Search results

User behavior in online information evaluation is the result of a multitude of factors related to social, cultural, personal and psychological issues. The present study aimed to examine the effects of three important psychological variables including personality, self-efficacy and attitude on online information evaluation.

Four validated measures were administrated in person and online among 355 postgraduate students at Shahed University, Tehran, Iran. For testing the possible relationships among the variables, the reliability, normality and Pearson correlation tests were performed by using SPSS 24.0. Moreover, to test the ten hypotheses of the research, the structural equation modeling was considered using AMOS 26.0.

The findings confirmed the first five research hypotheses indicating the direct positive relationships among the four variables except for the impact of self-efficacy on attitude. The mediated effects of the variables were not supported except for the mediating role of attitude in the impact of personality on online evaluation behavior. The variable personality was found to be fundamental among the tested paths because it influenced the information evaluation behavior, both directly and indirectly.

The study showed the impacts of the three variables, which demonstrates that online information evaluation is greatly affected by psychological factors.

The common methods for clustering time series are the use of specific distance criteria or the use of standard clustering algorithms. Ensemble clustering is one of the common techniques used in data mining to increase the accuracy of clustering. In this study, based on segmentation, selecting the best segments, and using ensemble clustering for selected segments, a multistep approach has been developed for the whole clustering of time series data.

First, this approach divides the time series dataset into equal segments. In the next step, using one or more internal clustering criteria, the best segments are selected, and then the selected segments are combined for final clustering. By using a loop and how to select the best segments for the final clustering (using one criterion or several criteria simultaneously), two algorithms have been developed in different settings. A logarithmic relationship limits the number of segments created in the loop.

According to Rand's external criteria and statistical tests, at first, the best setting of the two developed algorithms has been selected. Then this setting has been compared to different algorithms in the literature on clustering accuracy and execution time. The obtained results indicate more accuracy and less execution time for the proposed approach.

This paper proposed a fast and accurate approach for time series clustering in three main steps. This is the first work that uses a combination of segmentation and ensemble clustering. More accuracy and less execution time are the remarkable achievements of this study.

This study aims to investigate the intervening role of lean management (LM) in the direct relationships between green market orientation, green value-based innovation, green reputation and enterprise social performance.

Data for the study is carefully garnered from 217 managers in Ghanaian small- and medium-sized enterprises. The methodological technique used to validate all hypothesized relationships is partial least squares structural equation modelling.

The empirical results of the study suggest that although green market orientation has a positive impact on green value-based innovation, the effect is not significant. However, the results confirm that green market orientation has a significant positive impact on green reputation and enterprise social performance. The results further suggest that LM has a significant positive impact on green value-based innovation, green reputation and enterprise social performance. The mediation analysis provides empirical evidence to suggest that LM fully mediates the relationship between green market orientation and green value-based innovation. Lastly, the results of the mediation analysis suggest that LM plays a complementary partial mediation role between green market orientation, green reputation and enterprise social performance.

Despite the flourishing research on green market orientation in marketing management and environmental literature, no study has been carried out to explore the intervening role of LM in the relationships between green market orientation, green value-based innovation, green reputation and enterprise social performance. Thus, considering LM as a missing link between green market orientation, green value-based innovation, green reputation and enterprise social performance is a noteworthy research gap which this study fills.

This study aims to explore and identify potential challenges and prospects for conducting the professional shariah audit training programme via an e-learning approach during coronavirus disease 2019 (COVID-19).

Questionnaires were administered to 296 participants who were enrolled in the professional shariah audit training programme via e-learning during the COVID-19 pandemic outbreak in 2020. These participants were final-year students from selected Malaysian public universities.

Findings show that several main challenges are faced in adopting an e-learning approach for conducting the professional shariah audit training programme such as the inability to do more hands-on, group and physical activities, different understandings based on academic backgrounds, difficulty in learning practical and technical topics, technical issues and problems during e-learning sessions. These lead to the unsuitability of conducting professional training via the e-learning approach. In terms of prospects of knowledge learnt via the e-learning approach, participants showed that they are able to master all six modules covered in the professional shariah audit training programme via the e-learning approach. These include (1) shariah principles; (2) shariah governance; (3) Islamic financial transactions; (4) shariah risk management; (5) shariah audit planning and programme; and (6) shariah audit fieldwork and communication.

Based on the findings, it is suggested to have more time spent and earlier preparation on the learning contents and sessions, more discussion on actual contents and practical exercises and competency of the trainers in delivering e-learning sessions.

This study is believed to be one among the pioneering studies on the potential challenges and prospects in adopting e-learning for conducting the professional shariah audit training programme due to COVID-19.

This paper seeks to revisit the interrelationship among tourists’ perceived value of the destination, tourist satisfaction and destination loyalty in the heritage tourism site of Hoi An. In addition, the moderating role of tourists’ perceived crowding, which has become remarkably common at the site, in such a triangle relationship will also be explored. In other words, this study aims to validate an extended model of perceived value – tourist satisfaction – destination loyalty – perceived crowding.

The study collects data from 403 tourists who visited Hoi An during peak season through an online questionnaire. The data were later analysed using AMOS and Warp partial least squares.

The results validate the significant and positive correlation among perceived value, customer satisfaction and destination loyalty. Also, perceived crowding was confirmed to affect the relationship among these three variables negatively. In terms of academic contributions, this paper empirically proved that low levels of tourist satisfaction and destination loyalty among tourists who highly value their visiting experience at World Heritage Sites (WHS) can be caused by perceived crowding.

So far, current literature has investigated the direct (either positive or negative) relationship between perceived crowding and post-visit behaviours of tourists (Nie et al., 2022; Papadopoulou, Ribeiro, & Prayag, 2023; Stemmer, Gjerald, & Øgaard, 2022). Broadening this area of research, the authors of this paper used the social interference theory and the stimulus-overload theory to explain the low level of tourist satisfaction and destination loyalty among tourists who highly value their visiting experience at WHS.

This paper aims to conduct a fuzzy discrete time cost quality risk in the ambiguous mode CO_{2 tradeoff problem} (FDTCQRP*TP) in a megaproject based on fuzzy ground.

A combinatorial evolutionary algorithm using Fuzzy Invasive Weed Optimization (FIWO) is used in the discrete form of the problem where the parameters are fully fuzzy multi-objective and provide a space incorporating all dimensions of the problem. Also, the fuzzy data and computations are used with the Chanas method selected for the computational analysis. Moreover, uncertainty is defined in FIWO. The presented FIWO simulation, its utility and superiority are tested on sample problems.

The reproduction, rearrangement and maintaining elite invasive weeds in FIWO can lead to a higher level of accuracy, convergence and strength for solving FDTCQRP*TP fuzzy rules and a risk ground in the ambiguous mode with the emphasis on the necessity of CO₂ pollution reduction. The results reveal the effectiveness of the algorithm and its flexibility in the megaproject managers' decision making, convergence and accuracy regarding CO₂ pollution reduction.

This paper offers a multi-objective fully fuzzy tradeoff in the ambiguous mode with the approach of CO₂ pollution reduction.

Road freight transportation companies need to take advantage of information and communication technologies to develop capabilities. This study proposes a framework to guide road freight transportation companies to achieve data visibility in their operations by developing such capabilities. By proposing this framework, this research contributes to literature and practice, highlighting the capabilities and the respective supporting technologies for improved data visibility in road freight transportation.

A mixed-method approach is used to develop the framework, considering three methodological steps. In phase 1, the capabilities are identified in the literature and validated by experts. In phase 2, an empirical assessment of cause–effect relationships between capabilities is performed using a multiple case study and DEMATEL. Lastly, in phase 3, an analysis of the cause model and significant associations is conducted to enable the development of the framework. In addition, the proposed framework was validated by the experts interviewed.

The results provide a framework that explains the link between the technology-enabled data visibility capabilities in road freight transportation operations. In addition, a pathway was established that road freight transportation companies could follow to achieve data visibility in their operations by developing such capabilities.

This work develops the first framework that provides a path for data visibility in road freight transportation operations from adopting certain technologies. The insights are compelling for researchers and practitioners to optimize the decision-making process for adopting technologies and developing capabilities related to data visibility.

The purpose of this paper is to study the high temperature oxidation behavior of Ti and C-added FeCoCrNiMn high entropy alloys (HEAs).

Cyclic oxidation method was used to obtain the oxidation kinetic profile and oxidation rate. The microstructures of the surface and cross section of the samples after oxidation were characterized by X-ray diffraction (XRD) and scanning electron microscope (SEM).

The results show that the microstructure of the alloy mainly consisted of FCC (Face-centered Cubic Structure) main phase and carbides (M₇C₃, M₂₃C₆ and TiC). With the increase of Ti and C content, the microhardness, strength and oxidation resistance of the alloy were effectively improved. After oxidation at a constant temperature of 800 °C for 100 h, the preferential oxidation of chromium in the chromium carbide determined the early formation of dense chromium oxide layers compared to the HEAs substrate, resulting in the optimal oxidation resistance of the TC30 alloy.

More precipitated CrC can preferentially oxidize and rapidly form a dense Cr₂O₃ layer early in the oxidation, which will slow down the further oxidation of the alloy.

Brand crowdfunding, launched through brands’ social media platforms, can provide a myriad of crowdfunding and branding benefits, such as strengthening brands’ social networks, validating product launches, generating mass exposure and enabling cocreation. Gamification positions brand crowdfunding as an exciting and joyful activity that more deeply engages prosumers. Anchored on resource-based theory, theory of planned behavior and service-dominant logic, this paper aims to develop a brand crowdfunding framework for established brands with insights from two emerging markets: China and India.

A deductive cross-sectional design is used to gather data from an established brand’s (e.g. Xiaomi) social media followers in China (n = 826) and India (n = 358), which is analyzed through PLSc-SEM.

The results reveal that social media brand engagement is an antecedent of brand crowdfunding participation, brand crowdfunding intention is a predictor of brand loyalty and gamification is a significant moderator in technology-oriented societies.

The paper develops a brand crowdfunding framework that provides insights on how established brands can leverage crowdfunding to enhance their new product development process. The results contribute to the social media brand engagement, crowdfunding, gamification and emerging markets literature.

This study aims to proposed that blockchain helps the organization improve supply chain (SC) performance by improving integration, agility and security through real-time information sharing, end-to-end visibility, transparency, data management, immutability, irrevocable information and cyber-security platforms.

This study has made an initial effort toward proposing a framework that shows the problems and challenges for the O&G SC under its segments (upstream, midstream and downstream) and provides the interlink among blockchain properties for SCM problems. SC managers were selected for survey questionnaires from the Pakistan O&G industries.

This study analyzes the impact of blockchain-enabled SC on firm performance with an understanding of the SC robustness capabilities as a mediator. The result revealed that the SC manager believes that the blockchain-enabled SC has a positive and significant on firm performance and robustness capabilities.

Blockchain technology is reflected as high-tech to support the firm process, responses and methods. The technology helps eliminate bottlenecks, avoid uncertainties and improve decision-making, leading to improved SC functions. This study guides managers about the potential problems of existing SC and how blockchain solves SC problems more effectively.

The oil and gas (O&G) sectors are neglected by researchers, and there are limited studies on O&G supply chain management (SCM). Additionally, no empirical evidence suggests implementing blockchain for O&G as a solution for potential problems. Furthermore, present the roadmap to other industries those having complex SC networks for the implication of blockchain to improve the SC performance.