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This study aims to investigate the effects of organizational culture factors on the selection of software process development models and develops a conceptual model for selecting and adopting process development models with an organizational culture approach, using 12 criteria and their sub-criteria defined in Fey and Denison’s model (12 criteria).

The research hypotheses were investigated using statistical analysis, and then the criteria and sub-criteria were selected based on Fey and Denison’s model and the experts’ viewpoints. Afterward, the organizational culture of the selected company was measured using the data from 2016 and 2017, based on Fey and Denison’s questionnaire. Due to the correlation between the criteria, using the decision-making trial and evaluation technique, the correlation between sub-criteria were determined, and by analytical network process method and using Super-Decision software, the process development model was preferred to the 12 common models in information systems development.

Results indicated a significant and positive effect of organizational culture factors (except the core values factor) on the selection of development models. Also, by changing the value of organizational culture, the selected process development model changed either. Sensitivity analysis performed on the sub-criteria implied that by changing and improving some sub-criteria, the organization will be ready and willing to use the agile or risk-based models such as spiral and win-win models. Concerning units where the mentioned indicators were at moderate and low limits, models such as waterfall, V-shaped and incremental worked more appropriately.

While many studies were performed in comparing development models and investigating their strengths and weaknesses, and the impact of organizational culture on the success of information technology projects, literature indicated that the impact of organizational sub-culture prevailing in the selection of development process models has not been investigated. In this study, new factors and indicators were addressed affecting the selection of development models with a focus on organizational culture. Correlation among the factors and indicators was also investigated and, finally, a conceptual model was proposed for proper adoption of the models and methodologies of system development.

This research investigates the critical role of data governance (DG) in shaping a data-driven culture (DDC) within organizations, recognizing the transformative potential of data utilization for efficiency, opportunities, and productivity. The study delves into the influence of DG on DDC, emphasizing the mediating effect of data literacy (DL).

The study empirically assesses 125 experienced managers in Indonesian public service sector organizations using a quantitative approach. Structural Equation Modeling (SEM) analysis was chosen to examine the impact of DG on DDC and the mediating effects of DL on this relationship.

The findings highlight that both DG and DL serve as antecedents to DDC, with DL identified as a crucial mediator, explaining a significant portion of the effects between DG and DDC.

Beyond unveiling these relationships, the study discusses practical implications for organizational leaders and managers, emphasizing the need for effective policies and strategies in data-driven decision-making.

This research fills an important research gap by introducing an original model and providing empirical evidence on the dynamic interplay between DG, DL, and DDC, contributing to the evolving landscape of data-driven organizational cultures.

Damage to reinforced concrete (RC) structural elements is inevitable. Such damage can be the result of several factors, including aggressive environmental conditions, overloading, inadequate design, poor work execution, fire, storm, earthquakes etc. Therefore, repairing and strengthening is one way to improve damaged structures, so that they can be reutilized. In this research, the use of an ultra high-performance fibre-reinforced concrete (UHPFRC) layer is proposed as a strengthening material to rehabilitate damaged-RC beams. Different strengthening schemes pertaining to the structural performance of the retrofitted RC beams due to the flexural load were investigated.

A total of 13 normal RC beams were prepared. All the beams were subjected to a four-point flexural test. One beam was selected as the control beam and tested to failure, whereas the remaining beams were tested under a load of up to 50% of the ultimate load capacity of the control beam. The damaged beams were then strengthened using a UHPFRC layer with two different schemes; strip-shape and U-shape schemes, before all the beams were tested to failure.

Based on the test results, the control beam and all strengthened beams failed in the flexural mode. Compared to the control beam, the damaged-RC beams strengthened using the strip-shape scheme provided an increase in the ultimate load capacity ranging from 14.50% to 43.48% (or an increase of 1.1450 to 1.4348 times), whereas for the U-shape scheme beams ranged from 48.70% to 149.37% (or an increase of 1.4870–2.4937 times). The U-shape scheme was more effective in rehabilitating the damaged-RC beams. The UHPFRC mixtures are workable, as well easy to place and cast into the formworks. Furthermore, the damaged-RC beams strengthened using strip-shape scheme and U-shape scheme generated ductility factors of greater than 4 and 3, respectively. According to Eurocode8, these values are suitable for seismically active regions. Therefore, the strengthened damaged-RC beams under this study can quite feasibly be used in such regions.

Observations of crack patterns were not accompanied by measurements of crack widths due to the unavailability of a microcrack meter in the laboratory. The cost of the strengthening system application were not evaluated in this study, so the users should consider wisely related to the application of this method on the constructions.

Rehabilitation of the damaged-RC beams exhibited an adequate structural performance, where all strengthened RC beams fail in the flexural mode, as well as having increment in the failure load capacity and ductility. So, the used strengthening system in this study can be applied for the building construction in the seismic regions.

Aside from equipment, application of this strengthening system need also the labours.

The use of sand blasting on the surfaces of the damaged-RC beams, as well as the application of UHPFRC layers of different thicknesses and shapes to strengthen the damaged-RC beams, provides a novel innovation in the strengthening of damaged-RC beams, which can be applicable to either bridge or building constructions.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.

In most economies, there are rules from the market regulators or government to sell at an equal wholesale price (EWP). But when one upstream channel is facing a negative demand disruption and another positive, EWP can create extra pressure on the disadvantageous supply chain partner, which faces negative disruption. The purpose of this study is to analyse the impact of EWP and the scope of the discriminatory wholesale price (DWP) during disruptions.

For the study, the authors used a dual-channel supply chain consisting of a manufacturer, online retailer (OR) and traditional brick-and-mortar (BM) retailer. Stackelberg game is used to model the interaction between the upstream and downstream channel partners, and the horizontal Nash game to analyse the interaction within downstream channel partners. For modelling asymmetric disruption, the authors took instances from the lock-down and post-lock-down periods of the COVID-19 pandemic, where consumers flow from BM retailer to OR store.

By analysing the disruption period, the authors found that this asymmetric disruption is detrimental to the BM channel, favourable to OR and has no impact on the manufacturer. But with DWP, the authors found that the profit of the BM channel and manufacturer can be increased during disruption. Though the profit of the OR decreased, it was found to be higher than in the pre-disruption period. Under DWP, the consumer surplus increased during disruption, making it favourable for the customers also. Thus, DWP can aid in creating a win-win strategy for all the supply chain partners during asymmetric disruption. Later as an extension to the study, the authors analysed the impact of the consumer transfer factor and found that it plays a crucial role in the optimal decisions of the channel partner during DWP.

Very scant literature analyses the intersection of DWP and disruptions. To the best of the authors’ knowledge, this study, for the first time uses DWP as a tool to help the disadvantageous supply chain partner during asymmetric disruptions. The study findings will assist the government, market regulators and manufacturers in revamping the wholesale pricing policies and strategies to help the disadvantageous supply chain partner during asymmetric disruption.

Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.

An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.

On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.

The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.

This study aims to design and validate a theoretical model for capacitive imaging (CI) sensors that incorporates the interelectrode shielding and surrounding shielding electrodes. Through experimental verification, the effectiveness of the theoretical model in evaluating CI sensors equipped with shielding electrodes has been demonstrated.

The study begins by incorporating the interelectrode shielding and surrounding shielding electrodes of CI sensors into the theoretical model. A method for deriving the semianalytical model is proposed, using the renormalization group method and physical model. Based on random geometric parameters of CI sensors, capacitance values are calculated using both simulation models and theoretical models. Three different types of CI sensors with varying geometric parameters are designed and manufactured for experimental testing.

The study’s results indicate that the errors of the semianalytical model for the CI sensor are predominantly below 5%, with all errors falling below 10%. This suggests that the semianalytical model, derived using the renormalization group method, effectively evaluates CI sensors equipped with shielding electrodes. The experimental results demonstrate the efficacy of the theoretical model in accurately predicting the capacitance values of the CI sensors.

The theoretical model of CI sensors is described by incorporating the interelectrode shielding and surrounding shielding electrodes into the model. This comprehensive approach allows for a more accurate evaluation of the detecting capability of CI sensors, as well as optimization of their performance.

The current study aims to analyze the role of International Federation of Accountants (IFAC) in sustainability issues and its impact on the attitude of practitioners (auditors) in industrial companies. The current study relies on the analytical method, one of the tools of the inductive approach, by examining the literature of researchers, international and local organizations, publications, series, alerts, and topics dealt with by the IFAC, as well as reviewing studies, theoretical and applied research, periodicals, books, and statistics. And specialized publications for this subject, which is related to other sciences – such as – environmental science, economic, and political sciences. The study reached many results, the most important of which are: (1) The first half of the current decade has seen high interest from the IFAC, has led to the issuance of International Auditing and Assurance Standards Board (IAASB) international standard on assurance engagements 3410, (GHG) Statements. (2) Sustainability has become important to a growing number of enterprises, and may have a significant influence, in certain cases, the financial statements, also became the sustainability of the topics under increasing attention from users of financial statements. Thus, the financial statements will need a practitioner to take into consideration sustainability issues and a private greenhouse gas when auditing the financial statements. This study is distinguished by analyzing the role of the IFAC and the IAASB for the period from 1998 to 2023 regarding sustainability issues.

The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.

Different studies have been conducted on the relationship between technological capability and firm performance. These studies obtain different values for the relationship, known as heterogeneous results. The purpose of this paper is to analyze the relationship between technological capability and firm performance and its statistical between-study heterogeneity.

In order to analyze all the results from this relationship that were found in the literature, we adopted the literature review with a meta-analytic method. We consulted the Scopus and Web of Science databases, which returned, after the application of inclusion criteria, 23 primary studies with data from 5,882 manufacturing firms.

We observed that technological capability and performance are positively related; however, the results regarding this relationship are heterogeneous. We discovered four possible sources of statistical between-study heterogeneity: (i) the statistical between-study heterogeneity of the variables to measure technological capability and performance; (ii) orientation of the thematic approach – some illustrate the relationship between technological capability and performance using mathematical and theoretical models, while others examine the relationship between technological capability and performance and propose implications pertaining to that relationship; (iii) the source of data for primary studies and (iv) the context in which this relationship is observed.

It is necessary to standardize a set of variables through which technological capability and performance are evaluated so that results and implications can be usefully compared between countries and industrial sectors.

The contribution to knowledge is identifying the statistical between-study heterogeneity on the relationship between technological capabilities and firm performance, as well as its potential sources.