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This study aims to propose a model to examine the relationships between e-government development, cybersecurity commitment, business usage and economic prosperity of the country.

Structural equation modeling was used to analyze the country-level variables to explain the second-order impact of e-government development through the mediating role of cybersecurity commitment.

Findings suggest that e-government development demonstrated a stronger association with cybersecurity commitment and business usage. There is preliminary evidence that the improvement of cybersecurity measures initiated by e-government development will drive business usage and improve macroeconomic conditions.

This paper has constructed a theoretical model and validated it using publicly available archival data. Further, this study hypothesizes and demonstrates empirically the direct, as well as indirect relationships between e-government development, cybersecurity commitment, business usage and economic prosperity. To summarize, the study unearths the role of a nation’s cybersecurity commitment and how it is associated with other macro parameters in a country.

As an initial step, the present study highlights the pivotal role of e-government and its positive influence on cybersecurity commitment at the country level. Further, this study also recognizes the role of cyber commitment to boost information communication and technology usage in business, the use of e-government services for the profitability of the business and effectively influence economic prosperity.

The current body of empirical research regarding the impact of trust in the cybersecurity commitment of institutions on digital payment usage has focused solely on a macro-level analysis, overlooking the intricate dynamics between institutions' cybersecurity commitments and the trust levels of digital payment users. In light of this limitation, this study aims to offer a more comprehensive understanding of this complex relationship.

A case study was conducted on digital payment users in India through the critical realist lens. To gather data, interviews and focus group discussions were conducted with digital payment users from various regions of the country.

The citizen-centric outcomes of the national cybersecurity commitment (performance and responsiveness) are the most prominent and impactful trust indicators. These outcomes play a crucial role in shaping digital payment users' perception and trust in the cybersecurity commitment of public institutions. Individuals' value positions also influence trust judgments, as it is essential to recognize the value tensions that may arise due to security implementation and their congruence with citizens' values.

The findings of this study have significant implications for policymakers. They are potentially an artifact of the security and perception of digital payment users and the cultural uniqueness of digital payment users in India.

The study proposes a holistic understanding of the relationship between institutions' cybersecurity commitments and the trust levels of digital payment users. It offers a qualitative evaluation of how digital payment users perceive and construe efficient information security management implemented by public institutions.

Service-oriented architecture is an emerging software architecture, in which web service (WS) plays a crucial role. In this architecture, the task of WS composition and verification is required when handling complex requirement of services from users. When the number of WS becomes very huge in practice, the complexity of the composition and verification is also correspondingly high. In this paper, the authors aim to propose a logic-based clustering approach to solve this problem by separating the original repository of WS into clusters. Moreover, they also propose a so-called quality-controlled clustering approach to ensure the quality of generated clusters in a reasonable execution time.

The approach represents WSs as logical formulas on which the authors conduct the clustering task. They also combine two most popular clustering approaches of hierarchical agglomerative clustering (HAC) and k-means to ensure the quality of generated clusters.

This logic-based clustering approach really helps to increase the performance of the WS composition and verification significantly. Furthermore, the logic-based approach helps us to maintain the soundness and completeness of the composition solution. Eventually, the quality-controlled strategy can ensure the quality of generated clusters in low complexity time.

The work discussed in this paper is just implemented as a research tool known as WSCOVER. More work is needed to make it a practical and usable system for real life applications.

In this paper, the authors propose a logic-based paradigm to represent and cluster WSs. Moreover, they also propose an approach of quality-controlled clustering which combines and takes advantages of two most popular clustering approaches of HAC and k-means.

The purpose of this paper is to evaluate the utility of clinical processes in healthcare institutions of different sizes. The implications of adoption rate of computerized physicians order entry (CPOE) and electronic medical/health records (EMRs/EHRs) in different sized healthcare institutions in the USA were studied in terms of understanding its impact on enhancement of quality of patient care.

This study has used secondary data to obtain insights on the processes and technologies used in hospitals of different sizes in the USA and enlighten those in the developing countries to adopt a strategy that would be most appropriate for them. The Dorenfest Institute for H.I.T. Research and Education Analytics database (The Dorenfest Institute, 2011) provided the data for 5,038 US hospitals. Logistic regression was performed to study the impact of the different types of processes and technologies on institutions of different sizes, classified based on the number of beds, physicians, and nurses.

The findings show that small sized hospitals had a positive relationship with drug dosing interactions process and nursing and clinician content process. On the contrary, medium sized hospitals had a negative relationship with the usage of CPOE for entering medical records, i.e. <25 percent (p<0.05). In order to be effective, these institutions should increase the usage of EMRs by more than 25 percent to get positive outcomes. Large hospitals showed a positive relationship with the usage of >75 percent of CPOE to enter medical records and usage of medical records >75 percent.

The authors demonstrate the need for an evaluation of utility of acute care hospitals based on hospital size in terms of number of physicians, and nurses, which have not been dealt earlier by the past studies. Moreover, there is also a need for an evaluation of utility of acute care hospitals for implementation of CPOEs and EMRs that are integrated with clinical decision support systems.

Although the data are US-centric, the insights provided by the results are very much relevant to the Indian scenario to support the improvement of the quality of care. The findings may help those implementing processes in healthcare institutions in India. No study has addressed the measurement of the positive and negative outcomes arising due to the implementation of different percentages of CPOEs and EMRs in different sized institutions. Further the number of physicians and nurses have not been considered earlier. Therefore, the authors have classified the hospitals based on physicians and nurses and studied their impact on the adoption of CPOEs, clinical decision support systems, and EMRs.

This study aims at exploring the choices of livelihood strategies amongst the rural youth and how these choices relate to food security and income poverty.

The study used data from the 2016/17 wave of Integrated Household Living Condition Survey, with a sample size of 1,050 rural youths. Statistical and econometrics methods including descriptive statistics and the Multinomial Endogenous Treatment Effect (METE) model were used to analyse the data.

Livelihood choices were grouped into five categories, namely agriculture, non-farm wage employment, agriculture plus non-farm wage, agriculture plus self-employment and agriculture plus non-farm wage plus self-employment. The estimates from METE indicate that the youths' choice of non-farm wage, agriculture plus non-farm wage and agriculture plus self-employment contributes substantially to household food security improvement and poverty reduction. These findings show that agriculture is necessary but not a sufficient livelihood strategy to sustain the rural youth's contribution to youth's household welfare. The rural youth will pursue agriculture as a reliable source of livelihood not only for food self-sufficiency, but also for ensuring adequate return to labour.

This paper extends single choice analysis to multiple choices impact analysis, which has the advantage of accounting for selection bias due to both observed and unobserved heterogeneity. This paper assesses the differential impact of the choice of single as well as multiple livelihood strategies.

The purpose of this paper is to propose a competitiveness measurement system for start-ups considering multiple critical success factors.

The methodological approach uses concepts from key performance indicators (KPIs) and multi-criteria decision analysis (MCDA) based on the fuzzy AHP (FAHP) methodology to weight the criteria related to fundamental points of view (FPVs) and critical success factors (CSFs).

Data collection was performed with 21 specialists and 28 start-ups, which returned the weights and performance of CSFs and FPVs related to the start-ups’ competitiveness. The results show only one start-up had a highly competitive global performance. In addition, all start-ups showed low competitiveness related to industry 4.0 technologies.

The article collaborates with existing research as a starting point for discussions on the subject, considering that previous research did not address the measurement of the start-ups’ competitiveness level through multiple factors, as developed in this article. In addition, we provide decision-makers and other stakeholders in the start-up ecosystem with a robust measurement system to assess business competitiveness and diagnose the company’s situation.

The purpose of this work is to implement an ambient intelligence (AmI) testbed to improve human sleeping conditions.

The implemented testbed is composed of the sensor node, sink node and actor node. As sensor node, the authors use a microwave sensor module (MSM) called DC6M4JN3000, which emits microwaves in the direction of a human or animal subject. These microwaves reflect back off the surface of the subject and change slightly in accordance with movements of the subject’s heart and lungs. As sink node, the authors use Raspberry Pi 3 Model B computers. In the sink node, the data are processed and then clustered by the k-means clustering algorithm. Then, the result is sent to the actor node (Reidan Shiki PAD module), which can be used for cooling and heating the bed.

The authors carried out simulations and experiments. Based on the simulation results, it was found that the room lighting, humidity and temperature have different effects on humans during sleeping. The best performance is shown when LIG parameter is 10 units, HUM parameter is 50 and TEM parameter is 25. Based on experimental results, it was found that the implemented AmI testbed has a good effect on humans during sleeping.

For simulations, three input parameters were considered. However, new parameters that affect human sleeping conditions also need to be investigated. Further, the experiments were carried out for one person. More extensive experiments with multiple people are needed to have a better evaluation.

In this research work, a new fuzzy-based system was implemented to improve human sleeping conditions. The authors presented three new input parameters to evaluate the output (sleeping condition). The authors implemented and evaluated a testbed and showed that the implemented AmI testbed has a good effect on humans during sleeping, thus improving their quality of life (QoL).

This study aims to propose an offline exploratory method that consists of two stages: first, the authors focus on completing the kinematics model of the system by analyzing the Jacobians in the vicinity of the starting point and deducing a virtual input to effectively navigate the system along the non-holonomic constraint. Second, the authors explore the sensorimotor space in a predetermined pattern and obtain an approximate mapping from sensor space to chained form that facilitates controllability.

In this paper, the authors tackle the controller acquisition problem of unknown sensorimotor model in non-holonomic driftless systems. This feature is interesting to simplify and speed up the process of setting up industrial mobile robots with feedback controllers.

The authors validate the approach for the test case of the unicycle by controlling the system with time-state control policy. The authors present simulated and experimental results that show the effectiveness of the proposed method, and a comparison with the proximal policy optimization algorithm.

This research indicates clearly that feedback control of non-holonomic systems with uncertain kinematics and unknown sensor configuration is possible.