Abdullah Alharbi, Wajdi Alhakami, Sami Bourouis, Fatma Najar and Nizar Bouguila
We propose in this paper a novel reliable detection method to recognize forged inpainting images. Detecting potential forgeries and authenticating the content of digital images is…
Abstract
We propose in this paper a novel reliable detection method to recognize forged inpainting images. Detecting potential forgeries and authenticating the content of digital images is extremely challenging and important for many applications. The proposed approach involves developing new probabilistic support vector machines (SVMs) kernels from a flexible generative statistical model named “bounded generalized Gaussian mixture model”. The developed learning framework has the advantage to combine properly the benefits of both discriminative and generative models and to include prior knowledge about the nature of data. It can effectively recognize if an image is a tampered one and also to identify both forged and authentic images. The obtained results confirmed that the developed framework has good performance under numerous inpainted images.
Details
Keywords
Fatma Lehyani, Alaeddine Zouari, Ahmed Ghorbel and Michel Tollenaere
Companies should enhance their market position and competitiveness by improving staff effectiveness, skills, resource commitment, and applying relevant managerial methods. This…
Abstract
Purpose
Companies should enhance their market position and competitiveness by improving staff effectiveness, skills, resource commitment, and applying relevant managerial methods. This study aims to examine the impact of knowledge management (KM) and total quality management (TQM) on employee effectiveness (EE) and supply chain performance (SCP) in emerging economies.
Design/methodology/approach
The used methodology consists on conducting a survey within Tunisian companies, where the authors gathered 206 responses. Collected data was analyzed using statistical package for the social sciences (SPSS) software, enabling the authors to establish a conceptual model. This model was further examined through structural equation modeling, using analysis of moment structures (AMOS) software for hypothesis validation. Additionally, the authors’ research aimed to enhance SCP and boost EE while minimizing costs through a nonlinear mathematical model and the quality function deployment method.
Findings
The results indicate that TQM and KM positively impact EE, and KM and EE positively impact SCP. However, the significance of employee performance on SCP varies depending on company location and industry sector studied.
Originality/value
This work emphasized the involvement of small- and medium-sized enterprise managers from emerging economies in the studied concepts and confirmed the effects of KM and TQM practices on EE and SCP.
Details
Keywords
Raouf Ahmad Rather and Dhouha Jaziri
Though customer experience (CX) is identified as a key research priority, empirically led insight with tourism consumers' resulting emotional attachment (EA) and customer loyalty…
Abstract
Though customer experience (CX) is identified as a key research priority, empirically led insight with tourism consumers' resulting emotional attachment (EA) and customer loyalty (CL) remains scarce, particularly during the COVID-19 crisis. Adopting service-dominant logic, this study develops a model that investigates the impact of customer engagement (CE) and customer co-creation (CC) on CX, which consequently effects EA and CL during the COVID-19 crisis in the tourism industry. First, our results suggest that CE and CC positively affect tourism CX. Second, results revealed the CX's significant positive effect on EA and CL. Third, findings confirmed the CE's and CC's indirect impact on EA and CL, as mediated via CX in pandemic situations. Our study offers key implications for destinations to develop tactics in surviving during a pandemic to rebuild tourism.
Details
Keywords
Adnan Muhammad Shah, Abdul Qayyum, Mahmood Shah, Raja Ahmed Jamil and KangYoon Lee
This study addresses tourists' post-consumption perspectives on the impact of online destination experiences and animosity on travel decisions. Developing a framework based on the…
Abstract
Purpose
This study addresses tourists' post-consumption perspectives on the impact of online destination experiences and animosity on travel decisions. Developing a framework based on the stimulus-organism-response (SOR) theory, we examine the previously unexplored relationship between post-negative events, online destination brand experience (ODBE), tourists' animosity and destination boycott intentions within the domestic tourism context.
Design/methodology/approach
Data from 355 actively engaged domestic travelers in Pakistan who follow destination social media pages (i.e. Instagram and Facebook) was analyzed using structural equation modeling.
Findings
The findings reveal that post-negative events ODBE significantly stimulate tourists' animosity, which in turn drives destination boycott intentions. The ODBE indirectly affects boycott intentions through animosity, acting as a partial mediator. The analysis highlights the significance of the users' prior experience levels (novice vs experienced). Multigroup analysis shows that novice visitors are more sensitive to negative online experiences, resulting in stronger animosity than experienced visitors. Animosity significantly drives boycott intentions, particularly among experienced visitors.
Originality/value
This study’s novelty lies in its comprehensive examination of post-negative events, focusing on how the ODBE influences tourists' negative emotions and boycott intentions. These findings offer valuable insights for tourism researchers and destination marketers, underscoring the importance of optimizing post-service failure ODBE strategies for brand repair, online reputation management, digital marketing innovation and customized service recovery to mitigate the impact of negative events.