PurposeThis study aims to advance the understanding of digital marketing capability by conducting a comprehensive, systematic review of relevant literature at the firm level.Design/methodology/approachThe study utilizes categorization and contextualization of qualitative methodologies to review the literature, using Scopus databases to collect 57 journals with 143 peer-reviewed papers as the main focus. The research gaps and DMCs were analyzed and synthesized and presented as collective categorization together with the proposed future direction framework.FindingsThis study proposed the relevance of digital marketing capabilities for businesses and the key measurement of business performance. The proposed dimensions of the digital marketing capabilities framework are to identify new research directions for both marketing and IT strands.Originality/valueThis study classify five main different themes in digital marketing incorporating with digital technologies (DTs) era and proposed relevance of digital marketing capabilities for businesses (B2C and B2B) and keys measurement of business performances.
This study is part of a government research project which aims to synthesise the current evidence on the factors affecting the intention of mobile application adoption called ‘Tripper Notifier Application’ (TNA) for the hospitality and tourism industrial sector in Thailand. The focus is on small and medium enterprises (SMEs), which emphasize restaurants, hotels, and attraction sites. The present article examines various factors influencing the intention to use such applications by employing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) as the theoretical underpinning of this research paradigm. Using 84 selected research papers in Scopus published between 2020 and 2022, A thematic analysis incorporating a grounded theory approach to systematically generate themes was conducted, and the findings found three main themes, including business transformation capabilities (BTC), digital transformation capabilities (DTC), and personal innovativeness (PI), as an extension of UTAUT-2 as mediator and moderator variables. To this end, the study fills the research gaps and extends the UTAUT-2 framework by including an initiative of twelve inside attributes-based lines, including performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit behavior, behavioral intention, and use behavior, together with three moderators: age, gender, and experience. Finally, the context dimensions of the UTAUT-2 extensions were mapped to highlight all the constructs of the TNA adoption framework for future research directions. The novel contribution of this study is to fill the gap with both theoretical and practical knowledge. On the theoretical level, this study constitutes constructs based on UTAUT-2 theory as a research-based setting to fill a gap in research. On the practical level, it provides insights and information about new capabilities that SME owners, managers, and practitioners should consider in order to differentiate their own capabilities. Doi: 10.28991/esj-2021-SP1-014 Full Text: PDF
This empirical research study aimed to examine factors influencing consumer’s behavioral intentions to purchase products via live-streaming services. This study proposed four key factors, namely customer perception, marketing mix, content marketing, and influencer, and tested their relationships with the perceived value and attitude through consumer’s behavior. At the same time, the path analysis of the perceived value and attitude was conducted to reveal the relationships with consumer’s behavioral intentions through consumer’s online purchase intention. The proposed theoretical model comprised relevant variables developed from the current literature on digital marketing disciplines under three theoretical strands, where the Theory of Planned Behavior (TPB) was established as the main theory. The study tested the structural model using cross-sectional data. Purposive sampling was used to administer a questionnaire to 198 participants who had experience with livestreaming online shopping, and the data was analyzed using the Partial Least Squares (PLS) approach and regression analysis. The findings showed that customer perception and marketing mix had significant positive impacts on perceived value. Content marketing and influencer marketing also had positive relationships with consumer’s attitudes. Moreover, consumer’s perceived value and attitudes influenced their behavior and actions. These results reaffirmed the positive role of consumer’s behavioral intentions in their online purchase intentions.
PurposeThe study aims to advance understanding of the intention of Augmented Reality (AR) technology adoption by conducting a systematic review of relevant literature articles in the hospitality sector where 93 articles were chosen and synthesized by generating a theme and proposing a conceptual framework with their research proposals.Design/methodology/approachA systematic literature review (SLR) has been conducted incorporating thematic analysis to investigate various determinants from selected articles and to identify the key themes in order to propose a conceptual framework and research proposal.FindingsThe findings reveal seven major themes in its research proposal for future research directions. This includes “Technology Engagement”, “Resilience”, “Knowledge is key”, “Readiness for changes”, “Uncertainty management”, “Environmental conditions” and “Business performance”.Originality/valueThe novel contribution of this study is that it focuses on both theoretical and practical knowledge. On the theoretical level, this study comprises factors that apply relevant theory in the areas of information technology and business management, whose integrative theoretical orientation provided insight into the AR adoption initiatives and to further examine the relationship between its proposed factors. On the practical level, it provides insights and information with a new body of knowledge that business owner–managers, policymakers and practitioners should consider in order to craft a strategic adoption of AR technology.
Forensic entomology is the branch of forensic science that is related to using arthropod specimens found in legal issues. Fly maggots are one of crucial pieces of evidence that can be used for estimating post-mortem intervals worldwide. However, the species-level identification of fly maggots is difficult, time consuming, and requires specialized taxonomic training. In this work, a novel method for the identification of different forensically-important fly species is proposed using convolutional neural networks (CNNs). The data used for the experiment were obtained from a digital camera connected to a compound microscope. We compared the performance of four widely used models that vary in complexity of architecture to evaluate tradeoffs in accuracy and speed for species classification including ResNet-101, Densenet161, Vgg19_bn, and AlexNet. In the validation step, all of the studied models provided 100% accuracy for identifying maggots of 4 species including Chrysomya megacephala (Diptera: Calliphoridae), Chrysomya (Achoetandrus) rufifacies (Diptera: Calliphoridae), Lucilia cuprina (Diptera: Calliphoridae), and Musca domestica (Diptera: Muscidae) based on images of posterior spiracles. However, AlexNet showed the fastest speed to process the identification model and presented a good balance between performance and speed. Therefore, the AlexNet model was selected for the testing step. The results of the confusion matrix of AlexNet showed that misclassification was found between C. megacephala and C. (Achoetandrus) rufifacies as well as between C. megacephala and L. cuprina. No misclassification was found for M. domestica. In addition, we created a web-application platform called thefly.ai to help users identify species of fly maggots in their own images using our classification model. The results from this study can be applied to identify further species by using other types of images. This model can also be used in the development of identification features in mobile applications. This study is a crucial step for integrating information from biology and AI-technology to develop a novel platform for use in forensic investigation.
Purpose The purpose of this research is to provide a strategic framework for business resilience plans (BRPs) to guide micro, small, and medium-sized firms (MSMEs) in determining their adaptability level and providing information on agility and resilience tactics while coping with turbulence. Design/methodology/approach A systematic literature review (SLR) is used in this work to collect and acquire a complete and high-quality sample of academic journal articles. As the primary focus, 63 high-quality journals were chosen from 154 academic papers in the Scopus and Web of Science databases by using qualitative data analysis. The method of thematic analysis incorporating grounded approach analysis was utilized for creating themes and key findings in this study. Findings This study proposes the dimensions of the BRPs framework along with key findings to identify future research directions for MSMEs. The three dimensions of BRP include responsiveness, reactiveness, and proactiveness based on the principles of agility, absorption, and resilience. Originality/value This study proposes a sustainable and resilient framework for post-disaster MSMEs as a catalyst towards sustainably resilient MSMEs. This study highlights viable avenues for future research for academics and provides a resilient plan at various levels for business owner-managers.
Manuscript type: Research paper Research aims: This study aims to investigate the role of short-form video content (SVC) in the association between marketing capabilities, influencers, and business brand engagement performance. Design/Methodology/Approach: Data was collected from 146 business owners and managers of private businesses from the central business district areas of the lower northern province of Thailand. A partial least square structure equation modelling (PLS-SEM) analysis was performed to examine the proposed relationships. Research findings: The findings indicate that SVCs enabled brand engagement and resulted in increased satisfaction with the influencer experience. The study found a positive relationship between marketing capabilities, SVCs, influencers, and brand engagement performance. Theoretical contribution/Originality: This study also contributes by providing empirical evidence of the mediation of short-form video content in the relationship between marketing capabilities and brand performance, thus suggesting that, in terms of the resource-based view (RBV), SVCs integrated with marketing capabilities contribute to fostering influencers to promote brand perception values into competitive advantage, while influencers are reaffirmed as having a positive impact on brand performance. Practitioner/Policy implications: This research also provides a practical outlook for businesses to better understand the adoption of SVCs at an initial stage and important practical implications for business entrepreneurs, managers, and practitioners regarding the use of SVCs to improve brand engagement performance. Research limitation: First, this study was limited by its focus on primary data collected using a survey approach. Therefore, future research may need to emphasise more subjective rather than objective research. Second, as this study focuses on top executives and higher levels of marketing managers, it could introduce potential biases. Further research, through the use of multiple informants (i.e., IT managers, lower-level frontline staff, etc.) in each business with well-rounded perspectives, could provide a deeper insight into the issues regarding such initiatives. Finally, more constructs related to the proposed research framework can be investigated.
Forensic entomology is the branch of forensic science that is related to using arthropod specimens found in legal issues. Fly maggots are one of crucial pieces of evidence that can be used for estimating post-mortem intervals worldwide. However, the species-level identification of fly maggots is difficult, time consuming, and requires specialized taxonomic training. In this work, a novel method for the identification of different forensically-important fly species is proposed using convolutional neural networks (CNNs). The data used for the experiment were obtained from a digital camera connected to a compound microscope. We compared the performance of four widely used models that vary in complexity of architecture to evaluate tradeoffs in accuracy and speed for species classification including ResNet-101, Densenet161, Vgg19_bn, and AlexNet. In the validation step, all of the studied models provided 100% accuracy for identifying maggots of 4 species including Chrysomya megacephala (Diptera: Calliphoridae), Chrysomya (Achoetandrus) rufifacies (Diptera: Calliphoridae), Lucilia cuprina (Diptera: Calliphoridae), and Musca domestica (Diptera: Muscidae) based on images of posterior spiracles. However, AlexNet showed the fastest speed to process the identification model and presented a good balance between performance and speed. Therefore, the AlexNet model was selected for the testing step. The results of the confusion matrix of AlexNet showed that misclassification was found between C. megacephala and C. (Achoetandrus) rufifacies as well as between C. megacephala and L. cuprina. No misclassification was found for M. domestica. In addition, we created a web-application platform called thefly.ai to help users identify species of fly maggots in their own images using our classification model. The results from this study can be applied to identify further species by using other types of images. This model can also be used in the development of identification features in mobile applications. This study is a crucial step for integrating information from biology and AI-technology to develop a novel platform for use in forensic investigation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.