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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.

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.

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.

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.

Controlled release systems are an efficient alternative for the effective use of agricultural supplies. Among the most versatile controlled release systems are intelligent or stimulus-sensitive polymeric materials, since these materials are multipurpose and adaptable alternatives that offer great adaptability for agricultural applications. The objective of this work was to develop stimulus-sensitive polyurethanes (PUs) based on cationic aminoglycosides (CAG) to be used as an active phase for the manufacture of systems for the controlled release of phytohormones such as naphthalene acetic acid (NAA).

The synthesis of stimulus-sensitive PUs was carried out by a polycondensation reaction using CAGs and methylene diphenyl isocyanate (MDI) as precursors. The NAA retention and release experiments were performed at different pH values and ionic forces to include the acidity and salinity of agricultural soils.

The results demonstrate that PUs can be obtained from CAG and MDI using the one-step method. The retention of NAA increased as the CAG content increased in the polymer structure, while it is seen that the effect of pH is weak compared to the effect of ionic strength. On the other hand, the release of NAA from cationic PUs can be accomplished by small changes in ionic strength that are mainly affected by the composition of the PU and the pH. The results suggest that, for developed systems, retention and release of NAA is affected by other interaction mechanisms that could probably be related to p-aromatic interactions.

Findings are limited to controlled conditions and the expanding of results to extensive crops should be analyzed in next research studies.

The practical implications of this study are improving of control for the dosage of phytohormones in stake propagation crops, greenhouse crops, optimization of reseeding operations, among others.

The social implication of this study is reduction of pollution by addition of excess of NAA, in consequence, production costs are decreased.

Originality and value of this research is the use of PUs based on CAG, and in consequence, the possibility to build novel environment-friendly systems for phytohormone dosage.

The purpose of this paper is to enhance the characteristics of TiO₂ nanoparticles (NPs). Because these NPs stick together easily and are difficult to distribute evenly, they cannot be used extensively in lubricating oils. Altering TiO₂ was recommended as an alternate way for making NPs simpler to disperse.

Through dielectric barrier discharge plasma (DBDP)-assisted ball mill diagnostics and modeling of molecular dynamics, TiO₂@PEG-400 NPs were produced using the DBDP-assisted ball mill. The NPs’ microstructure was examined using FESEM, TEM, XRD, FT-IR and TG-DSC. Using the CFT-1 reciprocating friction tester, the tribological properties of TiO₂@PEG-400 NPs as base oil additives were studied. EDS and XPS were used to examine the surface wear of the friction pair.

Tribological properties of the modified NPs are vastly superior to those of the original NPs, and the lipophilicity value of TiO₂ NPs was improved by 200%. It was determined through tribological testing that TiO₂@PEG-400’s exceptional performance might be attributable to a chemical reaction film made up of TiO₂, Fe₂O₃, iron oxide and other organic chemicals.

This work describes an approach for preventing the aggregation of TiO₂ NPs by coating their surface with PEG-400. In addition, the prepared NPs can enhance the tribological performance of lubricating oil. This low-cost, high-performance lubricant additive has tremendous promise for usage in marine engines to minimize operating costs while preserving navigational safety.

In community question answering (CQA), people who answer questions assume readers have mastered the content in the answers. Nevertheless, some readers cannot understand all content. Thus, there is a need for further explanation of the concepts that appear in the answers. Moreover, the large number of question and answer (Q&A) documents make manual retrieval difficult. This paper aims to alleviate these issues for CQA websites.

In the paper, an algorithm for recommending explanatory Q&A documents is proposed. Q&A documents are modeled with the biterm topic model (BTM) (Yan et al., 2013). Then, the growing neural gas (GNG) algorithm (Fritzke, 1995) is used to cluster Q&A documents. To train multiple classifiers, three features are extracted from the Q&A categories. Thereafter, an ensemble classification model is constructed to identify the explanatory relationships. Finally, the explanatory Q&A documents are recommended.

The GNG algorithm shows good clustering performance. The ensemble classification model performs better than other classifiers. The both effect and quality scores of explanatory Q&A recommendations are high. These scores indicate the practicality and good performance of the proposed recommendation algorithm.

The proposed algorithm alleviates information overload in CQA from the new perspective of recommending explanatory knowledge. It provides new insight into research on recommendations in CQA. Moreover, in practice, CQA websites can use it to help retrieve Q&A documents and facilitate understanding of their contents. However, the algorithm is for the general recommendation of Q&A documents which does not consider individual personalized characteristics. In future work, personalized recommendations will be evaluated.

A novel explanatory Q&A recommendation algorithm is proposed for CQA to alleviate the burden of manual retrieval and Q&A overload. The novel GNG clustering algorithm and ensemble classification model provide a more accurate way to identify explanatory Q&A documents. The method of ranking the explanatory Q&A documents improves the effectiveness and quality of the recommendation. The proposed algorithm improves the accuracy and efficiency of retrieving explanatory Q&A documents. It assists users in grasping answers easily.

The study investigates the impact of information and communications technology (ICT) and financial development on tourism development in Ghana.

The researchers employ data covering from 1995Q1 to 2020Q4 and apply the autoregressive distributed lag (ARDL) estimation technique.

The findings reveal that ICT exerts a positive significant impact on tourism development in both long- and short-term periods. The authors find that financial development has a negative significant effect on tourism development in the long run. However, financial development significantly increases tourism revenue in the short term. The results further reveal a significant positive link between infrastructure development and tourism receipts in the long run.

This study is a pioneering effort to investigate the impact of ICT and financial development on tourism development in Ghana, as far as the researchers are aware. Additionally, the use of an index of ICT adds novelty to the literature. In terms of policy, the findings of this study can inform policymakers on the importance of investing in ICT and financial development to boost the tourism industry in Ghana.