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This study aims to report business preferences for achieving net-zero power production emissions in Saskatchewan, Canada as well as business perceptions of the most preferable power production sources, barriers to change and suggestions for improvement. Mixed methods included focus groups and a survey with experimental design. This research demonstrates that this method of advancing academic and business knowledge systems can engender a paradigmatic shift to decarbonization.

The study is a mixed-methods study using five focus groups and a survey which included a 15-min information video providing more information on power production sources (small modular reactors and biomass). Participants requested more information on these topics in the initial three focus groups.

There is a significant gap in Canadian Government targets for net-zero emissions by 2050 and businesses’ plans. Communications, knowledge and capacity gaps identified include lack of regulatory requirements, institutional barriers (including a capacity charge in the event a business chooses to self-generate with a cleaner source) and multi-level governance dissonance. More cooperation between provincial governments and the federal government was identified by participants as a requirement for achieving targets. Providing information to survey respondents increased support for clean and renewable sources, but gender and knowledge are still important characteristics contributing to support for different power production sources. Scientists and teachers were the most trusted sources of information. Power generated from small modular nuclear reactors was identified as the primary future source of power production followed by solar, wind and natural gas. Research results also confirmed the high level of support for hydropower generated in Saskatchewan versus import from Manitoba based on high values of energy solidarity and security within the province.

This study is original, as it concerns upstream system power production portfolios and not failed projects; the mixed-method research design including a focus group and an experimental survey is novel. This research partially addresses a gap in knowledge surrounding which knowledge systems advance paradigmatic shifts and how and whether involving business people in upstream power production decisions can inform decarbonization.

Building on Kavaratzis and Hatch’s (2013) identity-based place branding model, this paper aims to explore the spatial and social dimensions of the place brand identity formation process and how residents used social media to participate in the process of shaping a city brand during a crisis.

Adopting an interpretive and social constructionist approach, this study analyses a sample of 187 short videos created and posted by Wuhan residents on the social media app Douyin during a COVID-19 lockdown. The authors read the videos as cultural texts and analysed underlying social processes in the construction of place brand identity by residents.

This study develops an adapted conceptual model of place identity formation unfolding in four sub-processes: expressing, impressing, mirroring and reflecting, and each sub-process subsumes two dimensions: the social and the spatial. In addition, this study empirically describes how residents participated in place branding processes in two ways, namely, their construction of city brand identity via communicative practice and their exertion of changes to a city brand during a crisis. The model reveals how place brands emerge and can be transformed.

This paper amplifies Kavaratzis and Hatch's (2013) identity-based place branding model by testing it in an empirical study and highlighting the social and spatial dimensions. This paper contributes to research about participatory place branding by exploring how residents participated in the place branding process. This study analysed short videos on social media, a new communication format, rather than textual narratives dominating past studies.

Currently, China’s economy is in the critical phase of transforming economic development patterns and replacing old growth drivers with new ones. Whether it can successfully overcome the “middle-income trap” has become a significant issue attracting wide attention.

Driven by underlying digital technologies such as artificial intelligence, blockchain, cloud computing and big data, the fourth industrial revolution featuring the booming digital economy has provided significant opportunities for China’s economy to “overtake” and overcome the “middle-income trap”. The transformation of economic development pattern, the optimization of industrial structure, and the change of growth drivers, brought by the deep integration of digital and real economies are the keys to leaping over the “middle-income trap”.

From the supply side, the digital economy can improve the quality and efficiency of the supply side and promote the supply-side structural reform and economic growth from the following three aspects: First, promote the quality, efficiency and diversification of the supply system; second, promote networking, opening-up and synergy in the innovation system and third, promote the socialization, modularization and flexibility of production pattern. From the demand side, the digital economy can boost the new drivers of the “troika” of economic growth consisting of consumption, exports and investment by changing the market investment direction, promoting consumption upgrade and fostering export strengths. However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

To overcome the “middle-income trap”, it is necessary to adapt to the laws of economic evolution and promote a fundamental change in economic growth drivers; boost the high-quality development of the digital economy by strengthening the support role of data in the digital economy; and accelerate digital industrialization and industrial digitalization to realize the integration of digital and real economies.

Korea and China have promoted a bilateral FTA since 2005 to upgrade their economic relationships. If the Korea-China FTA is concluded, then trade between the two countries is likely to involve substantial changes both quantitatively and qualitatively. Offer lists submitted by Korea include steel, petrochemicals and machinery and those by China include some agricultural and marine products as well as nonferrous metals. Korea's interest in the Korea-China FTA has focused mainly on damage to the agricultural sector and there have been a lot of studies on the effects of the FTA on Korean agricultural sector. However, little is known about why China includes the nonferrous metals industry for early voluntary liberalization and its implications for the domestic economy. Nonferrous metals industry is one of China’s national strategic sectors and has a large supply excess in the country. This study targets the survey of Chinese nonferrous metals industry and trade structure and considers the problem of nonferrous metals in the context of negotiations for the Korea-China FTA and its implications for a higher-quality Korea-China FTA.

The relationship between farm size and greenhouse gas (GHG) emissions has not been clearly defined. This paper aims to assess and compare the impact of farm size on greenhouse gas (GHG) emissions derived from wheat and maize production in the North China Plain (NCP), one of the most important agricultural regions in China.

A field survey through face-to-face interviews was conducted to collect the primary data, and life cycle assessment method, a worldwide comparable framework, was then adopted to characterize the farm-size effect on greenhouse gas (GHG) wheat and maize production in NCP.

It was confirmed that GHG emissions from N fertilizer production and use were the primary contributor to total carbon footprint (CF). As farm size increased, maize yield increased but wheat yield barely changed, while area-scaled and yield-scaled CF declined for both crops. These results were supposed to relate to utilize the inputs more efficiently resulting from increased application of modern agriculture methods on larger operations. It was also found maize not only had higher grain yields, but possessed much smaller CFs. More notably, the reduction of CF with farm size seemed to be more sensitive for maize as compared to wheat. To further mitigate GHG emissions, farm size should better be larger for wheat than for maize.

This study provides useful information guide for Chinese agriculture in increasing crop production, raising farm income and relieving environmental burdens caused by the misuse of agricultural resources.

This research sought to identify the best strategy for avoiding corporate amnesia in the context of the Industry 5.0 and an aging society.

To achieve this goal, a multi-phase methodology based on analytic network process was proposed and tested in one of the biggest companies in the bakery industry.

The results highlight that online communities of practice and storytelling are the best way to avoid corporate amnesia. The most important factors are commitment, work satisfaction and organizational culture. Commitment and work satisfaction also enhance the use of online communities of practice, while work satisfaction and organizational culture foster the use of storytelling.

This article proposes a nexus between knowledge management and operations management. This research also presents a decision-making tool that can help managers determine the most appropriate strategy for avoiding corporate amnesia.

To understand the context surrounding the sustainable supplier management (SSM) process (i.e. selection, development and evaluation), this paper aims to explore institutional logics existing in the Ecuadorian cocoa supply chain (SC). By considering local characteristics and sustainability practices, this study illustrates how competing logic influences SSM.

This paper uses a multiple-case study method for which the authors interviewed different cocoa SC members in Ecuador and used a ground-up approach to analyse the data and reveal singularities influencing sustainability management.

The analysis uncovered two main logics operating within the Ecuadorian cocoa SC SSM process: a commercial logic (e.g. potential for market access, product traceability) and a sustainability logic (e.g. local development and traditions/cultural issues). These logics address market demand requirements; however, some local producers’ needs that impact SSM remains unexplored such as the existence of a regional ancestral culture that poses sustainability as a dominant logic with meaning beyond the triple bottom line. While the two logics have influenced supplier sustainability performance, this paper finds that, of the three SSM sub-processes (selection, development and evaluation), supplier development was the most relevant sub-process receiving attention from SC managers in the studied context.

By understanding the differences in logic and needs, SC managers can better develop strategies for SSM.

The study highlighted in this paper investigated the underexplored topic of the effects that competing logic may have on SSM. This paper focusses on the supplier’s point of view regarding sustainability requirements, addressing a consistent research gap in the literature.

This study proposes a literature review and, based on the findings, the authors develop a conceptual framework, attempting to explain how technology may influence visitor behavior and eventually trade show performance.

The present research explores the role of visitors in the trade show context. The analysis specifically focuses on the variables that influence visitors’ participation at business-to-business trade shows and how their satisfaction and perception can be related to exhibition performance. The authors also take into consideration technological trends that prior to COVID-19 pandemics were slowly emerging in the trade show industry.

The findings highlight a continuity between pre-, at and postexhibition phases. Visitors’ behavior represents a signal of how a trade show is perceived as postexhibition purchases and next visit emerge as signals of an exhibition evaluation in relation to visitors’ perception. Besides being urgent tools for the continuity of the sector due to the pandemics, emerging technological trends can be key elements in understanding visitors’ behavior and in boosting their interest and loyalty toward trade shows.

The paper proposes a conceptual model including top notch and innovative technological trends to improve the understandment of visitors’ behavior. Both practitioners in companies and academics might find the study useful, given the digital uplift generated by the pandemics.

Mouth segmentation is one of the challenging tasks of development in lip reading applications due to illumination, low chromatic contrast and complex mouth appearance. Recently, deep learning methods effectively solved mouth segmentation problems with state-of-the-art performances. This study presents a modified Mobile DeepLabV3 based technique with a comprehensive evaluation based on mouth datasets.

This paper presents a novel approach to mouth segmentation by Mobile DeepLabV3 technique with integrating decode and auxiliary heads. Extensive data augmentation, online hard example mining (OHEM) and transfer learning have been applied. CelebAMask-HQ and the mouth dataset from 15 healthy subjects in the department of rehabilitation medicine, Ramathibodi hospital, are used in validation for mouth segmentation performance.

Extensive data augmentation, OHEM and transfer learning had been performed in this study. This technique achieved better performance on CelebAMask-HQ than existing segmentation techniques with a mean Jaccard similarity coefficient (JSC), mean classification accuracy and mean Dice similarity coefficient (DSC) of 0.8640, 93.34% and 0.9267, respectively. This technique also achieved better performance on the mouth dataset with a mean JSC, mean classification accuracy and mean DSC of 0.8834, 94.87% and 0.9367, respectively. The proposed technique achieved inference time usage per image of 48.12 ms.

The modified Mobile DeepLabV3 technique was developed with extensive data augmentation, OHEM and transfer learning. This technique gained better mouth segmentation performance than existing techniques. This makes it suitable for implementation in further lip-reading applications.

Soil nutrient management and fertilizer use by farmers are important for sustainable grain production. The authors examined the effect of an experimental agricultural extension program, the science and technology backyard, in promoting sustainable soil nutrient management in the North China Plain (NCP). The science and technology backyard integrates farmer field schools, field demonstrations, and case-to-case counselling to promote sustainable farming practices among rural smallholders.

The authors conducted a large-scale household survey of more than 2,000 rural smallholders. The authors used a multivariate regression analysis as the benchmark to assess the effect of the science-and-technology backyard on smallholder soil nutrient management. Furthermore, the authors used coarse exact matching (CEM) methods to control for potential bias due to self-selection and the (endogenous) switching regression approach as the main empirical analysis.

The results show that the science-and-technology backyard program increased smallholders' wheat yield by approximately 0.23 standard deviation; however, no significant increase in maize yield was observed. Regarding soil nutrient use efficiency, the authors found a significant improvement in smallholders' phosphorus and potassium use efficiencies for both wheat and maize production, and a significant improvement in nitrogen use efficiency for wheat production, but no significant improvement of nitrogen use efficiency for maize production.

This study evaluated a novel participatory agricultural extension model to improve soil nutrient management practices among smallholders. The integration of agronomists' scientific knowledge and smallholders' local contextual experiences could be an effective way to improve farmers' soil nutrient management. This study provides the first quantitative estimates based on rigorous impact assessment methods of this novel extension approach in rural China.