Zeitschriftenartikel zum Thema „Proximity, innovation, business model, topic modeling“

The topic raised in this research is the emphasis on the relevance of Business Model Innovation (BMI). Based on this, the purpose of this study is to explore the management approach and Business Model Innovation (BMI) to foster SMEs in Kolaka Regency with an approach that connects management capabilities to Business Model Innovation (BMI). This is purposively from 89 SMEs in Kolaka Regency, Southeast Sulawesi Province by adopting the Qualitative Comparative Analysis (QCA) method. The data analysis technique used in this study also uses the concept of Structural Equatin Modeling (SEM) with the Partial Least Square (PLS) program using a configuration approach, the results show that management ability shows a significant influence on Business Model Innovation (BMI). The results of fsQCA strengthen these findings and refine SEM which provides good conditions for the development of Business Model Innovation (BMI).

Purpose This paper aims to use the proximity approach of economic geography with its spatial dimension (geographic) and their non-spatial dimensions (social, institutional, cognitive and organizational) to shed light on the determinants of business cooperation with other organizations. It is also examined whetherthis cooperation is a determining factor for business innovation (innovation networks), drawing a distinction between technological and non-technological innovations. Design/methodology/approach The study has a quantitative approach; it analyzes the case of 312 companies in a cluster of agribusinesses in an emerging economy (Chile). The proposal model and its interrelations are tested with exploratory factor analysis, confirmatory factor analysis and structural equation modeling. Findings The results show that cognitive-organizational proximity is a positive determinant of business cooperation with other organizations, whereas social and institutional proximity are negative determinants. It is also established that business cooperation is a positive determinant of business innovation. It is more relevant in the case of technological innovation unlike non-technological innovations. In addition, it is noted that business cooperation levels are lower in micro-enterprises, a result that differs from developed countries. Practical implications For business managers, it is best to cooperate with companies that are similar in terms of cognitive and organizational levels for innovation. At the same time, it is necessary develop strategies to reduce the social and institutional barriers to cooperation, especially in the agribusiness sector. Originality/value The contributions of the study are as follows: an in-depth quantitative examination of the relationships of various non-spatial proximities as determinants of business cooperation; an analysis of whether business cooperation with other organizations is a determining factor for business innovation, distinguishing between technological and non-technological innovation; and testing these relationships in the context of agribusiness in an emerging economy such as Chile’s because most of studies are related to high-tech sector and developed economies.

Purpose Although the business model field of study has been a focus of attention for both researchers and practitioners within the past two decades, it still suffers from concern about its identity. Accordingly, this paper aims to clarify the intellectual structure of business model through identifying the research clusters and their sub-clusters, the prominent relations and the dominant research trends. Design/methodology/approach This paper uses some common text mining methods including co-word analysis, burst analysis, timeline analysis and topic modeling to analyze and mine the title, abstract and keywords of 14,081 research documents related to the domain of business model. Findings The results revealed that the business model field of study consists of three main research areas including electronic business model, business model innovation and sustainable business model, each of which has some sub-areas and has been more evident in some particular industries. Additionally, from the time perspective, research issues in the domain of sustainable development are considered as the hot and emerging topics in this field. In addition, the results confirmed that information technology has been one of the most important drivers, influencing the appearance of different study topics in the various periods. Originality/value The contribution of this study is to quantitatively uncover the dominant knowledge structure and prominent research trends in the business model field of study, considering a broad range of scholarly publications and using some promising and reliable text mining techniques.

PurposeThe purpose of this paper is to investigate the role of cognitive proximity on supply chain collaboration and how it relates to radical and incremental innovation.Design/methodology/approachThe paper is based on quantitative approach to analyze the data of 218 firms in a developing and transition economy. The proposal model is tested with exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM).FindingsThe authors’ findings show that cognitive proximity facilitates decision synchronization and incentive alignment in the supply chain. Furthermore, the authors’ results indicate that information sharing and decision synchronization are determinants of radical innovation while incentive alignment is a determinant of incremental innovation.Research limitations/implicationsThis study was cross-sectional, so the authors could not consider the control variable such as sectors or firms’ size. It is hard to control the specific features of cognitive proximity in one single industry when using cross-sectional data. In future investigations, it may be possible to use a different dimension of proximity to explain the implementation of collaboration for innovation.Originality/valueThis study attempted to explore the role of cognitive proximity on supply chain implementation process in the context of a transition economy. Moreover, the authors’ findings provide the clearer understanding of the relationship between collaboration and innovation.

Exploring areas of innovation and development and promoting total factor productivity is a topic that is crucial to implementing innovation-driven strategies and building a modern economic system in the Hubei province in China. So, the aim of the research is to find a methodology for computing innovation performance and its influence factors in the Hubei region of China. Based on the existing efficiency measurement methods, this study measures the innovation efficiency performance and subsequently the innovation performance by using the optimized Färe-Primont index for a sample of 28 manufacturing industries in Hubei. A threshold regression model of multidimensional explanatory variables focusing on business performance, government support, industry openness, and synergic innovation is used to investigate the core factors that affect the improvement of innovation performance in Hubei’s manufacturing industries. Results show that there is a significant “technological heterogeneity” in Hubei’s manufacturing industries. Business performance plays a significant role in promoting the innovation performance of manufacturing industries, while the roles of industry development, government support, and synergic innovation on innovation performance change depending on the “technological characteristics” of industries.

This study presents a systematic approach that integrates the information adoption model (IAM) with topic modeling to analyze the digital voice of users in online open innovation communities (OOICs) and empirically examines the usefulness of UGC with large amounts of redundant information and varying content quality across two dimensions: information quality and information source credibility. A total of 61,227 bug comments were collected from the OOIC of Huawei EMUI and analyzed using binary logistic regression. The results show that information timeliness and completeness have a positive effect on the usefulness of UGC in OOICs; conversely, information semantics have a negative effect on the usefulness of UGC. Prior user experience has no influence on the usefulness of UGC in OOICs, while active user contribution has a positive effect on the usefulness of UGC. The results of this study offer several implications to researchers and practitioners, and thus could serve as a pivotal reference source for further investigation of potential determinants of UGC usefulness in OOICs.

The startup business ecosystem in India has experienced exponential growth. The amount of investment in Indian startups in the last decade demonstrates the strong interest of the technology industry to these business models based on innovation. In this context, the present study aims to identify investment opportunities for investors in Indian startups by identifying key indicators that characterize the startup ecosystem in India. To this end, a three steps data mining method is developed using data mining techniques. First, a sentiment analysis (SA), a machine learning approach that classifies the topics into groups expressing feelings, is applied to a dataset. Next, we develop a Latent Dirichlet Allocation (LDA) model, a topic-modeling technique that divides the sample of n = 14.531 tweets from Twitter into topics, using user-generated content (UGC) as data. Finally, in order to identify the characteristics of each topic we apply textual analysis (TA) to identify key indicators. The originality of the present study lies in the methodological process used for data analysis. Our results also contribute to the literature on startups. The results demonstrate that the Indian startup ecosystem is influenced by areas such as fintech, innovation, crowdfunding, hardware, funds, competition, artificial intelligence, augmented reality and electronic commerce. Of note, in view of the exploratory approach of the present study, the results and implications should be taken as descriptive, rather than determining for future investments in the Indian startup ecosystem.

For mobile and multi-channel information systems it is often relevant to model where something is supposed to take place. Traditional business process modeling notations seldom capture location. Examining if there might be any gain in extending mainstream modeling notations with the capture of location is an interesting research topic. This paper addresses this question both through an analytical comparison of various notation alternatives and two experiments investigating different ways of visualizing location. The results of the experiments indicate that the notation using color for distinguishing different places have advantage over textual annotations, whereas no significant difference was found between the use color and pattern fills when it came to the subjects’ performance solving the experimental tasks.

In order to help Energy Internet (EI) enterprises develop sustainably, promote the transformation and upgrading of energy systems and achieve the goal of carbon peaking and carbon neutrality, a study on the influencing factors of green technology innovation (GTI) in EI enterprises was conducted using the Decision-making Trial and Evaluation Laboratory-Adversarial Interpretive Structure Modeling Method (DEMATEL-AISM). Through a literature review and field research, the DEMATEL-AISM-based model of the GTI influencing factors of EI enterprises was constructed on the basis of summarizing the system of GTI influencing factors of EI enterprises, visualizing the interrelationship and hierarchical structure among GTI influencing factors of EI enterprises and finally proposing relevant countermeasures and suggestions. This study shows that the proximity-level factors such as R&D investment and external cooperation directly affect the GTI of EI enterprises; the essential-level factors such as environmental regulation and development strategy are the root causes of the GTI of EI enterprises. The transition-level factors such as market competition and business model are the key nodes of the GTI of EI enterprises, and the above factors should be focused on.

Purpose- Protecting the natural environment and its wealth for future generations has become an essential topic for policymakers and executives. This study seeks to examine the impact of green Human Resource Management practices through green innovation on the environmental performance of small and medium-sized manufacturing enterprises in Ghana. Design/Methodology- Through simple random probability sampling, data were obtained from three hundred (300) business owners and employees from ten (10) small and medium-sized manufacturing enterprises in the Greater Accra Region of Ghana. However, two hundred and ninety-four (294) accurate responses were used in the analysis due to incomplete and missing figures. Data were analyzed using partial least squared based on Structural Equation Modeling (SEM). Findings- The studied data met internal consistency reliability, convergent, and discriminant validity from the results, and also, there was no multicollinearity issue in the study model. The findings revealed that green Human Resource Management practices directly and significantly influence environmental performance. Furthermore, green innovation partially mediated the influence of green Human Resource Management practices on environmental performance. Green compensation through green innovation has the most incredible impact on environmental performance and was statistically significant at p< 0.01. Practical Implications- This finding provides valuable suggestions for policymakers, emerging and existing organizations, particularly manufacturing firms, to encourage environmentally-friendly activities and produce goods and processes through a successful incentive scheme, thus increasing customer loyalty.

The relevance of the chosen topic is related to the growing interest of researchers in technologies and mechanisms of growth of new touristic opportunities in the smart era of society, features of its impact on national policies in order to achieve strategic socio-economic goals of the countries both for domestic territories and along the path of development of geoeconomic strategies in the global space. In addition the relevance of the research direction is enhanced by the fact that tourism is one of the sectors of the world economy that has suffered the most from restrictions on movement during the pandemic crisis. The European Commission has recently presented a series of proposals setting out the foundations of the EU economy and society suitable for the digital age, outlining the development of a genuine European data space and offering a European approach to new technologies. The new industrial strategy and the SME strategy (adopted on March 10, 2020) identify the path to digital transformation to empower industry and small and medium-sized enterprises. The latest strategic communication of the European Commission “Tourism and Transport for 2020 and beyond” emphasizes the role of digital transformation and sustainability. This involves investing in digital skills and promoting digital innovation, as well as linking the tourism business and businesses to existing data spaces, technology providers, and community actors at the local and regional levels. To determine the possibilities of further evelopment of the industry, ithe article proposes a factor model of the total revenue from tourism activities, taking into account regional changes in tourist flow, provide recommendations for the effective development of the industry with account of future trands of tourism industry and ecosystem development. These issues are equally pertinent both for tourism, given the advantages innovative, new technologies can bring to tourism destinations and for businesses, local communities and travellers. They can facilitate tourism management both at destination and business level, contributing to balanced and sustainable growth of tourism in post Pandemic time. New smart technologies can help businesses provide more personalised services and therefore enhance the tourism experience.

This article considers the problem of finding text documents similar in meaning in the corpus. We investigate a problem arising when developing applied intelligent information systems that is non-detection of a part of solutions by the TF-IDF algorithm: one can lose some document pairs that are similar according to human assessment, but receive a low similarity assessment from the program. A modification of the algorithm, with the replacement of the complete vocabulary with a vocabulary of specific terms is proposed. The addition of thesauri when building a corpus vector model based on a ranking function has not been previously investigated; the use of thesauri has so far been studied only to improve topic models. The purpose of this work is to improve the quality of the solution by minimizing the loss of its significant part and not adding “false similar” pairs of documents. The improvement is provided by the use of a vocabulary of specific terms extracted from the text of the analyzed documents when calculating the TF-IDF values for corpus vector representation. The experiment was carried out on two corpora of structured normative and technical documents united by a subject: state standards related to information technology and to the field of railways. The glossary of specific terms was compiled by automatic analysis of the text of the documents under consideration, and rule-based NER methods were used. It was demonstrated that the calculation of TF-IDF based on the terminology vocabulary gives more relevant results for the problem under study, which confirmed the hypothesis put forward. The proposed method is less dependent on the shortcomings of the text layer (such as recognition errors) than the calculation of the documents’ proximity using the complete vocabulary of the corpus. We determined the factors that can affect the quality of the decision: the way of compiling a terminology vocabulary, the choice of the range of n-grams for the vocabulary, the correctness of the wording of specific terms and the validity of their inclusion in the glossary of the document. The findings can be used to solve applied problems related to the search for documents that are close in meaning, such as semantic search, taking into account the subject area, corporate search in multi-user mode, detection of hidden plagiarism, identification of contradictions in a collection of documents, determination of novelty in documents when building a knowledge base.

Credit fraud modeling is an important topic covered by researchers. Overdue risk management is a critical business link in providing credit loan services. It directly impacts the rate of return and the bad debt percentage of lending organizations in this sector. Credit financial services have benefited the general public as a result of the development of the mobile Internet, and overdue risk control has evolved from the manual judgment that relied on rules in the past to a credit model built using a large amount of customer data to predict the likelihood of customers becoming delinquent. When creating a credit rating model, the emerging nature of the credit samples makes the minority class sample score very few; that is, when a large number of actual samples are obtained, this causes machine learning models to be biased towards the majority class when training. Traditional data balancing methods can reduce the bias of models to the majority category when the data is relatively unbalanced rather than excessive. Gradient boosting algorithms (XGBoost and CatBoost) are proposed in this paper to model highly unbalanced data to detect credit fraud. To find hyperparameters and determine the accuracy of the minority class as an optimization function of the model, Bayesian optimization is used to increase the model's accuracy for the minority class. The paper was tested with real European credit card fraud data. The results were compared to traditional machine learning (decision trees and logistic regression) and the performance of the bagging algorithm (random forest). For comparison, the traditional data balancing method (Oversample) is used

Relevance of the research topic. Continuous expansion of virtual networks, digitalization of all processes, transformation of global technologies lead not only to the development of new types of economic relations, but also to the logical change of traditional types of business. Formulation of the problem. The lack of a common definition of network structures management at the level of foreign economic and international activities in the digital century leads to slowing down the development of virtual enterprises in Ukraine and insufficient isolation of significant competitive advantages in the modern innovation and investment model of Ukrainian economy. Analysis of recent research and publications. To date, Timashova L., Serdyuk S., Shingur M., Amor D., Byrne JA, Brandt R., Davidow W., Malone M., Port O. have studied certain technological processes and business models of virtual enterprises, but in practice, there are no similar studies for implementation in the Ukrainian economy and no research on the management of virtual enterprises engaged in foreign economic activity. Selection of unexplored parts of the general problem. Drawing attention to the virtualization of production processes in the implementation of foreign economic activity contributes to the revision of the management strategy of the virtual enterprise to ensure its competitiveness in the long run. Problem setting, research goals. The objectives of the study are: to substantiate the key role of management of foreign economic activity for enterprises operating in virtual networks; to study modern conditions of virtual enterprises functioning; to determine the influence of the digital economy factors on the formation of management properties in them; analyze local goals and objectives of virtual enterprises in accordance with business models. The purpose of the study is a comprehensive scientific abstraction to the interpretation of the concept of "virtual enterprise engaged in foreign economic activity", and to analyze the peculiarities of the development of this network structure in Ukraine. Research methods. To achieve the goal of the article, a set of formal and informal methods of modeling and forecasting was used; operational-applied and analytical-prognostic; systemic; comparative analysis and theoretical generalization. Presentation of the main material (results of work). The article examines the conditions and functionality of creating a virtual enterprise engaged in foreign economic activity, as a new network form of online business. The expediency of creating virtual enterprises in order to intensify the process of business design and efficiency of business startups is substantiated. The main stages, goals and objectives are highlighted and the peculiarities of creating a virtual enterprise engaged in foreign economic activity are determined. Ways to accelerate the creation of virtual enterprises in Ukraine are proposed. Field of application of results: training courses in management and entrepreneurship, practical activities in business incubators to create innovative modern startups. Conclusions according to the article. The creation of Ukrainian virtual enterprises engaged in foreign economic activity will contribute to the formation of effective business design and development of intellectualization and digitalization of production, integration of resources, a transformation of global technologies in the Ukrainian market. Virtual enterprises of national origin have all the prerequisites and opportunities to enter foreign markets through cybersecurity and coordination of global business models and business processes, taking into account all existing risks.

Solar power systems and their related technologies have developed into a globally utilized green energy source. Given the relatively high installation costs, low conversion rates and battery capacity issues, solar energy is still not a widely applied energy source when compared to traditional energy sources. Despite the challenges, there are many innovative studies of new materials and new methods for improving solar energy transformation efficiency to improve the competitiveness of solar energy in the marketplace. This research searches for promising solar power technologies by text mining 2280 global patents and 5610 literature papers of the past decade (January 2008 to June 2018). First, a solar power knowledge ontology schema (or a key term relationship map) is constructed from the comprehensive literature and patent review. Non-supervised machine learning techniques for clustering patents and literature combined with the Latent Dirichlet Allocation (LDA) topic modeling algorithm identify sub-technology clusters and their main topics. A word-embedding algorithm is applied to identify the patent documents of the specified technologies. Cross-validation of the results is used to model the technology progress with a patent evolution map. Initial analysis show that many patents focus on solar hydropower storage systems, transferring light generated power to waterpower gravity systems. Batteries are also used but have several limitations. The objectives of this research are to review solar technology development progress and describe the innovation path that has evolved for the solar power domain. By adopting unsupervised learning approaches for literature and patent mining, this research develops a novel technology e-discovery methodology and presents the detailed reviews and analyses of the solar power technology using the proposed e-discovery workflow. The insights of global solar technology development, based on both comprehensive literature and patent reviews and cross-analyses, helps energy companies select advanced technologies related to their key technical R&D strengths and business interests. The structured solar-related technology mining can be extended to the analysis of other forms of renewable energy development.

Modern technologies and various domains of human activities increasingly rely on data science to develop smarter and autonomous systems. This trend has already changed the whole landscape of the global economy becoming more AI-driven. Massive production of data by humans and machines, its availability for feasible processing with advent of deep learning infrastructures, combined with advancements in reliable information transfer capacities, open unbounded horizons for societal progress in close future. Quite naturally, this brings also new challenges for science and industry. In that context, Internet of things (IoT) is an enormously huge factory of monitoring and data generation. It enables countless devices to act as sensors which record and manipulate data, while requiring efficient algorithms to derive actionable knowledge. Billions of end-users equipped with smart mobile phones are also producing immensely large volumes of data, being it about user interaction or indirect telemetry such as location coordinates. Social networks represent another kind of data-intensive sources, with both structured and unstructured components, containing valuable information about world&rsquo;s connectivity, dynamism, and more. Last but not least, to help businesses run smoothly, today&rsquo;s cloud computing infrastructures and applications are also serviced and managed through measuring huge amounts of data to leverage in various predictive and automation tasks for healthy performance and permanent availability. Therefore, all these technology areas, experts and practitioners, are facing innovation challenges on building novel methodologies, accurate models, and systems for respective data-driven solutions which are effective and efficient. In view of the complexity of contemporary neural network architectures and models with millions of parameters they derive, one of such challenges is related to the concept of explainability of the machine learning models. It refers to the ability of the model to give information which can be interpreted by humans about the reasons for the decision made or recommendation released. These challenges can only be met with a mix of basic research, process modeling and simulation under uncertainty using qualitative and quantitative methods from the involved sciences, and taking into account international standards and adequate evaluation methods. Based on a successful funded collaboration between the American University of Armenia, the University of Duisburg-Essen and the University of Chile, in previous years a network was built, and in September 2020 a group of researchers gathered (although virtually) for the 2nd CODASSCA workshop on &ldquo;Collaborative Technologies and Data Science in Smart City Applications&rdquo;. This event has attracted 25 paper submissions which deal with the problems and challenges mentioned above. The studies are in specialized areas and disclose novel solutions and approaches based on existing theories suitably applied. The authors of the best papers published in the conference proceedings on Collaborative Technologies and Data Science in Artificial Intelligence Applications by Logos edition Berlin were invited to submit significantly extended and improved versions of their contributions to be considered for a journal special issue of J.UCS. There was also a J.UCS open call so that any author could submit papers on the highlighted subject. For this volume, we selected those dealing with more theoretical issues which were rigorously reviewed in three rounds and 6 papers nominated to be published. The editors would like to express their gratitude to J.UCS foundation for accepting the special issues in their journal, to the German Research Foundation (DFG), the German Academic Exchange Service (DAAD) and the universities and sponsors involved for funding the common activities and thank the editors of the CODASSCA2020 proceedings for their ongoing encouragement and support, the authors for their contributions, and the anonymous reviewers for their invaluable support. The paper &ldquo;Incident Management for Explainable and Automated Root Cause Analysis in Cloud Data Centers&rdquo; by Arnak Poghosyan, Ashot Harutyunyan, Naira Grigoryan, and Nicholas Kushmerick addresses an increasingly important problem towards autonomous or self-X systems, intelligent management of modern cloud environments with an emphasis on explainable AI. It demonstrates techniques and methods that greatly help in automated discovery of explicit conditions leading to data center incidents. The paper &ldquo;Temporal Accelerators: Unleashing the Potential of Embedded FPGAs&rdquo; by Christopher Cichiwskyj and Gregor Schiele presents an approach for executing computational tasks that can be split into sequential sub-tasks. It divides accelerators into multiple, smaller parts and uses the reconfiguration capabilities of the FPGA to execute the parts according to a task graph. That improves the energy consumption and the cost of using FPGAs in IoT devices. The paper &ldquo;On Recurrent Neural Network based Theorem Prover for First Order Minimal Logic&rdquo; by Ashot Baghdasaryan and Hovhannes Bolibekyan investigates using recurrent neural networks to determine the order of proof search in a sequent calculus for first-order minimal logic with a history mechanism. It demonstrates reduced durations in automated theorem proving systems.&nbsp; The paper &ldquo;Incremental Autoencoders for Text Streams Clustering in Social Networks&rdquo; by Amal Rekik and Salma Jamoussi proposes a deep learning method to identify trending topics in a social network. It is built on detecting changes in streams of tweets. The method is experimentally validated to outperform relevant data stream algorithms in identifying &ldquo;hot&rdquo; topics. The paper &ldquo;E-Capacity&ndash;Equivocation Region of Wiretap Channel&rdquo; by Mariam Haroutunian studies a secure communication problem over the wiretap channel, where information transfer from the source to a legitimate receiver needs to be realized maximally secretly for an eavesdropper. This is an information-theoretic research which generalizes the capacity-equivocation region and secrecy-capacity function of the wiretap channel subject to error exponent criterion, thus deriving new and extended fundamental limits in reliable and secure communication in presence of a wiretapper. The paper &ldquo;Leveraging Multifaceted Proximity Measures among Developers in Predicting Future Collaborations to Improve the Social Capital of Software Projects&rdquo; by Amit Kumar and Sonali Agarwal targets improving the social capital of individual software developers and projects using machine learning. Authors&rsquo; approach applies network proximity and developer activity features to build a classifier for predicting the future collaborations among developers and generating relevant recommendations.

Purpose The purpose of this paper is to investigate the relationship between e-marketing (eM) and consumers’ buying behavior particularly exploratory buying behavior tendencies (EBBT) with moderating effect of a gender in the context of China. Design/methodology/approach Structural equation modeling using SPSS/AMOS was majorly applied to ascertain the relationship and hypotheses testing. First, the correlation of eM toward EBBT is examined using five factors: internet marketing (IM), e-mail marketing (EMa), intranet marketing (IMa), extranet marketing (EM), and mobile marketing (MM). Second, the relationship of each dimension of the eM model is determined autonomously to ensure the importance of such emerging technologies in marketing communications. Third, the effect of gender as a moderator is measured. To this end, primary data were collected through random distribution of the questionnaires among 1,600 consumers particularly students of the universities between February 2016 and August 2016 within North China. Findings The findings revealed that eM has a significant correlation on consumers’ EBBT. The comprehensive analysis of each factor of eM, i.e., IM, EMa, IMa, EM, and MM is positively correlated to EBBT. The present study revealed that gender did not moderate among the relationships of eM and EBBT. Additionally, study furnishes practical directions on how managers can utilize such emerging and revolutionary technologies in marketing activities to probe, understand, and reinforce consumers’ buying behavior. Research limitations/implications The research has limitations related to geographical location and sample size which thus limits the widespread generalization. Practical implications This study affirmed that organizations must engage the consumers using such technologies that are more likely acceptable by consumers in the present customer-oriented and digital era. The marketers must engage consumers the way they wish to be engaged by developing appropriate promotional strategies. The study provides possible implications both theoretical and managerial along with a contribution to the literature of eM and consumers’ buying behavior. Social implications Understanding the emerging technologies may furnish valuable insights for individuals to work well within Chinese SMEs. Originality/value The topic of eM has acknowledged as an evolving concept which is gaining an intense concern of both academician and practitioners. Therefore, more research mainly empirical work is still needed to probe the insights of eM across the globe. This study attempts to fulfill such need with empirical evidence together with an in-depth examination of eM determinants, collectively and autonomously.

Purpose This paper aims to define and measure the environmental capabilities that are applied when the circular economy (CE) is introduced in businesses. Founded on the dynamic capabilities theoretical approach, the study analyzes different environmental competences that firms apply during this process. Environmental management systems, corporate social responsibility, reporting and accountability and other environmental accounting practices are studied in the same analytical framework used to study the environmental capabilities that influence the circular scope (CS) of firms. This study contributes to bridging the gap between academic research focused on environmental accounting and that investigating the introduction of the CE in businesses. Design/methodology/approach The results were obtained by using partial least squares structural equation modeling to analyze the relationship between environmental capabilities for the CE and the CS achieved by a sample of Spanish firms with more than 50 employees that expressed interest in the CE, eco-design, eco-innovation and other environmental issues. Findings Based on an analysis using the dynamic capabilities theoretical approach, the results suggest a positive relationship between the CS of firms, their environmental accounting practices and their level of corporate social responsibility (CSR) and accountability. Stakeholders’ pressure – which has a mediating effect on the CS of firms – is also analyzed, adding new insights to recent studies of this topic at the micro-level. The authors also explore whether the CS of businesses, which is related to the degree of their development of capabilities, influences environmental and financial performance. Practical implications The new insights obtained in this study can help overcome the limitations of conventional accounting approaches and incorporates a much broader scale of environmental information that can be applied to CE practices. These results also offer insights to practitioners regarding the internal measurement processes related to the CE and regarding CSR in particular for small and medium enterprises, because these metrics can be partially applied depending on the practices introduced in each firm. For policymakers, a better understanding of the CE’s introduction into businesses will contribute to the design of policies that can enhance its deployment, for example, by providing tools that set up regional priorities depending on the CE-related practices adopted by the firms located in the territory. Social implications A CE involves the transformation of a linear economic model into a circular one to reduce dependence on raw materials and energy and to reduce the environmental impact of production and consumption. Understanding how to manage the specific competences that integrate capabilities applied to the CE will allow firms to improve their social and environmental reporting. In addition, other social implications of this study relate to improving relationships with consumers and stakeholders and to the practice of social corporate sustainability. Originality/value This study goes beyond previous research on the CE to extend the authors’ knowledge about its adoption at the micro-level by taking a transversal approach, as its subject spans the fields of environmental accounting and the CE while addressing both in a framework of analysis. The analysis of the accounting concerns of the CE in businesses and the study of concerns related to endogenous environmental competences are quite original under the theoretical framework of dynamic capabilities, and this study is a first step in an incipient line of inquiry.

“Quality is never an accident. It is always the result of an intelligent effort” - John Ruskin It is our pleasure to publish the inaugural issue of the Journal of Global Hospitality and Tourism (JGHT). This new journal aims to provide an intellectual platform and ideas for international scholars, by promoting studies related to global hospitality and tourism. Editorial policy of JGHT focuses on publishing original research articles, review papers and communications that identify, explain, analyze, and review real-world business phenomena/issues. Our vision is to make JGHT as one of the most innovative, proactive, and creative journals in our field and to establish itself as one of the leading academic journals in hospitality and tourism. To accomplish this vision, we have appointed international established scholars as well as many upcoming talented researchers to JGHT's editorial advisory board (EVB) and editorial review board (ERB). We are also proud to announce that we have a very good representation of individuals (in terms of geographical locations, gender, and academic position) on our EAB and ERB. We are also proud to announce that JGHT is a true open access journal which means that it is free to jats:submit, publish, and/or access the content in the journal. It is made possible with the generous support from M3 Center for Innovation in Hospitality and Tourism and the University of South Florida Library. While JGHT is an academic journal and focuses on research work conducted by academics working in higher education institutes; contributions to JGHT are particularly welcome from practitioners and professionals working in private, public, and non-profit organizations globally. JGHT welcomes theoretical, empirical, and applied manuscripts related to various sectors within the global hospitality and tourism industry to be considered for publication. Manuscripts can be based on theoretical arguments, empirical findings, case studies and/or methodological developments. Qualitative, quantitative, and mixed-methodology jats:submissions are all welcome. The first issue of JGHT includes five interesting and solid research articles and two viewpoints. The first article by Yuehan Cao, Jiyeon Jeon, Liang (Rebecca) Tang, and Xi Wang replicates an earlier study that analyzed hospitality and tourism research contributions in the first decade of the new millennium (Park et al., 2011) using a time frame of 2010-2019. Their study reviewed six top-tier hospitality and tourism journals, including the International Journal of Hospitality Management, Journal of Hospitality & Tourism Research, Cornell Hospitality Quarterly, Tourism Management, Journal of Travel Research, and Annals of Tourism Research. The papers were classified by research themes in the hospitality and tourism categories, respectively. The results offered the rankings by publication productivity pertaining to individual authors, universities, and countries/regions across the world. The findings give insights into future directions and identify research needs for academicians and industry practitioners in the hospitality and tourism field. The second article by Foad Irani and Hasan Kilic from Eastern Mediterranean University explores how to enhance hotels' environmental performance by adopting green human resource management practices. Their study developed and investigated a moderation model which examined the green process innovation as a moderator onto the relationship between green human resource management and environmental process through the lens of Ability-Motivation-Opportunity theory. They collected data from 220 full-time employees of 3, 4, and 5-stars green hotels in Turkey. The findings demonstrated the importance of adopting green practices in advancing organizational performance, especially the environmental aspect. The novel findings of this study enrich the moderation effect of green process innovation in hospitality literature. The third study is conducted by Jaewook Kim, Liang (Rebecca) Tang, Xi Wang, and Linan Zhang. This study aimed to examine the relationship among entrepreneurship capital, perceived feasibility, perceived desirability, and entrepreneurial intention in sharing lodging by using the entrepreneurial event model. Particularly, entrepreneurship capital was evaluated as a second-order factor with four first-order jats:sub-variables: financial, social, intellectual, and human capital. Data were collected from online surveys completed by 328 respondents. Second-order factor analysis and structural equation modeling were used in the analysis. Results confirmed that all four jats:sub-variables contributed to inclusive capital. Inclusive capital positively influenced perceived feasibility and perceived desirability, which led to entrepreneurial intention. This study contributes to the evolving knowledge of sharing accommodations and enriches the research body of entrepreneurship via examining hosts of sharing lodging as innovative micro-entrepreneurs. It offers practical tools to help prospective hosts assess whether they are ready to operate a sharing lodging business. The fourth study in this inaugural issue is conducted by Jessica Wiitala and Trishna Mistry. The purpose of this study was to analyze the relationships between hospitality organizations' crisis response during the COVID-19 pandemic with hospitality employees' attitudes and behaviors. Data was collected using a survey distributed on Amazon Mechanical Turk targeting hospitality industry employees. The findings reveal that crisis response is related to psychological well-being, job satisfaction, and organizational commitment among hospitality industry employees. This study broadens the scope of crisis management literature in the hospitality field. Furthermore, it establishes the significance of effective crisis response for hospitality industry employees' well-being and positive outcomes. The last article presents a study conducted by Tammy Wee and Melissa L. S. Liow. This article aims to establish the motivation factors behind the accommodation choices made by millennials for stays at short-term rental properties and small hotels amidst the COVID-19 pandemic, a topic that remains under-represented in the hospitality and tourism literature. Using data from a survey of 145 millennials who stayed at an Airbnb property and a small hotel, a non-parametric test was utilized to compare six motivation factors that affect millennials' accommodation choices, guided by the push-pull motivational framework. The results showed that the millennials significantly considered price and reviews as their common pull motivations when making accommodation choices. Interestingly, motivation factors such as location, service quality, facilities and amenities, safety, and security do not appear to significantly influence the millennials' choices for either accommodation. This paper contributes to the limited pool of empirical research on short-term rental properties and addresses the challenges faced by the small hotel industry by focusing on millennials' accommodation choices. In addition to these five research papers, this issue of JGHT also two viewpoints. The first viewpoint is an academic one and is written by Prof. Mark S. Rosenbaum and Germán C. Ramírez. Their viewpoint suggests that foundational theories and concepts which characterize the services marketing discipline may no longer be valid due to the global pandemic. The authors discuss the impact of the Great Resignation on both consumers and organizations and posit that many consumers now accept lower levels of service offerings and performance. They further question whether organizations will ever return to pre-pandemic service levels. Further, the authors contend that the discipline's focus on employee-customer relationships has now shifted to customer-technology exchanges and that human interactions, in many service exchanges, are diminishing in importance. The authors put forward future research questions. The second viewpoint is industry-based viewpoint and is contributed by Nancy Hutson from Full Stop Productions Inc., in Tampa, Florida USA. This viewpoint focuses on the event planning industry and takes a notion that while tourism and hospitality continue to show signs of rebounding, new, innovative strategies in event planning are needed more than ever. We would like to congratulate all the authors on the successful completion of their research endeavors. We would also like to thank to all our reviewers for their insightful and constructive comments that assisted the authors to improve the quality of the papers. We hope that our readers will find all the papers published in this issue timely, relevant, and insightful. Finally, we want to thank our readers, authors, reviewers, EAB members, editorial team, and colleagues from M3 Center for Hospitality Technology and Innovation, University of South Florida, and Prof. Cihan Cobanoglu for their support and contribution to this first issue of JGHT as well as creating a platform and opportunity to launch JGHT.

ABSTRAK Pandemi COVID-19 menyebabkan pertumbuhan ekonomi global melambat. Pertumbuhan ekonomi yang dikuru melalui GDP suatu negara dipengaruhi oleh beberapa hal. OIC merupakan organisasi negara-negara muslim didunia dimana GDP mereka juga juga terdampak secara signifikan akibat pandemi COVID-19. Penelitian ini bertujuan untuk mengobservasi pertumbuhan ekonomi negara anggota OKI yang dipengaruhi oleh variabel Industri manufaktur, Penanaman Modal Asing, dan Total konsumsi yang di moderasi oleh tenaga kerja. Penelitian ini menggunakan jenis data panel. Data diambil dengan menggunakan metode purposive sampling. Penelitian ini menggunakan sampel 10 negara aggota OKI dalam rentan tahun 2018-2020. Studi ini menggunakan teknik Random Effect Model (REM) untuk melihat pengaruh hubungan variabel independen terhadap variabel dependen secara simultan maupun parsial. Hasil menunjukkan bahwa beberapa variable independen seperti total konsumsi dan Penanaman Modal Asing mampu memberikan pengaruh signifikan untuk pertumbuhan ekonomi tanpa harus dimoderasi oleh Tenaga Kerja. Sedangkan industri manufaktur ketika dimoderasi oleh tenaga kerja, justru memberikan pengaruh yang relevan kepada pertumbuhan ekonomi di beberapa negara anggota OKI saat masa pandemi Covid-19. Maka, saran kepada pemangku kepentingan diharapkan memberikan perhatian khusus terhadap sektor industri manufaktur yang sangat banyak menyerap tenaga kerja. Untuk penelitian selanjutnya, diharapkan mampu menambah jumlah sampel data jika topik yang diambil sama dengan penelitian ini karena sampel data terbatas hanya pada negara OKI dalam penelitian ini. Kata kunci: Covid-19, Pertumbuhan Ekonomi, Penanaman Modal Asing, Tenaga Kerja, OKI. ABSTRACT The COVID-19 pandemic has caused global economic growth to slow down. Economic growth measured through a country's GDP is influenced by several things. OIC is an organization of Muslim countries in the world where their GDP has also been significantly affected by the COVID-19 pandemic. This study aimed to observe the economic growth of OIC member countries which is influenced by the variables of the manufacturing industry, foreign investment, and total consumption which are moderated by labor. This research used panel data type. Data were taken using purposive sampling method. This study used a sample of 10 OIC member countries in the 2018-2020 vulnerable years. This study uses the Random Effect Model (REM) technique to see the effect of the relationship of the independent variable on the dependent variable simultaneously or partially. The results showed that several independent variables such as total consumption and foreign investment are able to have a significant influence on economic growth without having to be moderated by the labour force. Meanwhile, the manufacturing industry, when moderated by the labour force, actually has a relevant influence on economic growth in several OIC member countries during the Covid-19 pandemic. Therefore, suggestions to stakeholders are expected to pay special attention to the manufacturing industry sector which absorbs a lot of workers. For further research, it is expected to be able to increase the number of data samples if the topic taken is similar to this recent study because the data sample in this study is limited to only the OIC countries. Keywords: Covid-19, Economics Growth, Foreign Direct Investment, Labor Force, OIC. REFERENCES Almosabbeh, I. A., & Almoree, M. A. (2018). The relationship between manufacturing production and economic growth in the kingdom of Saudi Arabia. Journal of Economic Studies, 45(4), 674–690. https://doi.org/10.1108/JES-02-2017-0029 Anto, M., H. (2013). Introducing an Islamic human development index (i-hdi) to measure development in oic countries. Islamic Economic Studies, Vol. 19 No.2, Life 1, 69–95. Apriyono, A., & Taman, A. (2013). Analisis overreaction pada harga saham perusahaan manufaktur di bursa efek Indonesia. Jurnal Nomina, 2(2), 76–96. https://doi.org/10.29264/jmmn.v9i1.2473 Apurv, R., & Uzma, S. H. (2021). The impact of infrastructure investment and development on economic growth on BRICS. Indian Growth and Development Review, 14(1), 122–147. https://doi.org/10.1108/IGDR-01-2020-0007 As’ari, R. (2018). Pengetahuan dan sikap masyarakat dalam melestarikan lingkungan hubungannya dengan perilaku menjaga kelestarian kawasan bukit sepuluh ribu di kota Tasikmalaya. Jurnal GeoEco, 4(1), 9–18. Auzina-Emsina, A. (2014). Labour productivity, economic growth and global competitiveness in post-crisis period. Procedia - Social and Behavioral Sciences, 156(April), 317–321. https://doi.org/10.1016/j.sbspro.2014.11.195 Barkah, T., Rusgianto, S., & Wardhana, A. (2022). Impact of agricultural land and the output of agricultural products moderated with internet users toward the total export of agricultural product in three Islamic Southeast Asian countries. Media Agribisnis, 6(1 SE - Articles). https://doi.org/10.35326/agribisnis.v6i1.2261 Boukhatem, J., & Ben Moussa, F. (2018). The effect of Islamic banks on GDP growth: some evidence from selected MENA countries. Borsa Istanbul Review, 18(3), 231–247. https://doi.org/10.1016/j.bir.2017.11.004 Cahyadin, M., & Prastity, N. (2015). The effect of foreign direct investment on economic growth in organization of Islamic conference (OIC) member countries in 2000-2013. Kajian, 20(3), 255–270. Chasanah, N., & Rusmita, S. A. (2019). Pengaruh profitabilitas terhadap harga saham dengan corporate responbility sebagai variabel moderasi (perusahaan yang terdaftar di JII dan indeks sri-kehati periode 2016-2018). Jurnal Ekonomi Syariah Teori Dan Terapan, 6(11), 2331–2346. https://doi.org/10.20473/vol6iss202011pp2331-2346 Choiriyah, E. A. N., & Auwalin, I. (2020). Pengaruh harga komoditas, kurs, inflasi, foreign direct investment (FDI), dan sumber daya manusia (SDM) terhadap perekonomian negara oki. Jurnal Ekonomi Syariah Teori Dan Terapan, 7(8), 1607-1628. https://doi.org/10.20473/vol7iss20208pp1607-1628 Cotula, L. (2021). Towards a political economy of the covid-19 crisis: Reflections on an agenda for research and action. World Development, 138, 105235. Denziana, A., Indrayenti, & Fatah, F. (2014). Corporate financial performance effects of macroeconomic factors against stock return. Akuntansi & Keuangan, 5(2), 17–40. Fadhil, M. A., & Almsafir, M. K. (2015). The Role of FDI Inflows in Economic Growth in Malaysia (Time Series: 1975-2010). Procedia Economics and Finance, 23(October 2014), 1558–1566. https://doi.org/10.1016/s2212-5671(15)00498-0 Fauziana, H., Wardhana, A. K., & Rusgianto, S. (2022). The effect of education, income, unemployment, and poverty toward the Gini ratio in member of OIC countries. Daengku: Journal of Humanities and Social Sciences Innovation, 2(2), 181–191. Febriyanti, A. R., & Shofawati, A. (2020). Pengaruh variabel internal bank dan variabel makroekonomi terhadap kinerja keuangan (studi bank umum syariah di indonesia periode 2014-2018). Jurnal Ekonomi Syariah Teori Dan Terapan, 7(8), 1538. https://doi.org/10.20473/vol7iss20208pp1538-1551 Firano, Z., & Fatine, F. A. (2020). The covid-19: Macroeconomics scenario and role of containment in Morocco. one health, 10 (July), 100152. https://doi.org/10.1016/j.onehlt.2020.100152 Ghifara, A. S., Iman, A. N., Wardhana, A. K., Rusgianto, S., & Ratnasari, R. T. (2022). The effect of economic growth, government spending, and human development index toward inequality of income distribution in the metropolitan cities in Indonesia. Daengku: Journal of Humanities and Social Sciences Innovation, 2(4), 529–536. Handriyani, R., Arwansyah, & Sahyar. (2018). Analysis effect of household consumption, investment and labor to economy growth in Sumatera Utara. Proceedings of the 3rd Annual International Seminar on Transformative Education and Educational Leadership (AISTEEL), 209–212. Hartono, D., Yusuf, A. A., Hastuti, S. H., Saputri, N. K., & Syaifudin, N. (2021). Effect of covid-19 on energy consumption and carbon dioxide emissions in Indonesia. Sustainable Production and Consumption, 28, 391–404. https://doi.org/10.1016/j.spc.2021.06.003 Hutagaol, D. T., Tarmizi, H. B., & Daulay, M. (2019). An analysis on the influence of population growth rate, economic growth, human development index, income distribution, and unemployment rate toward poverty in all provinces in Indonesia. International Journal of Research & Review, 6(1), 101–108. Iamsiraroj, S. (2016). The foreign direct investment-economic growth nexus. International Review of Economics and Finance, 42, 116–133. https://doi.org/10.1016/j.iref.2015.10.044 Juhro, S. M., & Iyke, B. N. (2019). Consumer confidence and consumption expenditure in Indonesia. Economic Modelling, 89(2020), 367–377. https://doi.org/10.1016/j.econmod.2019.11.001 Kuvvet, E. (2021). anti-corruption courts and foreign direct investments. International Review of Economics and Finance, 72(July 2020), 573–582. https://doi.org/10.1016/j.iref.2020.12.019 Liana, L. (2009). Penggunaan MRA dengan SPSS untuk menguji pengaruh variabel moderating terhadap hubungan antara variabel independen dan variabel dependen. Jurnal Teknologi Informasi DINAMIK, 14(2), 90–97. Liu, D., Xu, C., Yu, Y., Rong, K., & Zhang, J. (2020). economic growth target, distortion of public expenditure and business cycle in china. China Economic Review, 63(October 2019), 101373. https://doi.org/10.1016/j.chieco.2019.101373 Marelli, E., & Pastore, F. (2010). Labour, productivity and growth: an introductory essay. International Journal of Manpower, 31(7), 701–712. https://doi.org/10.1108/01437721011081554 Martanti, D. M., Magdalena, F., Ariska, N. P. D., Setiyawati, N., & Rumboirusi, W. C. B. (n.d.). Dampak pandemi covid-19 terhadap tenaga kerja formal di indonesia. Populasi, 28(2), 52–69. Maryati, S., Handra, H., & Muslim, I. (2021). Penyerapan tenaga kerja dan pertumbuhan ekonomi menuju era bonus demografi di sumatra barat labor absorption and economic growth towards the demographic bonus era in West Sumatra. Jurnal Ekonomi Dan Pembangunan Indonesia, 21(1), 95–107. Meilaniwati, H., & Tannia, T. (2021). Analisis pengaruh penanaman modal asing (PMA), penanaman modal dalam negeri (PMDN), trade openness (TO) dan inflasi terhadap pertumbuhan ekonomi di ASEAN-5 tahun 2009-2018. Business Management Journal, 17(1), 89–100. https://doi.org/10.30813/bmj.v17i1.2582 Pratiwi, A. C., Wardhana, A. K., & Rusgianto, S. (2022). Application of vector error correction model on macroeconomic variables toward changes in the composite stock price index. Daengku: Journal of Humanities and Social Sciences Innovation, 2(2), 219–229. Rahman, I., Ratnasari, R. T., & Wardhana, A. K. (2022). Effect of certificate of bank Indonesia sharia and Indonesian bank seven days repository rate to inflation ratio in Indonesia during covid-19 pandemic. Economic Education and Entrepreneurship Journal, 5(1), 157–174. Rashid, N. K. A., Sulaiman, N. F. C., Anang, Z., Possumah, B. T., Muhamad, S., Sa’at, N. H., Hasan, F. A., & Wahid, H. (2021). Survey dataset on the level of sustainable consumption of Malaysian households from the perspective of income and consumption expenditure. Data in Brief, 35, 106743. https://doi.org/10.1016/j.dib.2021.106743 Ridzuan, A. R., Khalid, M. W., Zarin, N. I., Ridzuan, A. R., Ismail, I., & Norizan, N. (2018). The impact of foreign direct investment, domestic investment, trade openness and population on economic growth: evidence from asean-5 countries. International Journal of Academic Research in Business and Social Sciences, 8(1), 128–143. https://doi.org/10.6007/ijarbss/v8-i1/3799 Setiawati. (2021). Analisis pengaruh kebijakan deviden terhadap nilai perusahaan pada perusahaan farmasi di BEI. Jurnal Inovasi Penelitian, 1(8), 1581–1590. Tesfay, Y. Y. (2016). Modified,l panel data regression model and its applications to the airline industry: modeling the load factor of europe north and europe mid atlantic flights. Journal of Traffic and Transportation Engineering (English Edition), 3(4), 283–295. https://doi.org/10.1016/j.jtte.2016.01.006 Usmadi. (2020). Pengujian persyaratan analisis (uji homogenitas dan uji normalitas). Inovasi Pendidikan, 7(1), 50–62. Wardhana, A. K. (2021a). the application of waqf and endowment fund based on the principles in the sharia maqashid pillar society. Prosperity: Journal of Society and Empowerment, 1(2), 107–119. https://doi.org/10.21580/prosperity.2021.1.2.8829 Wardhana, A. K. (2021b). the impact of the pro and cons policies in the jokowi era’s on the macro economy of society. Jurnal Ekonomi Dan Bisnis Airlangga, 31(2), 124–136. https://doi.org/https://doi.org/10.20473/jeba.V31I22021.124-136 Yıldırım, D. Ç., & Akinci, H. (2020). the dynamic relationships between the female labour force and economic growth. Journal of Economic Studies, 1970. https://doi.org/10.1108/JES-05-2020-0227 Zeytoonnejad Mousavian, S. R., Mirdamadi, S. M., Farajallah Hosseini, S. J., & Omidi NajafAbadi, M. (2021). determinants of foreign direct investment inflow to the agricultural sector: a panel-data analysis. Journal of Economic and Administrative Sciences, (ahead-of-print). https://doi.org/10.1108/jeas-11-2020-0196

The emergence of powerful information technologies (IT) has changed innovation and entrepreneurship in significant ways. Research in IT for entrepreneurship is relatively new and there is a growing interest from academics for further studies on investigating this area of research. This study reviews research carried out in the domain of IT for entrepreneurship. A total of 1005 papers, published between 1980 and 2021 were used to uncover the latent topics addressed in this domain. A topic modeling (LDA) algorithm was used to automate the process of extracting the initial research topics from the data. The results show that IT for entrepreneurship studies are classified into six aspects of research: entrepreneurship initiative and innovation, strategy, business process management and operation management, entrepreneurship education, industry analysis, and business model. The results raise awareness of IT-associated entrepreneurship areas of research, provide useful insights for future research, and informs practice in this domain of study.

Purpose The outbreak of COVID-19 is one of the most serious health events in recent times. In the business landscape, its effects may be more detrimental to micro-, small- and medium-sized enterprises (MSMEs) because they tend to have limited financial and human resources to manage the challenges caused by COVID-19. To help MSMEs enhance their resilience, this paper aims to discuss how they can leverage mass collaboration to build social media-based knowledge ecosystems to manage interactions among internal and external stakeholders for knowledge creation and innovation. Design/methodology/approach The paper proposes a model for MSMEs to build an online knowledge ecosystem and a standalone text analytics tool to use the advanced data analytics, e.g. topic modeling, to analyze and aggregate collective insights. Design science research methodology is used to develop the model and the tool. Findings Through mass collaboration using social media and advanced data analytics technology, MSMEs can generate new business ideas, leading to enhanced resilience to meet the challenges caused by COVID-19 or other unexpected or extraordinary circumstances, such as natural disasters and financial crises. Originality/value To the best of authors’ knowledge, this paper is one of the first papers in social media adoption for knowledge creation and innovation research, providing detailed approaches for MSMEs to build a knowledge ecosystem on social media and to use advanced data analytics to mine the meaning of the generated data.

Purpose Knowledge management has historically been approached in private firms as a key factor for business management. However, this is not the case for government institutions. The existing literature on the transfer of knowledge appears as a topic little addressed in government and even to a lesser degree within the police forces. This study aims to evaluate the relationship between motivation, knowledge absorption, knowledge transfer and innovative behavior in a public organization such as the Puerto Rico Police. Design/methodology/approach This quantitative research using the survey technique had the participation of 300 police officers from the 13 police regions of Puerto Rico and the research model was analyzed through partial least squares structural equation modeling. Findings The results contribute to the growth of the currently limited literature at identifies how motivation, knowledge absorption, knowledge transfer and institutional support influence innovative behavior. Originality/value The study discusses a series of implications on less explore the issue in how the transfer of knowledge becomes a key force to produce change and the success of all reforms. Various implications for the success of public administration in bringing a change from a bureaucratic culture to an advanced one are also discussed.

Purpose A lesson has been learned from the pandemic experience that less damages to the environment and realizing more social responsibilities would be the direction of the post-pandemic period globally. The purpose of this study is to focus on identifying the appropriate determinants of the proposed urban travel behavior model to develop Smart Mobility in Smart Cities to protect the environment. Potential to realize Smart Cities with infrastructure development has been explored in this study if road users are keen to combat climatic change which is clear from the challenges of flattening the infection rate through the enforcement of rules and regulations by the various government. Design/methodology/approach The proposed urban travel behavior model includes sub-drivers for each of the main drivers in the theory of interpersonal behavior (TIB). These sub-drivers emphasize in forming intentions to perform the behavioral changes while driving on urban roads during COVID-19 and post-pandemic periods. A primary online survey was conducted among road commuters in the most crowded place in Malaysia, the Greater Kuala Lumpur. A total of 383 respondents who frequently drive on road during the past one year were surveyed for this study. This data analysis of this quantitative study applied a partial least squares-structural equation modeling approach to determine the significant findings and results. Findings The significant findings of the study reveal that environmental consciousness and timely deviation in driving during traffic congestion are positively and significantly influencing the travel behavior performance (TBP) of commuters on urban roads. On the other hand, wet conditions due to weather, narrow road infrastructure and habits of road commuters are negatively influencing TBP. Social responsibility is positively and significantly influencing TBP through the mediating effect of the intention of road commuters’ behavior. Research limitations/implications The current environmental concerns and societal adherence efforts in breaking the chain of the infectious COVID-19 among people can be manifested to develop Smart Cities with less air and noise pollution in the future. In this context, the present study proposes an urban travel behavior model and tests for its suitability of a greener and cleaner environment for the benefit of future generations. The limitation of the present study is that travel hazards are not included in the framework, as it is a topic of its own volume. Originality/value It is timely to implement Smart Mobility on road business models for Smart Cities as the consequences of the pandemic make us to realize the importance of environmental concerns and the social responsibilities of everyone. TIB considers four drivers, namely, attitude, subjective norm, affect and habit which induce intention to perform behavioral decisions. The novelty of the present study is the development of sub-drivers for these four drivers in the context of the urban travel behavior model.

Purpose The purpose of this study was to demonstrate a cloud business intelligence model for industrial SMEs. An initial model was developed to accomplish this, followed by validation and finalization of the cloud business intelligence model. Additionally, this research employs a mixed-techniques approach, including both qualitative and quantitative methods. This paper aims to achieve the following objectives: (1) Recognize the Cloud business intelligence concepts. (2) Identify the role of cloud BI in SMEs. (3) Identify the factors that affect the design and presenting a Cloud business intelligence model based on critical factors affecting SMEs during pandemic COVID-19. (4) Discuss the importance of Cloud BI in pandemic COVID-19 for SMEs. (5) Provide managerial implications for using Cloud BI effectively in Iran’s SMEs. Design/methodology/approach In the current study, an initial model was first proposed, and the cloud business intelligence model was then validated and finalized. Moreover, this study uses a mixed-methods design in which both qualitative and quantitative methods are used. The fuzzy Delphi Method has been applied for parameter validation purposes, and eventually, the Cloud business intelligence model has been presented through exploiting the interpretive structural modeling. The partial least squares method was also applied to validate the model. Data were also analyzed using the MAXQDA and Smart PLS software package. Findings In this research, from the elimination of synonym and frequently repeated factors and classification of final factors, six main factors, 24 subfactors and 24 identifiers were discovered from the texts of the relevant papers and interviews conducted with 19 experts in the area of BI and Cloud computing. The main factors of our research include drivers, enablers, competencies, critical success factors, SME characteristics and adoption. The subfactors of included competitors pressure, decision-making time, data access, data analysis and calculations, budget, clear view, clear missions, BI tools, data infrastructure, information merging, business key sector, data owner, business process, data resource, data quality, IT skill, organizational preparedness, innovation orientation, SME characteristics, SME activity, SME structure, BI maturity, standardization, agility, balances between BI systems and business strategies. Then, the quantitative part continued with the fuzzy Delphi technique in which two factors, decision-making time and agility, were deleted in the first round, and the second round was conducted for the rest of the factors. In that step, 24 factors were assessed based on the opinions of 19 experts. In the second round, none of the factors were removed, and thus the Delphi analysis was concluded. Next, data analysis was carried out by building the structural self-interaction matrix to present the model. According to the results, adoptability is a first-level or dependent variable. Regarding the results of interpretive structural modeling (ISM), the variable of critical success factors is a second-level variable. Enablers, competencies and SME characteristics are the third-level and most effective variables of the model. Accordingly, the initial model of Cloud BI for SMEs is presented as follows: The results of ISM revealed the impact of SME characteristics on BI critical success factors and adoptability. Since this category was not an underlying category of BI; thus, it played the role of a moderating variable for the impact of critical success factors on adoptability in the final model. Research limitations/implications Since this study is limited to about 100 SMEs in the north of Iran, results should be applied cautiously to SMEs in other countries. Generalizing the study's results to other industries and geographic regions should be done with care since management perceptions, and financial condition of a business vary significantly. Additionally, the topic of business intelligence in SMEs constrained the sample from the start since not all SMEs use business intelligence systems, and others are unaware of their advantages. BI tools enable the effective management of companies of all sizes by providing analytic data and critical performance indicators. In general, SMEs used fewer business intelligence technologies than big companies. According to studies, SMEs understand the value of simplifying their information resources to make critical business choices. Additionally, they are aware of the market's abundance of business intelligence products. However, many SMEs lack the technical knowledge necessary to choose the optimal tool combination. In light of the frequently significant investment required to implement BI approaches, a viable alternative for SMEs may be to adopt cloud computing solutions that enable organizations to strengthen their systems and information technologies on a pay-per-use basis while also providing access to cutting-edge BI technologies at a reasonable price. Practical implications Before the implementation of Cloud BI in SMEs, condition of driver, competency and critical success factor of SMEs should also be considered. These will help to define the significant resources and skills that form the strategic edge and lead to the success of Cloud BI projects. Originality/value Most of the previous studies have been focused on factors such as critical success factors in cloud business intelligence and cloud computing in small and medium-sized enterprises, cloud business intelligence adoption models, the services used in cloud business intelligence, the factors involved in acceptance of cloud business intelligence, the challenges and advantages of cloud business intelligence, and drivers and barriers to cloud business intelligence. None of the studied resources proposed any comprehensive model for designing and implementing cloud business intelligence in small and medium-sized enterprises; they only investigated some of the aspects of this issue.

Purpose This study aims to propose an integrated model based on the DeLone and McLean Information System Success Model (DMISS) to examine whether quality factors (system, service and information) can affect user satisfaction and performance of cloud-based marketing systems. Design/methodology/approach Recently, technologies change quickly, innovation becomes a vital base of productivity and sustainable growth of businesses is widely accepted. Cyber-physical system technologies help industries change production and marketing cycles according to customers’ needs in real-time. In addition, processing information through cloud service helps companies meet customer needs. The advantages of cloud technology also make it easier for companies to quickly collect the latest data from various sources, making it more effective in decision-making. This research recommends cloud-based marketing to help companies maximize their revenue by providing useful information and better quality for business development. The data were gathered from China automotive companies’ customers. A total of 220 questionnaires were distributed, and 165 (82.5%) usable questionnaires were analyzed using structural equation modeling. Findings This study verified that costumers’ perceived information quality, system quality and service quality positively caused the user satisfaction in the cloud-based marketing system. Practical implications This paper presents beneficial advice for improving cloud-based marketing systems. Besides, the topic is relevant to cloud-based marketing systems’ success. A better understanding of the impact of intention to use and user satisfaction on cloud-based marketing systems could significantly enhance companies’ success. This paper’s theoretical and practical contributions are expressed to guide organizations and policymakers in increasing cloud-based marketing systems acceptance. Originality/value This study empirically tests the relationship of quality factors and performance outcome of cloud-based marketing system through a model based on DeLone and McLean theory. This study bridges the research gap by identifying the factors that drive the adoption of cloud-based services in marketing and the impact of user satisfaction and intention to use on the cloud-based marketing system performance in the case of china companies.

PurposeSuccessful stimulation of employee engagement in pro-environmental behavior (PEB) at work can reduce organizational environmental footprint and boost its green performance. The aim of this paper is to investigate the individual factors that may promote such behavior at work, offering a complex model with mediating relationships not studied before.Design/methodology/approachIn this paper data was collected through a survey of 331 bank employees from different banks in Kazakhstan and Ecuador. Structural equation modeling was used to test the relationships between the different constructs.FindingsThe results identified that environmental values and attitudes mediate the relationship between (1) personal environmental awareness and (2) environmental concern and employees' voluntary PEB at work. Harmonious environmental passion (HEP) mediates the relationship between environmental values and attitudes and employees' voluntary PEB at work.Practical implicationsThis study presents important organizational policymaking implications with regard to organizational greening. The importance of environmental awareness is underlined, guiding managers to offer environmental education and training to the employees with the aim of improving environmental knowledge that may lead to employees' voluntary PEB at work. Also, managers should work on enhancing HEP.Originality/valuePrior literature on this topic is still scarce. This research presents important contributions by discussing how individual antecedents may act as stimuli of employees' voluntary PEB at work in the context of the banking sector in two emerging countries that are often neglected by prior literature.