We propose that technological, service-dominant and design logics must interplay for an IT artefact to succeed. Based on data from a project aiming at a B2B platform for manufacturing small and medium enterprises (SMEs) in Europe, we explore these three logics in an agile software design context. By using an inductive approach, we theorise about what is needed for the alignment of the three logics. We contribute with a novel theoretical lens, the Framework for Adaptive Space. We offer insights into the importance of continuously reflecting on all three logics during the agile software design process to ensure mutual understanding among the agile team and the B2B platform end-users involved.

Along with amazing advancements in the field of digital payments, this article seeks to provide a summary of research undertaken over the last four decades and to suggest areas in need of additional study. This study employs a two-pronged technique for analysing its data. The first is concerned with performance analysis, and the second with science mapping. The study uses the apps VOS viewer and R-studio to do bibliometric data analysis. From 1982 until May 2022, the most trustworthy database, Scopus, is used to compile a database of 923 publications The findings of this study identify the scope of current research interest, which is explored with critical contributions from a variety of authors, journals, countries, affiliations, keyword analysis, citation analysis, co-citation analysis, and bibliometric coupling, as well as a potential research direction for further investigation in this emerging field.

The utilisation of big data presents significant opportunities for businesses to create value and gain a competitive edge. This capability enables firms to anticipate and uncover information quickly and intelligently. The author introduces a human resource scheduling optimisation strategy using a parallel network fusion structure model. The author's approach involves designing a set of network structures based on parallel networks and streaming media, enabling the macro implementation of the enterprise parallel network fusion structure. Furthermore, the author proposes a human resource scheduling optimisation method based on a parallel deep learning network fusion structure. It combines convolutional neural networks and transformer networks to fuse streaming media features, thereby achieving comprehensive identification of the effectiveness of the current human resource scheduling in enterprises. The result shows that the macro and deep learning methods achieve a recognition rate of 87.53%, making it feasible to assess the current state of human resource scheduling in enterprises.

In the context of smart city development, the managed pressure drilling (MPD) drilling process faces many uncertainties, but the characteristics of the process are complex and require accurate wellbore pressure control. However, this process runs the risk of introducing un-modelled dynamics into the system. To this problem, this paper employs neural network control techniques to construct a dual-network system for throttle pressure control, the design encompasses both the controller and identifier components. The radial basis function (RBF) network and proportional features are connected in parallel in the controller structure, and the RBF network learning algorithm is used to train the identifier structure. The simulation results show that the actual wellbore pressure can quickly track the reference pressure value when the pressure setpoint changes. In addition, the controller based on neural network realises effective control, which enables the system to track the input target quickly and achieve stable convergence.

In order to reduce the challenges encountered by learners and educators in engaging in educational activities, this paper classifies learners' roles in virtual learning communities, and explores the role of behaviour characteristics and their positions in collaborative knowledge construction networks in promoting the process of knowledge construction. This study begins with an analysis of the relationship structure among learners in the virtual learning community and then applies the FCM algorithm to arrange learners into various dimensional combinations and create distinct learning communities. The test results demonstrate that the FCM method performs consistently during the clustering process, with less performance oscillations, and good node aggregation, the ARI value of the model is up to 0.90. It is found that they play an important role in the social interaction of learners' virtual learning community, which plays a certain role in promoting the development of artificial intelligence.

This article studies the application of artificial intelligence technology in natural resource planning and management. This article first introduces the background of NR and AI intelligent technology, then conducts academic research and summary on NR planning management and AI intelligent technology. Then, an algorithm model based on multi-objective intelligent planning algorithm is established. Finally, simulation experiments are conducted, and experiments summary and discussion are provided. The experimental results show that the average efficiency value of the four stages of NR planning and management before use is 5.25, and the average efficiency value of the four stages of NR planning and management after use is 7. The difference in the average efficiency value before and after use is 1.75. It can be seen that the use of AI intelligent technology can effectively improve the efficiency of natural resource planning and management.

As IOT develops drastically these years, the application of cloud computing in many fields has become possible. In this paper, we take low-voltage current transformers in power systems as the research object and propose a TCN-BI-GRU power measurement method that incorporates the signal characteristics based on the transformer input and output. Firstly, the basic signal enhancement extraction of input and output is completed by using EMD and correlation coefficients. Secondly, multi-dimensional feature extraction is completed to improve the data performance according to the established TCN network. Finally, the power prediction is completed by using BI-GRU, and the results show that the RMSE of this framework is 5.69 significantly lower than other methods. In the laboratory test, the device after being subjected to strong disturbance, its correlation coefficient feature has a large impact, leading to a large deviation in the prediction, which provides a new idea for future intelligent prediction.

Since its birth, the stock market has received widespread attention from many scholars and investors. However, there are many factors that affect stock prices, including the company's own internal factors and the impact of external policies. The extent and manner of fundamental impacts also vary, making stock price predictions very difficult. Based on this, this article first introduces the research significance of the stock market prediction framework, and then conducts academic research and analysis on two key sentences of stock market prediction and artificial intelligence in stock market prediction. Then this article proposes a constructive algorithm theory, and finally conducts a simulation comparison experiment and summarises and discusses the experiment. Research results show that the neural network prediction method is more effective in stock market prediction; the minimum training rate is generally 0.9; the agency's expected dilution rate and the published stock market dilution rate are both around 6%.

Elections hold immense significance in shaping the leadership of a nation or organisation, serving as a pivotal moment that influences the trajectory of the entity involved. Despite their centrality to modern democratic systems, elections face a significant hurdle: widespread mistrust in the electoral process. This pervasive lack of confidence poses a substantial threat to the democratic framework, even in the case of prominent democracies such as India and US, where inherent flaws persist in the electoral system. Issues such as vote rigging, electronic voting machine (EVM) hacking, election manipulation, and polling booth capturing remain prominent concerns within the current voting paradigm. Leveraging blockchain for electronic voting systems offers an effective solution to alleviate the prevailing apprehensions associated with e-voting. By incorporating blockchain into the electoral process, the integrity and security of the system could be significantly strengthened, addressing the current vulnerabilities and fostering trust in democratic elections.

The aim of the study is to examine the determinants of digitalisation in public sector. This research is particularly relevant as digital transformation has become a crucial factor in modernising public sector and enhancing service delivery to citizens. The method of the systematic literature review (SLR) was implemented by searching documents on the Scopus database. The initial research reached the 7902 documents and after specifying the keywords the authors found 207 relevant documents. Finally; after the careful read of their abstracts and the use of inclusion and exclusion criteria; the most cited and relevant 32 papers constituted the final sample. Findings highlighted the focus of the literature on technological factors such as the sense of trust and safety as well as the ease of use in the adoption of digital governance; emphasising the need for effective; trustworthy and user-friendly digital services. The most discussed internal factors were leadership and organisational culture. The study offers a deeper understanding of the factors that shape the successful implementation of digital governance initiatives.

This study investigates the well-being of healthcare professionals in India, with a specific focus on the detrimental effects of the pandemic on their mental and physical health, including stress, burnout, and fatigue. This research examines the roles played by calling, mindfulness, and compassionate love as essential resources in promoting the well-being of healthcare professionals. Utilising structural equation modelling (SEM), the results reveal a significant cause and effect relationship between calling, mindfulness, and compassionate love and their influence on overall well-being. Furthermore, the study identifies a noteworthy parallel mediation effect, demonstrating that mindfulness and compassionate love serve as mediators in the relationship between calling and well-being. This research offers practitioners invaluable insights into the effective utilisation of mindfulness and compassionate love practices to enhance the overall well-being of healthcare professionals.

The study investigated the influence of ebullient supervision on employee commitment in a Ghanaian public university through the mediating role of employee engagement. The simple random sampling technique was used to draw 302 administrative staff of the university to respond to the self-administered questionnaire on the constructs. Furthermore, the partial least square structural equation technique was deployed to test the research hypotheses in the study. The results showed that ebullient supervision had a significant positive relationship with employee commitment and employee engagement. The findings further revealed that employee engagement positively correlated with employee commitment. Finally, the study's findings established that employee engagement partially mediated the link between ebullient supervision and employee commitment. The study emphasised that various supervisors in a university's administration should create an environment that favours fun where subordinates can form ties with one another.

Physical and social aspects each make up a separate part of servicescape. Together, these make up the servicescape. Although previous research has frequently investigated these aspects separately, the purpose of this study is to simultaneously find out the impact of both aspects within the casual dining restaurants' context. In total, 462 customers in Delhi were polled for this study, and structural equation modelling was used to analyse the data. According to the results, both the social and physical parts of the servicescape have the ability to affect how satisfied customers are, which in turn can affect how they behave in the future.

Drawn from technology acceptance model, this study establishes a theoretical framework for the analytical interpretation of factors affecting job-seekers intention to use e-recruitment websites. Using the data obtained from 379 respondents in India, ten hypotheses derived from the experimental model are evaluated using a structural equation modelling technique. Vividness, perceived usefulness (PU), and attitude have been shown to have a significant positive impact on the behavioural intentions (BIs) of job-seekers, although perceived ease of use (PEOU) did not. Furthermore, perceived internet stress (PIS) is observed to be a significant antecedent PEOU; and PEOU is of PU. Such findings broaden our knowledge of e-recruiting in various ways and offer qualitative insights into the potential impact of website functionality on the attractiveness of job-seekers.

Software start-ups generally use development practices that are adapted to their agile and innovative environment. However, these practices, although consolidated, may not be the best ones for a specific context. This paper aims to present a set of guidelines for software development in start-ups. It also aims to show the results of three studies to validate and refine the proposed guidelines: a confirmatory survey, a focus group, and an expert panel. The participants were actors from both the industry and the academia. The results revealed that the guidelines obtained a positive perception from the participants of both contexts. Based on their approval, we can infer that those guidelines can increase the quality of products generated by start-ups and the chances of success for these organisations. Besides, the need for some improvements has been identified, and they will be implemented in the next version of the guidelines.

Disease pandemics, once thought to be historical relics, are now again challenging healthcare systems globally. Of essential importance is sufficiently investing in preparedness and responsiveness, but approaches to such investments vary significantly by country. These variations provide excellent opportunities to learn and prepare for future pandemics. Therefore, we examine digital health infrastructure and the state of healthcare and public health services in relation to pandemic preparedness and responsiveness. The research focuses on two countries: South Africa and the USA. We apply case analysis at the country level toward understanding digital health policy preparedness and responsiveness to a pandemic. We also provide a teaching note at the end for use in guiding students in this area to formulate digital health policy recommendations for pandemic preparedness and responsiveness.

A number of studies have applied social network analysis (SNA) to show that the patterns of social interaction between software developers explain important organisational outcomes. However, these insights are based on a single network relation (i.e., uniplex social ties) between software developers and do not consider the multiple network relations (i.e., multiplex social ties) that truly exist among project members. This study reassesses the understanding of software developer networks and what it means for performance in software development settings. A systematic review of SNA studies between 1990 and 2020 across six digital libraries within the IS and management science domain was conducted. The central contributions of this paper are an in-depth overview of SNA studies to date and the establishment of a research agenda to advance our knowledge of the concept of multiplexity on how a multiplex perspective can contribute to a software developer's coordination of tasks and performance advantages.

The supply chains of the Canadian forest products industry are largely dependent on accurate demand forecasts. The USA is the major export market for the Canadian forest products industry, although some Canadian provinces are also exporting forest products to other global markets. However, it is very difficult for each province to develop accurate demand forecasts, given the number of factors determining the demand of the forest products in the global markets. We develop multi-layer feed-forward artificial neural network (ANN) models for demand forecasting of the Canadian forest products industry. We find that the ANN models have lower prediction errors and higher threshold statistics as compared to that of the traditional models for predicting the demand of the Canadian forest products. Accurate future demand forecasts will not only help in improving the short-term profitability of the Canadian forest products industry, but also their long-term competitiveness in the global markets.

Intellectual assets, especially its relational forms, have become increasingly important to explain a firm's innovation. To examine relational forms of intellectual assets (IA), this study theoretically and empirically advances a concept of alliance management capability (AMC) to explain the value creation and capture aspects of a firm's innovation process. The concepts of value-creating alliance experiences (VCAE) and value capturing alliance experiences (VCPAE) were introduced in which a firm's ability to learn from these alliance experiences increases the firm's ability to discover and govern partnerships that bring the firm's innovations to market. Hypotheses were developed and empirically examined in the biotechnology industry. A contribution of this study is that a firm's VCAE and VCPAE introduce a greater 'openness' to a firm's innovation process. This openness enables a firm to better adapt and respond to the opportunities of the market and thus impact a firm's competitive advantage to innovate.

The notion of creative slack purposefully refers to the notion of organisational slack proposed by Penrose (1959), who suggested that managers in organisations always have some stock of unused resources that inevitably accumulate when developing projects and are the primary factors determining the growth and innovation of the firm. In this contribution, we aim at adding a new dimension to the notion of organisational slack. Our view is that in many innovative organisations the slack of unused ideas is essentially a creative one, which is accumulated in diverse communities through multiple projects. This creative slack is a key intangible asset and a source of knowledge creation and innovation. To explain how organisations may benefit from exploiting the creative slack accumulated by communities, we rely on the analysis of two case studies, that of the Hydro-Québec Research Institute (IREQ), and of Ubisoft Montreal.

This article explores dual affiliated graduate students that conduct research involving both universities and firms, which we conceptualise as a form of academic engagement, e.g., knowledge networks. We explore what they do during their studies, and their perceptions about their contributions to the firm's capacities for technology and innovation. So far, university-industry interactions in engineering are less researched than other fields, and this qualitative study focuses upon one department of Electrical Engineering in Sweden. First, we define and describe how the partner firms and universities organise this research collaboration as a form of academic engagement. Secondly, we propose a conceptual framework specifying how graduate students act as boundary-spanners between universities and firms. This framework is used for the empirical analysis, when exploring their perceptions of impact. Our results reveal that they primarily engage in problem-solving activities in technology, which augment particularly the early stages of absorptive capacities in firms.

Science-based university spin-offs face considerable technology and market uncertainty over extended periods of time, increasing the challenges of commercialisation. Scientist-entrepreneurs can play formative roles in commercialising lab-based scientific inventions through the formation of well-endowed university spin-offs. Through case study analysis of three science-based university spin-offs within a biotechnology innovation ecosystem, we unpack the impact of <i>pre-formation</i> intangible assets of academic scientists (research excellence, patenting, and international networks) and their entrepreneurial capabilities on spin-off performance. We find evidence that the pre-formation entrepreneurial capabilities of academic scientists can endow science-based university spin-offs by leveraging the scientists' pre-formation intangible assets. A theory-driven model depicting the role of pre-formation intangible assets and entrepreneurial capabilities in endowing science-based university spin-offs is developed. Recommendations are provided for scholars, practitioners, and policymakers to more effectively commercialise high potential inventions in the university lab through the development and deployment of pre-formation intangible assets and entrepreneurial capabilities.

The research uses a machine learning approach to appraising the validity of customer aptness for a loan. Banks and non-banking financial companies (NBFC) face significant non-performing assets (NPAs) threats because of the non-payment of loans. In this study, the data is collected from Kaggle and tested using various machine learning models to determine if the borrower can repay its loan. In addition, we analysed the performance of the models [K-nearest neighbours (K-NN), logistic regression, support vector machines (SVM), decision tree, naive Bayes and neural networks]. The purpose is to support decisions that are based not on subjective aspects but objective data analysis. This work aims to analyse how objective factors influence borrowers to default loans, identify the leading causes contributing to a borrower's default loan. The results show that the decision tree classifier gives the best result, with a recall rate of 0.0885 and a false- negative rate of 5.4%.

Pandemic has compelled the entire world to change their way of life and work. To control the infection rate, academic institutes deliver education online similarly. At least one smartphone is available in every home, and students use their smartphones to attend class. The study investigates the link between smartphone usage (SU) and academic performance (AP) during the pandemic. 490 data were obtained from various institutions and undergraduate students using stratified random sampling. These components were identified using factor analysis and descriptive methods, while the relationship of SU and AP based on gender classification was tested using Smart-PLS-SEM. The findings show that SU has a substantial relationship with academic success, whether done in class or outside of it. Even yet, the study found that SU and AP significantly impact both male and female students. Furthermore, the research focuses on SU outside and within the classroom to improve students' AP.

This study aimed to assess the level of GW in Jordanian university students and compare the level of awareness of students according to their academic level (high and low), faculty (science and humanities), gender (male and female), and year of study (first and final years). This study is quantitative research that provides a comprehensive view of GW in Jordanian universities. A total of 383 university students of currently registered undergraduate programs from six independent universities in Jordan were recruited. An online questionnaire covering three aspects of GW was sent to participants in December 2020. Inferential and descriptive statistics were used to analyse data. Participants had 'good' (67%) overall knowledge about GW, a 'very good' level of GW causes (81%), and a 'poor' level of knowledge about the GW impacts on humans and the environment (47%) and knowledge about GW possible solutions (59%). Significant differences were founded between males and females, students from scientific faculties and students from other faculties, students with higher academic achievement than lower achievement in the total GW knowledge. But no significant differences were between students in the first year and the final years.

For a long time, high school students have been forced to practice selecting correct answers on college scholastic ability tests. Recently, it has been suggested that schools introduce biomimicry activities for STEM education to develop students' 21st century competency. However, there have been arguments about which system is more appropriate in terms of enhancing a student's competency development. Therefore, we evaluated neurological evidence of students' competency using fMRI scans taken during the selecting a correct answer for a biology question and during a biomimicry activity. Results showed that the repetitive practice of selecting correct responses limited a student's neurological activities to the brain network of the visual cortex and the front-parietal working memory cortex. However, the biomimicry activity simultaneously involved diverse prefrontal, parietal and temporal cortexes, and the putamen, limbic and cerebellum lobes. Therefore, this study proposes that the biomimicry activities could stimulate their coordinated brain development.

The face of the hospitality sector in India is continuously changing and in times of career transitiveness, it is important to know the factors that support a successful career. The current research aims to explore the relationship between career planning, employee optimism, career adaptability and career satisfaction in the Indian hospitality sector. The study included 283 employees from Indian hospitality sector. Additionally, the study used SEM and bootstrap method to measure the dual mediating relationship between career planning, employee optimism dimensions, career adaptability dimensions, and career satisfaction in Indian setting. The results indicated that optimism dimensions and career adaptability dimensions partially mediate the relationship between career planning and career satisfaction in Indian hospitality sector. The study suggests useful implications for academia and industrial purpose. The limitations and future research avenues have been discussed. The study would contribute to the sparse literature on employee optimism, career planning, career adaptability and subjective career success. It would contribute to the social cognitive career theory (SCCT).