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Despite the wide research and discussion on international performance, innovation and digital resilience dimensions of enterprises, the investigation and understanding of their interrelations seem to be limited. The purpose of this study is to identify the influential factors affecting the mentioned dimensions, determine the causal relationships among these identified factors and finally evaluate their importance in an aggregated framework from the viewpoint of small and medium-sized enterprises (SMEs).

A hybrid methodology is used to achieve the objectives. First, the main factors of international performance, innovation and digital resilience are extracted by an in-depth review of the literature. These factors are then screened by expert opinions to localize them in accordance with the conditions of an emerging economy. Finally, the relationship and the importance of the factors are determined using an uncertain multi-criteria decision-making (MCDM) approach.

The findings reveal that there is a correlation between digital resilience and innovation, and both factors have an impact on the international performance of SMEs. The cause-or-effect nature of the factors belonging to each dimension is also determined. Among the effect factors, business model innovation (BMI), agility, product and organizational innovation are known as the most important factors. International knowledge, personal drivers and digital transformation are also determined to be the most important cause factors.

This study extends the literature both in methodological and practical directions. Practically, the study aggregates the factors in the mentioned dimensions and provides insights into their cause-and-effect interrelations. Methodologically, the study proposes an uncertain MCDM approach that has been rarely used in previous studies in this field.

Operational excellence (OpEx) is a direction toward learning and developing an excellent culture in all aspects of an organization. To reach this culture, revolutionizing activities using industry 4.0 (i4.0) technologies might be a significant empowering tool. This study aims to identify the challenges and benefits of both concepts and investigate their interrelationship to be considered in applying industry 4.0 technologies toward operational excellence.

The challenges and benefits of OpEx and i4.0 are identified and finalized by reviewing the literature. The causal relations between the considered factors are extracted using the fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) method. Then, the analytical network process (ANP) is applied to determine the importance and weight of the factors (challenges and benefits of OpEx and i4.0) according to the constructed network.

The findings illustrated a strong network structure between the factors. First, the causal factors included OpEx and i4.0 challenges, while the OpEx challenges also affected the i4.0 challenges. Both group challenges had a significant effect on OpEx and i4.0 benefits. This means that challenges are the causal factors to be considered in the alignment of i4.0 toward OpEx. Among the OpEx challenges, lack of strategic planning and proper infrastructure were the main influential factors. In contrast, lack of government support and undeveloped business models were identified as the main challenges of i4.0.

OpEx and i4.0 concepts are reviewed and their pros and cons are studied. Previous studies determined an interaction among these concepts. However, from a practical viewpoint, the relation between the challenges and benefits of i4.0 and OpEx was studied for the first time for their alignment.

International collaboration is a crucial requirement of entrepreneurship, particularly in developing emerging economies. This collaboration seems so necessary in the food industry as a major contributor to environmental, social and economic problems. This paper aims to identify, analyse the influential network relationship and prioritise the key success factors (KSFs) of international collaboration formation in the entrepreneurial food industry with a case study on Iran's emerging economy.

To identify a list of KSFs, a qualitative method, literature review, is initially used. A quantitative method, fuzzy-Delphi, then is employed to finalise the main KSFs based on the entrepreneurial food industry experts' opinion. To analyse the causal relationship, and prioritise the KSFs, a fuzzy decision-making trial and evaluation laboratory (DEMATEL)-analytic network process (ANP) methodology, i.e. FDANP, is applied. At the first stage, the cause–effect diagram of KSFs is extracted using fuzzy DEMATEL and then, the KSFs weights and priorities are evaluated using a fuzzy ANP.

The results illustrate that the characteristics of effective development workers are the leading dimension of a successful international collaboration that directly affects other dimensions. On the other hand, increased marketing and trading is the most important KSF that is directly related to international entrepreneurial collaboration team capabilities and professionalism. The leading and casual role of team members also plays a vital role in strategic and communication issues affecting the collaboration success, e.g. market research and new product development. Availability of financial resources and the ability of partners in continuous financing is also a crucial and required factor for a successful collaboration.

Using an extensive review of the literature to extract the KSFs of international entrepreneurial collaboration and finalising them using a fuzzy-Delphi method and examining the cause-effect relations between them, as well as prioritising the KSFs are the main contributions of this paper.

Taking a mixed-method approach, this research developed and validated a novel, value-centric experience framework delineating robotic involvement in the service encounter and its subsequent impact on customers' experiences.

Focused on robotic restaurant businesses where robots are mainly involved in food production processes, this research utilized online customer review data and a multistage, mixed-method design for empirical examination. Automated thematic analysis was first adopted to facilitate a comprehensive understanding of the empirical reality as reflected in online customer reviews. Following an analytic induction process, a theoretical framework was developed integrating prior literature with the empirical reality to uncover the relationships across robotic involvement, experiential values and evaluative outcomes. A theory-driven, dictionary-based content analysis together with path analysis further enabled empirical validation of the developed theoretical framework.

The current research developed and validated a value-centric experience framework to theorize robotic involvement in the service encounter and its downstream impact on customers' experiences. Specifically, this framework conceptualizes robotic involvement as a five-dimensional composition of robotic visibility, competency, performanism, co-creativity and prominence. In addition, the framework specifies seven dimensions of experiential values revolving around high-tech–high-touch robotic service encounters, namely sensorial, utilitarian, hedonic, social, agentic, epistemic and aesthetic values. Following empirical validation, this framework sheds light on robotic involvement and experience design for high-tech–high-touch service businesses aiming to incorporate robots in their service encounters.

Drawing on classic service role theory and consumption value theory, this research developed and validated a novel theoretical model connecting robotic involvement dimensions with experiential consumption values and downstream customer evaluative outcomes. This research and theoretical framework open an exciting avenue for future research in robotic services and customer experiences.

Pressure on business to direct their activities responsibly has been increased during the last years to extent their suitability performance in all economic, social and environmental dimensions. This has motivated businesses and researchers to identify ways to implement sustainable and resilient operations. In the era of economic globalisation, small and medium enterprises (SMEs) are recognised as an engine of sustainable economic development in both the developed and developing world. Their competitiveness drives the economy, both nationally and internationally. SMEs have faced challenges in developing, internationalisation and achieving competitive advantage. Purpose of current study is to identify and analyse the sustainability and resiliency (SR) barriers to SME internationalisation and prioritise the practices to overcome the negative influence of barriers. In this regard, first, barriers and innovative practices have been identified through the literature review. Second, the essential barriers will be selected through reduction steps by the intuitionistic fuzzy Delphi (IF-Delphi) method. After computing the weight of barriers through the IF-DEMATEL method, the practices were prioritised using four multiple attribute decision-making (MADM) methods in an IF environment. Finally, the scores were aggregated by correlation coefficient and standard deviation (CCSD) technique. Results present that ‘Lack of economical resources to global exports’ and ‘Complications in acclimatizing export product design’ are the top priority barriers and ‘Knowledge of global market opportunities’ and ‘Networking with business incubator institutions’ have been recognised as the essential SMEs internationalisation practices. This study contributes to creating a more focussed approach towards the growth of SMEs. The study results would be helpful for industry, policymakers and academia.

Despite the undoubted role of family firms in the economy, some main factors challenge their attempts for business internationalisation. These drivers are varied from organisational and environmental to individual attributes. This study tries to recognise and explore the impacts of the personality traits of managers, founders, and owners of family firms in their business internationalisation. The study used a questionnaire to collect data from a sample of 204 managers, founders, and owners of small- and medium-sized family firms to consider the relationship between personality traits: conscientiousness, openness, extroversion, neuroticism and agreeableness, and business internationalisation (BI). The hypotheses were analysed through structural equation modelling (SEM) using Lisrel. The results suggest different impacts of personality traits on facilitating the internationalisation process. According to the finding, extroversion and openness have a significant positive and agreeableness and conscientiousness have positive, less significant impacts on the tendency towards business internationalisation. Moreover, neuroticism impacts negatively significantly. Therefore, managers, founders, and owners of small- and medium-sized family firms who are extrovert, open, and non-neuroticism (tranquil) are more encaustic to making strategic decisions for extending their business to international markets.

The study aims to provide a critical review of the origin, development and process of sentiment analysis (SA) and a demonstration for hospitality researchers and students on how to perform SA using a sample study.

A critical review and sample case demonstration approach was applied. The sample study used Leximancer to perform SA using TripAdvisor review data.

A critical evaluation of the most popular SA tools was provided, highlighting their advantages and disadvantages. A step-by-step demonstration with data provided makes it possible for readers to learn this technique at own pace.

By providing a critical review of SA supported with a demonstration case study, this study makes a timely contribution for broader awareness and understanding, as well as the application of SA in hospitality.

The purpose of this study is to discover the components of virtual leadership in universities and higher education institutions during Covid-19 pandemic.

This research uses the qualitative research design, and semi-structured interviews with senior leaders were conducted with non-random purposeful and snowball sampling methods. Also, grounded theory was used for analyzing, coding and classifying the data.

After analyzing data, five main components influencing virtual leadership including leader's personality traits, followers' characteristics, technological, environmental and organizational components were identified.

As leadership, particularly virtual leadership, highly depends on context such as the level of technology in that certain region, the results cannot be generalized to other sectors or countries.

The research advances leadership development theory by highlighting the main components of virtual leadership in educational sector as a comprehensive perspective and complement the other aspects of virtual leadership such as consequences and challenges investigated by other studies.

The purpose of this study is to document how a traditional residential neighborhood, Ihwa village in Seoul, South Korea, is transformed into a tourist attraction and demonstrate the complexity of the overtourism phenomenon and the multifaceted conflicts among stakeholders that emerged in the course of urban transformation. Particularly, the study explores how tourism growth, urban transformation and overtourism are intertwined with each other and how the role of social media and media contributed to tourism growth and the transformation of an urban neighborhood.

The study conducted text analytics (a big data analysis) using personal blogs and news articles. Our data for text analytics was defined to retrieve all news articles and blogs existent in the NAVER portal, the largest Korean portal and search engine, for the period between January 1, 2006, and December 31, 2018. The data was collected using a web crawling program, TEXTOM version 3.0.

Text analysis of blog entries and news articles suggests that each medium has its unique role and domain to play. While the news media contributed to the initial surge of interest in Ihwa village, genuine growth of tourism in Ihwa village seems to be attributed to social media. Texts that appeared in blogs strongly indicated that people used their blogs to share their trip experiences, which can be subsequently assumed that blogs had an influential role in promoting a small place like Ihwa mural village, while news articles tended to highlight negative or unusual events occurred in Ihwa village. The study also addressed the multifaceted nature of the conflicts that were inherent in the issue of urban regeneration and how those conflicts were developed and manifested in the process of touristification and overtourism in Ihwa village. As touristification can manifest in various forms in different places, the case of Ihwa village demonstrates a unique development of touristification; private tourism companies or tourism agencies did not initiate or intend to cause tourism gentrification. Rather, touristification is a byproduct of urban revitalization through public art and is a result of interplay between the local government’s interest, social media and new tourist demand.

Text analytics using big data have rarely been attempted to understand the role of social media in relation to tourism growth and touristification of an urban tourism place. This study advances the literature by applying big data analysis to user-generated content in blogs. The study also contributes to the deeper understanding of a different developmental pattern of touristification in an urban tourism place as well as the complexity of the overtourism phenomenon and the multifaceted conflicts among stakeholders.

Sentiment lexicon is an essential resource for sentiment analysis of user reviews. By far, there is still a lack of domain sentiment lexicon with large scale and high accuracy for Chinese book reviews. This paper aims to construct a large-scale sentiment lexicon based on the ultrashort reviews of Chinese books.

First, large-scale ultrashort reviews of Chinese books, whose length is no more than six Chinese characters, are collected and preprocessed as candidate sentiment words. Second, non-sentiment words are filtered out through certain rules, such as part of speech rules, context rules, feature word rules and user behaviour rules. Third, the relative frequency is used to select and judge the polarity of sentiment words. Finally, the performance of the sentiment lexicon is evaluated through experiments.

This paper proposes a method of sentiment lexicon construction based on ultrashort reviews and successfully builds one for Chinese books with nearly 40,000 words based on the Douban book.

Compared with the idea of constructing a sentiment lexicon based on a small number of reviews, the proposed method can give full play to the advantages of data scale to build a corpus. Moreover, different from the computer segmentation method, this method helps to avoid the problems caused by immature segmentation technology and an imperfect N-gram language model.