Search results

The purpose of the study is distributed generation planning in a radial delivery framework to identify an appropriate location with a suitable rating of DG units energized by renewable energy resources to scale back the power loss and to recover the voltage levels. Though several algorithms have already been proposed through the target of power loss reduction and voltage stability enhancement, further optimization of the objectives is improved by using a combination of heuristic algorithms like DE and particle swarm optimization (PSO).

The identification of the candidate buses for the location of DG units and optimal rating of DG units is found by a combined differential evolution (DE) and PSO algorithm. In the combined strategy of DE and PSO, the key merits of both algorithms are combined. The DE algorithm prevents the individuals from getting trapped into the local optimum, thereby providing efficient global optimization. At the same time, PSO provides a fast convergence rate by providing the best particle among the entire iteration to obtain the best fitness value.

The proposed DE-PSO takes advantage of the global optimization of DE and the convergence rate of PSO. The different case studies of multiple DG types are carried out for the suggested procedure for the 33- and 69-bus radial delivery frameworks and a real 16-bus distribution substation in Tamil Nadu to show the effectiveness of the proposed methodology and distribution system performance. From the obtained results, there is a substantial decrease in the power loss and an improvement of voltage levels across all the buses of the system, thereby maintaining the distribution system within the framework of system operation and safety constraints.

A comparison of an equivalent system with the DE, PSO algorithm when used separately and other algorithms available in literature shows that the proposed method results in an improved performance in terms of the convergence rate and objective function values. Finally, an economic benefit analysis is performed if a photo-voltaic based DG unit is allocated in the considered test systems.

The multisource uncertainties, including material dispersion, load fluctuation and geometrical tolerance, have crucial effects on fatigue performance of turbine bladed disks. In view of the aim of this paper, it is essential to develop an advanced approach to efficiently quantify their influences and evaluate the fatigue life of turbine bladed disks.

In this study, a novel combined machine learning strategy is performed to fatigue assessment of turbine bladed disks. Proposed model consists of two modeling phases in terms of response surface method (RSM) and support vector regression (SVR), namely RSM-SVR. Two different input sets obtained from basic variables were used as the inputs of RSM, then the predicted results by RSM in first phase is used as inputs of SVR model by using a group data-handling strategy. By this way, the nonlinear flexibility of SVR inputs is improved and RSM-SVR model presents the high-tendency and efficiency characteristics.

The accuracy and tendency of the RSM-SVR model, applied to the fatigue life estimation of turbine bladed disks, are validated. The results indicate that the proposed model is capable of accurately simulating the nonlinear response of turbine bladed disks under multisource uncertainties, and SVR-RSM model provides an accurate prediction strategy compared to RSM and SVR for fatigue analysis of complex structures.

The results indicate that the proposed model is capable of accurately simulate the nonlinear response of turbine bladed disks under multisource uncertainties, and SVR-RSM model provides an accurate prediction compared to RSM and SVRE for fatigue analysis of turbine bladed disk.

The research question is how can a company implement a circular innovation in a supply network context? Leveraging the main conceptual and interpretative models of the industrial marketing and purchasing thinking, this study aims to investigate the interplay between the process of circular innovation development and the changes in the structure and dynamics of the supply network in which innovation takes place.

This research applies a case study design focusing on participant interaction dynamics. The case relates to an industrial company producing an innovative coating solution for compostable packaging. The data used to develop the case study came from multiple sources but primarily from semistructured interviews that cover the implementation of the circular innovation and the configuration of the circular network.

The dynamics of interconnected relationships can configure a circular network that interconnects business and non business actors through vertical, horizontal and heterogeneous relationships. The network configuration is supported by the new mobilizer actor that facilitates the sharing of circular knowledge within the circular network, together with the sharing of a market orientation and entrepreneurial orientation within the supply network, through the educational learning path.

This paper aims to contribute to a new understanding of how circular innovation can be developed, adopted and diffused. In a network, when circular innovation takes place, the focal issue is not the new product or technology in itself but how such innovation is developed and implemented by and through the reconfiguration of the business and non-business relationships into circular network.

The aim of this study is to gain important insights on integration oriented servitization identifying essential dimensions of effective structures, coordination approaches and management controls adopted by manufacturing firms that integrate forward towards distribution, sales and services.

The study adopts a theory-guided qualitative abductive methodology to conduct a comparative case-study of two manufacturing firms in the same industry integrating forward to enhance servitization but with significantly different performance outcomes. The findings are uncovered from a broad spectrum of primary and secondary data spanning two decades.

The consistently high-performing firm puts equal emphasis on production and downstream distribution, sales and services and motivate individuals to engage in entrepreneurial efforts to develop combined product-services offerings that are valued by customers. The underperforming firm prioritizes operating efficiency driven by engineering prowess and managed through planning, standardization, authority and central controls.

The study is based on two representative firms operating in a specific industry context, which has ramifications for the generalizability of results and calls for replication studies to substantiate and extend findings.

Forward integration from manufacturing into distribution, sales and services represents a specific servitization strategy that needs structure and particular coordination approaches to be effective in complex dynamic product-markets. The characteristics of the outperforming case company provide useful insights on effective integrated servitization efforts.

Forward integration is a commonly adopted strategy among manufacturing firms that constitute the backbone of modern economies and effective governance of these integration oriented servitization efforts has important implications for societal value creation.

This study builds on rationales from management science including economic theory, corporate strategy and different micro-foundational lenses and thereby hone recent calls for broader theoretical foundations to enlighten studies of the servitization puzzle.

This paper presents a decision-making framework for e-banking operations, based on the Quality Function Deployment and the Analytic Hierarchy Process. The main research question is the development of a framework and its potential contributions in supporting decision makers in implementing quality strategies that will encourage the usage of e-banking services (EBS).

The introduced framework comprises four distinct stages which include criteria determination, field surveys and EFA, QFD application including AHP and finally sensitivity analysis investigating the dynamic nature of the environment. AHP determines the intensity of the relationship between e-banking quality criteria and customer banking activities. A novel House of Quality (HoQ) is proposed, based on a market mix founded on key e-banking activities, and sensitivity analysis is used to investigate alternative scenarios. To illustrate the steps of applying this framework, the authors use a convenience sample from the Greek e-banking sector.

Through the illustrated example is supported that the proposed approach can reveal valuable information when contemplating strategies to improve e-banking usage and expand its acceptance. In addition, sensitivity analysis leads to purposeful insights regarding the effects of market segmentation and/or target settings on the ranking of e-banking quality/selection criteria provided by the HoQ. In the specific numerical example, the most critical quality factors were “Security and Reliability”, “Convenience”, “Design”, “Pricing” and “Skills,” although different rankings night well appear in different contexts or geographical regions. Moreover, sensitivity analysis showed that these results depend on the specific market mix and targets. As mentioned above, the implementation of the framework in different geographical regions or e-service sectors might certainly reveal different critical factors.

Discussed in the paper body.

Discussed in the paper body.

The paper presents a well-defined four stage framework for improving EBS penetration. It utilizes a structured qualitative and quantitative approach and outlines and ranks e-banking quality factors stemming from the market mix and allows assessment of alternative scenarios through sensitivity analysis.

The purpose of this article is to present qualitative research of the past organizational crisis at Mississippi Chemical Corporation that the authors use to theorize a typology of organizational crisis from the leadership perspective.

The authors combined ANTi-microhistory approach and staff ride research design to re-enact the sensemaking of the company’s former crisis leaders and elicit their retrospective oral accounts. A long interview format was used to interview the crisis leaders.

The authors found that the former crisis leaders not only conceptualized organizational crisis conventionally as an event or as a process but also that they engaged in the denial of the crisis to guard the company’s reputation and competed with their claims against the stakeholder claims about the ways how the crisis was to be managed.

Based on the paper’s findings, the authors proposed an original typology of organizational crisis.

Assess the realistic impacts of implementing an Radio Frequency Identification (RFID)/Internet of Things (IoT) uniforms’ distribution system for managing medical personnel’s scrubs in operating rooms. The authors use a hybrid simulation framework to address the following objectives and challenges: a) reduce and control operating rooms’ level of inventory; b) stabilize scrubs’ demand and c) improve infection control and prevention of cross-contamination (through scrubs over manipulation and hoarding).

The authors adopt a Design Science approach. This methodological approach is used to design, develop, create and evaluate information technology “artifacts” (e.g. constructs, models, methods and instantiations) intended to solve organizational problems and make research contributions (Peffers et al., 2007). More specifically, the authors follow the Design Science Research Methodology process model which includes six steps: problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication.

To assess the realistic impacts of implementing an RFID-IoT uniforms’ distribution system for managing medical personnel’s scrubs in operating rooms, the authors adopted a design science approach and initiated the research by documenting the business case and reviewed the existing literature to build a comparative analysis of existing uniforms’ distribution systems. The authors used a hybrid simulation model to assess the impact of three business cases: present mode of operation, implementing smart shelves or the smart distributors. The authors show that smart dispensers allow a greater control on scrubs’ utilization while eliminating the cross-contamination of the medical personnel.

Through this research study, the authors provide hospitals’ managers a scientific support for uniforms’ (scrubs) distribution process improvement. The authors use a hybrid simulation model to compare innovative solutions for uniforms’ distribution systems in the form of “smart cabinets” supported by Radio Frequency Identification (RFID)/Internet of Things (IoT) technologies and choose the most appropriate design for the hospital to meet two main challenges: a) inefficiency of uniform replenishment-distribution system and b) noncompliancy with infection control regulations caused by the distribution system.

From a methodological perspective, this paper addresses concerns from researchers calling quantitative research methods and using case-based research strategy to address IoT issues and assess the system in practice. From a broader point of view, this work confirms the predominant interest of RFID-IoT research work in the arena of supply chain management and logistics as the technology is used for tracking purpose and for monitoring applications. It is also one response to the research community suggesting that “hospitals should evaluate the medical effectiveness of the new technologies as well as the cost before adoption”.

The purpose of this study is not only to develop an integrated model of subjective well-being (SWB) by using confirmatory factor analysis (CFA) and structural equation modeling (SEM) but also to prioritize the subfactors of personality and SWB that affect the contextual performance (CP) of an employee by using a fuzzy-analytical hierarchy process (FAHP), which has not been done in the past.

The data were collected from 15 field experts and 412 employees of information technology (IT) companies operating in India. The data analysis was performed in two stages. The first stage includes CFA and SEM. The second stage includes prioritizing the factor through FAHP.

The results of SEM analysis manifested that all the dimensions of personality have a significant impact on CP. However, in the case of SWB, only two components (satisfaction with life and positive affect) have a significant impact on CP. Results of FAHP show that SWB is more important in predicting CP than the Big Five personality dimensions.

This research is a novel attempt to test and prioritize the factors affecting the CP of IT employees. The findings of the research will be useful for managers in increasing the performance of their employees. Further, the findings of the research will contribute to the literature on the factors affecting CP.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.

From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries.

This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development.

ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals.

This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.