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This study empirically examines the impact of announcements on supply chain strategic collaboration (SCSC) on companies' shareholder value.

This study analyzes changes in shareholder value of companies listed in China based on data of 208 SCSC announcements. The signaling theory is applied to determine correlation among SCSC announcements and the market. An event study is used to estimate the stock market reaction to SCSC announcements. The common market model estimates stock abnormal returns after the event. The least squares method and regression model calculate the model parameter value.

There is a positive and statistically significant relationship between SCSC announcement and shareholder value. Market reaction to product development collaboration is significantly higher than to technology-sharing collaboration, market collaboration, and other SCSC types. The market reacts more positively to suppliers and companies with greater supply chain control power than to buyers and companies with lower control power. Announcements from the service supply chain can lead to stronger market reactions than those from manufacturing supply chains.

The findings provide a systematic assessment of how SCSC announcements contribute to firms' shareholder value. The result provides a benchmark of value promotion that can be expected from SCSC announcements.

This study fills the research gap that using secondary data to assess changes in companies’ shareholder value caused by SCSC announcements and firstly examines these changes by constructing the signaler–signal–receiver progress based on signaling theory. The research results provide a new reference and inspiration for deeper understanding of the impact mechanism of SCSC. Furthermore, this study contributes to the development of the signaling theory using an empirical study in an emerging market, China.

This study aims to investigate the differences in consumer reviews across multiple e-commerce platforms to better assist consumers in making informed decisions. By examining the specific content of these differentiated reviews, the study seeks to provide insights that can enhance e-commerce services and improve consumer satisfaction.

The research utilizes the latent Dirichlet allocation (LDA) method for text analysis to identify the varying concerns of consumers across different e-commerce platforms for the same product. Additionally, the study expands the sentiment dictionary to address polysemy issues, allowing for a more precise capture of sentiment differences among consumers. A non-parametric test is employed to compare reviews across multiple platforms, providing a comprehensive analysis of review disparities.

The findings reveal that consumer concerns and sentiments vary significantly across different e-commerce platforms, even for the same product. The combination of text analysis and non-parametric testing highlights the objectivity of the research, offering valuable evidence and recommendations for improving e-commerce services and enhancing the shopping experience.

This study is original in its approach to combining text analysis with non-parametric testing to examine multi-platform review differences. The research not only contributes to the understanding of consumer behavior in the context of e-commerce but also provides practical suggestions for platforms and consumers, aiming to optimize service quality and consumer satisfaction.

Resident perceptions of tourism impacts are a swiftly growing area in tourism research that has the potential to contribute to sustainability of destinations. Understanding and analyzing the perceptions of local communities for improving destination attractiveness is key to many destinations, the most popular being mountainous regions. Leh, Ladakh, in the northern part of the Trans-Himalayan region is a renowned Indian tourist place, which sees hordes of tourists in the short summer season. The influx of a large number of visitors in the short season has proved beneficial and also a problem for the destination as tourist numbers overpower the local population numbers leading to pressure on natural resources. Costs of mass tourism are becoming prominent each year and if not scrutinized can damage the likeability of the place. This research attempts to understand resident opinions of impacts of tourism in Leh through primary research. It also aims to find out the link between the demographic profile of residents and perceptions of tourism impacts using a Chi-square test. Results suggest that residents perceive many unfavorable impacts of tourism along with positive impacts. The Chi-square test reveals a significant association between demographic variables and tourism impacts.

This chapter explores the present state of the worldwide tourism sector and its complex phenomenological interconnection with climate change. This analysis emphasizes the significant environmental consequences resulting from the rise of tourism, which can be attributed to the exponential growth facilitated by enhanced connectivity and the concurrent increase in disposable incomes. It thoroughly analyses the primary factors that contribute to the environmental impact of the sector, which encompasses emissions from transportation, infrastructure development, waste generation, and resource usage. Furthermore, this analysis sheds light on the obstacles encountered in the process of shifting toward sustainability, including limited knowledge and understanding, deficiencies in policy implementation, and reluctance to embrace transformation within the sector. However, it also provides insights into numerous activities and solutions currently in progress to alleviate the environmental impact of the industry. The aforementioned approaches encompass the implementation of sustainable tourism practices, legislation revisions, and advancements in technology. This chapter concludes by highlighting the imperative need for a collaborative initiative including governmental bodies, industrial participants, and tourists to establish a harmonious equilibrium between the pursuit of economic expansion and the protection of the environment. The future trajectory of global tourism is contingent upon the adoption of sustainable practices, which are crucial for fostering a healthy coexistence between the tourism industry and the environment.

The purpose of this paper is to improve the mechanical and tribological properties of Si₃N₄ ceramics and to make the application of Si₃N₄ ceramics as tribological materials more extensive.

Si₃N₄-based composite ceramics (SN-2L) containing nitrogen-doped graphene quantum dots (N-GQDs) were prepared by hot press sintering process through adding 2 Wt.% nanolignin as precursor to the Si₃N₄ matrix, and the dry friction and wear behaviors of Si₃N₄-based composite against TC4 disc were performed at the different loads by using pin-on-disc tester.

The friction coefficients and wear rates of SN-2L composite against TC4 were significantly lower than those of the single-phase Si₃N₄ against TC4 at the load range from 15 to 45 N. At higher load of 45 N, SN-2L/TC4 pair presented the lowest friction coefficient of 0.25, and the wear rates of the pins and discs were as low as 1.76 × 10⁻⁶ and 2.59 × 10⁻⁴mm³/N·m. The low friction and wear behavior could be attributed to the detachment of N-GQDs from the ceramic matrix to the worn surface at the load of 30 N or higher, and then an effective lubricating film containing N-GQDs, SiO₂, TiO₂ and Al₂SiO₅ formed in the worn surface. While, at the same test condition, the friction coefficient of the single-phase Si₃N₄ against TC4 was at a range from 0.45 to 0.58. The spalling and cracking morphology formed on the worn surface of single-phase Si3N4, and the wear mechanism was mainly dominated by adhesive and abrasive wear.

Overall, a high-performance green ceramic composite was prepared, and the composite had a good potential for application in engineering tribology fields (such as aerospace bearings).

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0161/

While rapid increase in demand for foods but limited availability of croplands has forced to adopt input-intensive farming practices to increase yield, there are serious long-term ecological implications including degradation of biodiversity. It is increasingly recognised that ensuring agricultural sustainability under the changing climatic conditions requires a change in the production system along with necessary policies and institutional arrangements. In this context, this chapter examines if climate-smart agriculture (CSA) can facilitate adaptation and mitigation practices by improving resource utilisation efficiency in India. Such an attempt has special significance as the existing studies have very limited discussions on three main aspects, viz., resource productivity, adaptation practices and mitigation strategies in a comprehensive manner. Based on insights from the existing studies, this chapter points out that CSA can potentially make significant contribution to enhancing resource productivity, adaptation practices, mitigation strategies and food security, especially among the land-constrained farmers who are highly prone to environmental shocks. In this connection, staggered trench irrigation structure has facilitated rainwater harvesting, local irrigation and livelihood generation in West Bengal. However, it is necessary to revisit the existing approaches to promotion of CSA and dissemination of information on the design of local adaptation strategies. This chapter also proposes a change in the food system from climate-sensitive to CSA through integration of technologies, institutions and policies.

This study aims to investigate the microtopography transformation at a low-speed heavy-load interface with the lubrication of powder particles and its nonlinear friction effect on the sliding pair in contact.

Based on the universal mechanical tester (UMT) tribometer and VK shape-measuring laser microscope, comparative friction experiments were conducted with graphite powder lubrication. The friction coefficient with nonlinear fluctuations and the three-dimensional morphology of the boundary layer at the interface were observed and analyzed under different operating conditions. The effects on lubrication mechanisms and frictional nonlinearity at the sliding pair were focused on under different surface roughness and powder layer thickness conditions.

At a certain external load and sliding speed, the initial specimen surface with an appropriate initial roughness and powder thickness can store and bond the powder lubricant to form a boundary film readily. The relatively flat and firm boundary layer of powder at the microscopic interface can reduce the coefficient of friction and suppress its nonlinear fluctuation effectively. Therefore, proper surface roughness and powder layer thickness are beneficial to the graphite lubrication and stability maintenance of a friction pair.

This research is conducive to developing a deep understanding of the microtopography transformation with frictional nonlinearity at a low-speed heavy-load interface with graphite powder lubrication.

The current study aims to map the scientific output of grey literature (GL) through bibliometric approaches.

The source for data extraction is a comprehensive “indexing and abstracting” database, “Web of Science” (WOS). A lexical title search was applied to get the corpus of the study – a total of 4,599 articles were extracted for data analysis and visualisation. Further, the data were analysed by using the data analytical tools, R-studio and VOSViewer.

The findings showed that the “publications” have substantially grown up during the timeline. The most productive phase (2018–2021) resulted in 47% of articles. The prominent sources were PLOS One and NeuroImage. The highest number of papers were contributed by Haddaway and Kumar. The most relevant countries were the USA and UK.

The study is useful for researchers interested in the GL research domain. The study helps to understand the evolution of the GL to provide research support further in this area.

The present study provides a new orientation to the scholarly output of the GL. The study is rigorous and all-inclusive based on analytical operations like the research networks, collaboration and visualisation. To the best of the authors' knowledge, this manuscript is original, and no similar works have been found with the research objectives included here.

This paper aims to investigate the use of big data (BDU) in predicting technological innovation, supply chain and SMEs' performance and whether technological innovation mediates the association between BDU and firm performance. Additionally, this research also seeks to explore the moderating effect of information sharing in the association between BDU and technological innovation.

Using survey methods and structural associations in AMOS 24.0., the proposed model was tested on SME managers recruited from the largest economic and manufacturing hub of China, Pearl River Delta.

The findings suggest that BDU is positively related to technological innovation (product and process) and organizational outcomes (e.g., supply chain and SMEs performance). Technological innovation (i.e., product and process) significantly mediates the association between BDU and organizational outcomes. Moreover, information sharing positively moderates the association between BDU and technological innovations.

This research provides deeper insights into how BDU is useful for SME managers in achieving the firm’s goals. Particularly, SME managers can bring technological innovation into their business processes, overcome the challenges of forecasting, and generate dynamic capabilities for attaining the best SMEs’ performance. Additionally, BDU with information sharing enables SMEs reduce their risk and decrease production costs in their manufacturing process.

Firms always need to adopt new ways to enhance their productivity using available resources. This is the first study that contributes to big data and performance management literature by exploring the moderating and mediation mechanism of information sharing and technological innovation respectively using RBVT. The study and research model enhances our insights on BDU, information sharing, and technological innovation as valuable resources for organizations to improve supply chain performance, which subsequently increases SME productivity. This gap was overlooked by previous researchers in the domain of big data.

Open-access repositories (OARs) are essential for openly disseminating intellectual knowledge on the internet and providing free access to it. The current study aims to evaluate the growth and development of OARs in the field of technology by investigating several characteristics such as coverage, OA policies, software type, content type, yearly growth, repository type and geographic contribution.

The directory of OARs acts as the source for data harvesting, which provides a quality-assured list of OARs across the globe.

The study found that 125 nations contributed a total of 4,045 repositories in the field of research, with the USA leading the list with the most repositories. Maximum repositories were operated by institutions having multidisciplinary approaches. The DSpace and Eprints were the preferred software types for repositories. The preferred upload content by contributors was “research articles” and “electronic thesis and dissertations”.

The study is limited to the subject area technology as listed in OpenDOAR; therefore, the results may differ in other subject areas.

The work can benefit researchers across disciplines and, interested researchers can take this study as a base for evaluating online repositories. Moreover, policymakers and repository managers could also get benefitted from this study.

The study is the first of its kind, to the best of the authors’ knowledge, to investigate the repositories of subject technology in the open-access platform.