to drive the cycle, using pure water as an eco-friendly HFC-free refrigerant, and being mechanically simple with only the magnetic valves as moving parts. Several advancements and breakthroughs have been developed in the area of solar adsorption air-conditioners during the previous decade. However, further study is required before this technology can be put into practise. As a result, this book chapter highlights current research that adds to the understanding of solar adsorption air-conditioning technologies, with a focus on practical research. These systems have the potential to become the next iteration of air-conditioning systems, with the benefit of lowering energy usage while using plentiful solar energy supplies to supply the cooling demand.

The aim of this study is to examine the agency problems that arise between retail property owners and outsourced facility management (FM) service vendors in Ghana.

This study was carried out using telephone and face-to-face interviews. Nine facility managers (n =9) and six retail property owners (n = 6) purposively selected participated in the interviews. The responses from the interviews were analysed using content analysis. To begin with the analysis, the recorded audio for each respondent during the interviews was transcribed to augment what was written during the interviews. The next step was the development of a coding framework where each of the agency problems was assigned unique codes and grouped under themes. Each response was assigned a predefined code based on the agency problems identified in the literature. The research team discussed the consistency of the thematic codes assigned to each of the responses to ensure that each response was captured under the appropriate agency problem theme it best represents.

The results showed that agency problems in FM outsourcing in the Ghanaian retail sector are related to disagreement on expenditure associated with maintenance and repairs and improper tenant information sharing and use by FM service providers. Based on the findings, it is recommended that property owners explore the mixed approach to FM to mitigate the risks of complete outsourcing of FM services. It is also recommended that a clear path on how tenant information can be shared be pre-agreed in FM contracts.

This study provides new literature relating to agency problems in outsourcing and may be the first of its kind for FM in the Ghanaian retail industry. The findings could serve as a starting point for service providers and their principals to find common grounds to understand each other and mitigate the agency problems that could arise and their overall impact on performance.