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Smart farming technologies (SFTs) can increase yields and reduce the environmental impacts of farming by improving the efficient use of inputs. This paper is to estimate farmers' preference and willingness to pay (WTP) for a well-defined SFT, smart drip irrigation (SDI) technology.

This study conducted a discrete choice experiment (DCE) among 1,300 maize farmers in North China to understand their WTP for various functions of SDI using mixed logit (MIXL) models.

The results show that farmers have a strong preference for SDI in general and its specific functions of smart sensing and smart control. However, farmers do not have a preference for the function of region-level agronomic planning. Farmers' preferences for different functions of SDI are heterogeneous. Their preference was significantly associated with their education, experience of being village cadres and using computers, household income and holding of land and machines. Further analysis show that farmers' WTP for functions facilitated by hardware is close to the estimated prices, whereas their WTP for functions wholly or partially facilitated by software is substantially lower than the estimated prices.

Findings from the empirical study lead to policy implications for enhancing the design of SFTs by integrating software and hardware and optimizing agricultural extension strategies for SFTs with digital techniques such as videos.

This study provides initial insights into understanding farmers' preferences and WTP for specific functions of SFTs with a DCE.

This study explores challenges facing the applicability of deep learning (DL) in software-defined networks (SDN) based campus networks. The study intensively explains the automation problem that exists in traditional campus networks and how SDN and DL can provide mitigating solutions. It further highlights some challenges which need to be addressed in order to successfully implement SDN and DL in campus networks to make them better than traditional networks.

The study uses a systematic literature review. Studies on DL relevant to campus networks have been presented for different use cases. Their limitations are given out for further research.

Following the analysis of the selected studies, it showed that the availability of specific training datasets for campus networks, SDN and DL interfacing and integration in production networks are key issues that must be addressed to successfully deploy DL in SDN-enabled campus networks.

This study reports on challenges associated with implementation of SDN and DL models in campus networks. It contributes towards further thinking and architecting of proposed SDN-based DL solutions for campus networks. It highlights that single problem-based solutions are harder to implement and unlikely to be adopted in production networks.

In the continuous development of high-speed railways, ensuring the safety of the operation control system is crucial. Electromagnetic interference (EMI) faults in signaling equipment may cause transportation interruptions, delays and even threaten the safety of train operations. Exploring the impact of disturbances on signaling equipment and establishing evaluation methods for the correlation between EMI and safety is urgently needed.

This paper elaborates on the necessity and significance of studying the impact of EMI as an unavoidable and widespread risk factor in the external environment of high-speed railway operations and continuous development. The current status of research methods and achievements from the perspectives of standard systems, reliability analysis and safety assessment are examined layer by layer. Additionally, it provides prospects for innovative ideas for exploring the quantitative correlation between EMI and signaling safety.

Despite certain innovative achievements in both domestic and international standard systems and related research for ensuring and evaluating railway signaling safety, there’s a lack of quantitative and strategic research on the degradation of safety performance in signaling equipment due to EMI. A quantitative correlation between EMI and safety has yet to be established. On this basis, this paper proposes considerations for research methods pertaining to the correlation between EMI and safety.

This paper overviews a series of methods and outcomes derived from domestic and international studies regarding railway signaling safety, encompassing standard systems, reliability analysis and safety assessment. Recognizing the necessity for quantitatively describing and predicting the impact of EMI on high-speed railway signaling safety, an innovative approach using risk assessment techniques as a bridge to establish the correlation between EMI and signaling safety is proposed.

Information and communication technologies (ICT) are indispensable tools for Knowledge Management (KM) practices in today’s knowledge-intensive and globally interconnected marketplace. This paper seeks to investigate the impact of family ownership on ICT investments in an emerging economy (EE) context.

This empirical paper uses data from 300 large Indian listed firms with 2,650 observations in the period 2008–2017, to test its hypothesis.

The results indicate that family firms are not favourably inclined towards ICT investments for formalizing their KM practices. However, under certain contexts, such as higher foreign institutional ownership or business group affiliation, they are more willing to invest in ICT resources.

This study establishes a nuanced understanding of how family firms approach ICT investments and KM practices. This research can help family owners/managers to commit sufficient resources on ICT projects.

Literature on KM has largely emanated from developed countries. This is one of the first papers from an EE context that studies the impact of family ownership on ICT investments and subsequent KM practices. In this way, this paper offers specific insights into the context of Indian family firms and offers some interesting findings that can contribute to the literature, policy and practice.

The article aims to identify the association between each smart home service category's benefits and barriers to their adoption. The results seek to identify efficient approaches that motivate users to adopt smart homes services and support suppliers to establish strategies to expand and optimize smart home technologies.

The research used the chi-square test of independence to reveal the association between the benefits and barriers perceived by the users during smart home services implementation. Furthermore, the statistical analysis using reliable evidence based on 122 articles reported in the literature provides valuable knowledge for smart home implementation.

The results reveal which barriers and benefits in the smart home are essential for implementing each type of service. Therefore, the association between barriers and benefits with smart home services implementation can support the dissemination of smart home technologies.

The article provides evidence to develop strategies for implementing smart home services, supporting companies with guidelines to be more assertive in disseminating smart homes technologies.

Using the literature as a data source and raising the associations through the chi-square test of independence, the methodology provides a high level of generalization and strong evidence regarding the association of smart home benefits or barriers associated with every smart home service.

Nations are opening their “digital borders” to allow the free movement of business, employment and skills. However, this process of digitalization is fraught with challenges. This study aims to identify these challenges to build a solution-oriented framework for smart nations.

This study conducted a systematic literature review, analyzing 69 peer-reviewed academic papers out of 5,958 identified papers.

The identified challenges for smart nation building were categorized as follows: people and society, technology and innovation, digital infrastructure, politics, governance, economics and business and sustainability. To overcome these challenges, this study highlights the need for a holistic national approach, which includes solutions such as improving education, technology-driven innovations, investments for building smart nation infrastructure, top political leadership involvement, national vision and action plan, national regulatory frameworks, business environment and job creation, stakeholder engagement, renewable energy use and technological integration – all of which are key for sustainable development.

This study provides directions for building a smart nation framework, but the literature review results are confined to articles, conference papers and book chapters. This study could be further enriched if the findings are cross-checked with experts. This limitation will be addressed in future research.

Given the dearth of literature on this nascent concept, the insights from this study can guide policymakers and industry leaders involved in smart nation building and benefit researchers engaged in theoretical development.

Sex and age estimation is important, particularly when information about the deceased is unavailable. There are limited radiological studies investigating side, sex and age differences in normal ankle morphometric parameters. The authors’ goal was to evaluate different ankle joint morphometric measurements and document variations among Egyptians.

A prospective study was conducted throughout 23 months on 203 (100 males and 103 females) adult Egyptians, aged between 20-69 years old, who were referred for a plain x-ray of bilateral normal ankle joints.

Ankle parameters showed no statistical difference between both sides, except for tarsal width (TaW) which was significantly higher on right than left side (26.92 ± 2.66 vs 26.18 ± 2.65 mm). Males showed significantly higher morphometric values except for anteroposterior gap (APG) and talus height (TaH) which were significantly higher in females (2.29 ± 0.80 vs 1.80 ± 0.61 mm and 13.01 ± 1.68 vs 11.87 ± 1.91 mm, respectively). There was significant increase in tibial arc length, APG, distance of level of MTiTh from anterior limit of mortise, distance of level of MTiTh from vertex of mortise, sagittal distance between tibial and talar vertices and sagittal radius of trochlea tali arc in old age group compared to young one. A significant decrease in tibial width, malleolar width, TaW and TaH was noted in old age group compared to young one.

Ankle joints of both sides are mostly symmetrical; however, there are significant differences in most morphometric values due to sex and age factors. These findings may be essential during side, sex and age determination.

In today's fast developing era, the volume of data is increasing day by day. The traditional methods are lagging for efficiently managing the huge amount of data. The adoption of machine learning techniques helps in efficient management of data and draws relevant patterns from that data. The main aim of this research paper is to provide brief information about the proposed adoption of machine learning techniques in different sectors of manufacturing supply chain.

This research paper has done rigorous systematic literature review of adoption of machine learning techniques in manufacturing supply chain from year 2015 to 2023. Out of 511 papers, 74 papers are shortlisted for detailed analysis.

The papers are subcategorised into 8 sections which helps in scrutinizing the work done in manufacturing supply chain. This paper helps in finding out the contribution of application of machine learning techniques in manufacturing field mostly in automotive sector.

The research is limited to papers published from year 2015 to year 2023. The limitation of the current research that book chapters, unpublished work, white papers and conference papers are not considered for study. Only English language articles and review papers are studied in brief. This study helps in adoption of machine learning techniques in manufacturing supply chain.

This study is one of the few studies which investigate machine learning techniques in manufacturing sector and supply chain through systematic literature survey.

1. A comprehensive understanding of Machine Learning techniques is presented.

2. The state of art of adoption of Machine Learning techniques are investigated.

3. The methodology of (SLR) is proposed.

4. An innovative study of Machine Learning techniques in manufacturing supply chain.

A comprehensive understanding of Machine Learning techniques is presented.

The state of art of adoption of Machine Learning techniques are investigated.

The methodology of (SLR) is proposed.

An innovative study of Machine Learning techniques in manufacturing supply chain.

Agile principles have been widely used in software development team practice since the creation of the Agile Manifesto. Studies have examined variables related to agile principles without systematically considering the relationships among key team, agile methodology, and process variables underlying the agile principles and how these variables jointly influence the achievement of software development agility. In this study, the authors tested a team/methodology–process–agility model that links team variables (team autonomy and team competence) and methodological variable (iterative development) to process variables (communication and collaborative decision-making), which are in turn linked to software development agility (ability to sense, respond and learn).

Survey data from one hundred and sixty software development professionals were analyzed using structural equation modeling methods.

The results support the team/methodology–process–agility model. Process variables (communication and collaborative decision-making) mediated the effects of team (autonomy and competence) and methodological (iterative development) variables on software development agility. In addition, team, methodology and process variables had different effects on the three dimensions of software development agility.

The results contribute to the literature on organizational IT management by establishing a team/methodology–process–agility model that can serve as a basis for developing a core theoretical foundation underlying agile principles and practices. The results also have practical implications for organizations in understanding and managing holistically the different roles that agile methodological, team and process factors play in achieving software development agility.

This article explores how the social media usage affect team creative performance via transactive memory system, knowledge interaction and expertise coordination.

The study is based on the perspective of transaction memory system and expertise coordination theory. A research model was constructed and tested, involving 289 individuals from 67 distributed agile software development teams.

The results indicate that social media usage is positively correlated with transactive memory system, and social media usage and transactive memory system have positive relations to knowledge interaction and expertise coordination. Moreover, this analysis shows that knowledge interaction has a positive relationship with expertise coordination, and expertise coordination positively affects team creative performance. However, knowledge interaction has no direct relationship on team creative performance, and its indirect impact on team creative performance was fully mediated by expertise coordination. This research shows that social media usage by distributed agile software development teams can support the development of transactive memory system and promote expertise coordination. In addition, knowledge interaction alone is not enough, and expertise coordination must be achieved to increase team creative performance.

First, this paper explores the mechanism of transactive memory system in distributed Agile Software Development teams from the perspective of social media, which is different from the previous information processing theory framework that confined transactive memory system to the cognitive aspects of knowledge coding, storage and retrieval. Second, this research focuses on the knowledge interaction and expertise coordination formed by team members in the process of communication in the context of social media usage, which confirms the crucial roles of social media usage and transactive memory system in team knowledge management and team creative performance. Then, this research also shows that the development of transactive memory system in the team is indeed an important factor to promote knowledge interaction and professional expertise coordination.