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Wireless sensor networks (WSN), as a solution for buried water pipe monitoring, face a new set of challenges compared to traditional application for above-ground infrastructure monitoring. One of the main challenges for underground WSN deployment is the limited range (less than 3 m) at which reliable wireless underground communication can be achieved using radio signal propagation through the soil. To overcome this challenge, the purpose of this paper is to investigate a new approach for wireless underground communication using acoustic signal propagation along a buried water pipe.

An acoustic communication system was developed based on the requirements of low cost (tens of pounds at most), low power supply capacity (in the order of 1 W-h) and miniature (centimetre scale) size for a wireless communication node. The developed system was further tested along a buried steel pipe in poorly graded SAND and a buried medium density polyethylene (MDPE) pipe in well graded SAND.

With predicted acoustic attenuation of 1.3 dB/m and 2.1 dB/m along the buried steel and MDPE pipes, respectively, reliable acoustic communication is possible up to 17 m for the buried steel pipe and 11 m for the buried MDPE pipe.

Although an important first step, more research is needed to validate the acoustic communication system along a wider water distribution pipe network.

This paper shows the possibility of achieving reliable wireless underground communication along a buried water pipe (especially non-metallic material ones) using low-frequency acoustic propagation along the pipe wall.

FinTech offers numerous prospects for significant enhancements and fundamental changes in financial services. However, along with the myriad of benefits, it also has the potential to induce risks to individuals, organisations and society. This study focuses on understanding FinTech developers’ perspective of the dark side of FinTech.

This study conducted semi-structured interviews with 23 Nigerian FinTech developers using an exploratory, inductive methodology The data were transcribed and then thematically analysed using NVivo.

Three themes – customer vulnerability, technical inability and regulatory irresponsibility – arose from the thematic analysis. The poor existing technological infrastructure, data management challenges, limited access to data and smartphone adoption pose challenges to a speedy integration of FinTech in the country, making customers vulnerable. The lack of privacy control leads to ethical issues. The lack of skilled developers and the brain drain of good developers present additional obstacles to the development of FinTech in Nigeria.

FinTech operation in a developing country differs from that in developed countries with better technological infrastructure and institutional acceptance. This study recognises that basic banking operations through FinTech are still not well adopted, necessitating the need to be more open-minded about the global practicalities of FinTech.

FinTech managers, banks and policymakers can ethically collect consumer data that can help influence customer credit decisions, product development and recommendations using the mobile app and transaction history. There should be strict penalties on FinTech for selling customers’ data, sending unsolicited messages or gaining unnecessary access to the customer’s contact list. FinTech can offer to educate consumers about their financial management skills.

Whereas other studies have focused on the positive aspects of FinTech to understand client perceptions, this study offers new insights into the dark side of FinTech by analysing the viewpoints of FinTech developers. Furthermore, the study is based in Nigeria, an emerging economy adopting FinTech, adding a new dimension to the body of knowledge.

Effective use of data is critically important for the provision of health services. A large proportion of employees in health organisations work in non-clinical roles and play a major part in organisational information flows. However, their practice, data-related capabilities and learning needs have been rarely studied. The purpose of this paper is to investigate issues of capabilities and learning needs related to employees' interactions with data in non-clinical work roles.

The study used a mixed-method approach. Qualitative methods were used to explore issues, and survey was administered to gather additional data.

Data use and related capabilities at the workplace are highly contextual. A range of general, core and data-specific capabilities, underpinned by transferable skills and personal traits, enable successful interactions with data. Continuous learning is needed in most areas related to data use.

The study was conducted in a large public-health organisation in Australia, which is not representative of unique organisations elsewhere. The study has implications for the provision of health services, workplace learning and education.

Findings have implications for organisational decisions related to data-use and workplace learning, and for formal education and lifelong learning.

The study contributes to closing a research gap in understanding interactions with data, capabilities and learning needs of employees in non-clinical work roles. Capabilities continuum presented in this paper can be used to inform education, training and service provision. The workplace-based results contribute to theoretical considerations of capabilities required for work in technology-rich environments.

Environmental degradation resulting from human activities may adversely affect human health in multiple ways. Until now, policies aimed at mitigating environmental problems such as climate change, environmental pollution and damage to biodiversity have failed to clearly identify and drive the potential benefits of these policies on health. The conducted study assesses and demonstrates how specific environmental policies and instruments influence perceived human health in order to ensure input for a data-driven decision process.

The study was conducted for the 2004–2020 period in European Union (EU) countries with the use of dynamic panel data modeling. Verification of specific policies' impact on dependent variables allows to indicate this their effectiveness and importance. As a result of the computed dynamic panel data models, it has been confirmed that a number of significant and meaningful relationships between the self-perceived health index and environmental variables can be identified.

There is a strong positive impact of environmental taxation on the health index, and the strength of this relationship causes effects to be observed in the very short term, even the following year. In addition, the development of renewable energy sources (RES) and the elimination of fossil fuels from the energy mix exert positive, although milder, effects on health. The reduction of ammonia emissions from agriculture and reducing noise pollution are other health-supporting factors that have been shown to be statistically valid. Results allow to identify the most efficient policies in the analyzed area in order to introduce those with the best results or a mix of such measures.

The results of the authors' research clearly indicate the health benefits of measures primarily aimed at improving environmental factors, such as environmental taxes in general. The authors have also discovered an unexpected negative impact of an increase in the share of energy taxes in total taxes on the health index. The presented study opens several possibilities for further investigation, especially in the context of the rapidly changing geopolitical environment and global efforts to respond to environmental and health challenges. The authors believe that the outcome of the authors' study may provide new arguments to policymakers pursuing solutions that are not always easily acceptable by the public.

In recent years, there has been a growing interest in the potential of data analytics to enhance project delivery. Yet many argue that its application in projects is still lagging behind other disciplines. This paper aims to provide a review of the current use of data analytics in project delivery encompassing both academic research and practice to accelerate current understanding and use this to formulate questions and goals for future research.

We propose to achieve the research aim through the creation of a systematic review of the status of data analytics in project delivery. Fusing the methodology of integrative literature review with a recently established practice to include both white and grey literature amounts to an approach tailored to the state of the domain. It serves to delineate a research agenda informed by current developments in both academic research and industrial practice.

The literature review reveals a dearth of work in both academic research and practice relating to data analytics in project delivery and characterises this situation as having “more gap than knowledge.” Some work does exist in the application of machine learning to predicting project delivery though this is restricted to disparate, single context studies that do not reach extendible findings on algorithm selection or key predictive characteristics. Grey literature addresses the potential benefits of data analytics in project delivery but in a manner reliant on “thought-experiments” and devoid of empirical examples.

Based on the review we articulate a research agenda to create knowledge fundamental to the effective use of data analytics in project delivery. This is structured around the functional framework devised by this investigation and highlights both organisational and data analytic challenges. Specifically, we express this structure in the form of an “onion-skin” model for conceptual structuring of data analytics in projects. We conclude with a discussion about if and how today’s project studies research community can respond to the totality of these challenges. This paper provides a blueprint for a bridge connecting data analytics and project management.

In recent years, environmental issues and resource depletion have posed significant challenges to firms and society. To address these environmental challenges, firms seek to build strategic alliances of green supply chain management (GSCM) with their supply chain partner. As the largest developing country in the Asia–Pacific region, China needs to take more responsibility for environmental protection, which requires more Chinese firms to participate in GSCM. Therefore, focusing on the issue of GSCM and innovation persistence in the context of an increasingly harsh ecological environment is essential.

To test the hypothesis, the authors perform an empirical analysis on a sample of 124 listed firms in China from 2014 to 2019. The results are robust to a battery of robustness analyses the authors performed to take care of endogeneity.

Empirical results indicate that GSCM can promote innovation persistence and both market environment turbulence and technology environment turbulence have a positive moderating effect on the relationship between the two. Mechanism tests show that GSCM can improve innovation efficiency, ensure innovation quality and alleviate financing constraints, thus promoting the innovation persistence of firms.

This study can provide a theoretical basis for the country to promote GSCM orientation, raise firms' awareness of the value of GSCM, convey the significance of GSCM to investors, influence firms' investment decisions and give experience to other developing countries.

The purpose of the article was to identify the core dimensions of strategic thinking and create a measure that provides a comprehensive operationalization of the construct.

The construct validity of the measure was assessed in two studies using four samples with a total of 985 participants. The measure was created using a multi-step process that included item development and content validation, exploratory and confirmatory factor analysis, convergent and discriminant validity, criterion validity and test-retest validity.

The exploratory factor analysis (EFA) supported the existence of the three dimensions of strategic thinking (visionary, synthetic and creative thinking) as conceptually proposed. The measure was reduced to nine items. The confirmatory factor analysis (CFA) confirmed the three dimensions and revealed acceptable factor loadings and model fit. Convergent, discriminant and criterion validity were established, and the measure demonstrated acceptable test-retest reliability.

An individual's ability to think strategically is vital for making strategic decisions and relevant to upper echelon theory and strategic management. The definition and core dimensions of strategic thinking are unclear in the literature, creating confusion. This study added to the literature by defining the core dimensions of strategic thinking and developing the strategic thinking assessment (STA) to measure the construct.

The tender documents, an essential data source for internet-based logistics tendering platforms, incorporate massive fine-grained data, ranging from information on tenderee, shipping location and shipping items. Automated information extraction in this area is, however, under-researched, making the extraction process a time- and effort-consuming one. For Chinese logistics tender entities, in particular, existing named entity recognition (NER) solutions are mostly unsuitable as they involve domain-specific terminologies and possess different semantic features.

To tackle this problem, a novel lattice long short-term memory (LSTM) model, combining a variant contextual feature representation and a conditional random field (CRF) layer, is proposed in this paper for identifying valuable entities from logistic tender documents. Instead of traditional word embedding, the proposed model uses the pretrained Bidirectional Encoder Representations from Transformers (BERT) model as input to augment the contextual feature representation. Subsequently, with the Lattice-LSTM model, the information of characters and words is effectively utilized to avoid error segmentation.

The proposed model is then verified by the Chinese logistic tender named entity corpus. Moreover, the results suggest that the proposed model excels in the logistics tender corpus over other mainstream NER models. The proposed model underpins the automatic extraction of logistics tender information, enabling logistic companies to perceive the ever-changing market trends and make far-sighted logistic decisions.

(1) A practical model for logistic tender NER is proposed in the manuscript. By employing and fine-tuning BERT into the downstream task with a small amount of data, the experiment results show that the model has a better performance than other existing models. This is the first study, to the best of the authors' knowledge, to extract named entities from Chinese logistic tender documents. (2) A real logistic tender corpus for practical use is constructed and a program of the model for online-processing real logistic tender documents is developed in this work. The authors believe that the model will facilitate logistic companies in converting unstructured documents to structured data and further perceive the ever-changing market trends to make far-sighted logistic decisions.

Sustainability has emerged as a key concept in 21st-century education. The purpose of this paper is to identify faculty’s behavior and barriers to incorporating sustainability in business school classrooms and suggest potential ways to tackle them.

This study uses focus groups and interviews with faculty at a European business school using the theory of planned behavior (TPB) to explore their beliefs and practices in incorporating sustainability in the classroom.

The results show that business school faculty have a strong awareness of sustainability and a desire to incorporate it into the classrooms. Recommendations for deans and curriculum creators are proposed to reduce obstacles to successful implementation.

The perceptions of faculty, a key agent of change in the incorporation of sustainability in the classroom, are analyzed, and practical steps to support them are suggested through the use of a TPB framework.

This study offers a structured literature review (SLR) on female digital entrepreneurship (DE). This is done by providing insights into the recent developments of the topic, reviewing and critiquing previous studies in the literature, and pinpointing areas for future potential studies.

A comprehensive SLR was conducted on 18 papers published between 2017 and 2022 by discipline, time, methodologies, context, topic, and theoretical emphasis. The authors employed the three phases of critical research – insight, critique, and transformative redefinition – to conduct the literature review.

The literature on female DE is inadequate, fragmented, and divergent in terms of less practice-based insights. Furthermore, most female DE research is published in nonspecialized journals. The examination of the impact of gender and cross-country comparative studies is scarce. Existing literature lacks epistemological and methodological diversity. The lack of theoretical connections across the various research areas on female entrepreneurship may be the reason why this area of study has proven difficult for scholars. Few authors exhibit high specialization in the topic, whereas most authors contribute to either DE or female entrepreneurship.

This SLR research aims to provide an overview of the female DE field by identifying the current trend of research and recognizing future research directions and to improve readers’ knowledge of this research branch.

This review has classified the field's main topics and found that the influence of context (institutional and social) is the most investigated issue. Further, it presents a potential for practitioners' contribution to the field as coauthors and outlines needed studies.

This study provides a comprehensive, cross-disciplinary, updated review and research agenda that supplements rather than substitutes the existing literature reviews on female entrepreneurship. Moreover, this study makes a significant contribution by presenting the stages of development in female DE research within the context of the overall literature on female entrepreneurship.