This research aims to study the pre-pandemic and pandemic-period Industry 4.0 and Industry 5.0 characteristics in SME research using scientometrics and systematic review using the PRISMA 2020 approach. A total of 691 articles were found in SCOPUS database using keywords ((“Industry 4.0” OR “Industry 5.0”) AND “SME”). However, 398 documents, which were either conference proceedings, reviews, book chapters or published in languages other than English, were excluded, and the remaining 221 articles that were published in SCOPUS indexed Journals were included in the study. This research adopted a novel mix of scientometrics and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 recommendations for identifying the thematic evolution of pre-pandemic and pandemic-period Industry 4.0 and Industry 5.0 SME Research. The major findings of this systematic review are, (1) There is a conceptual shift among researchers in studying the Industry 4.0 adoption of SMEs during the pandemic period; (2) The pandemic period research focused on (a) human-centric approaches, (b) adoption/acceptance models, (c) cost-effective solutions, (d) COVID-19 impact and resilience, (e) artificial intelligence and predictive maintenance, and (f) the emerging role of open innovation in Industry 4.0 adoption of SMEs; (3) Though the concept of Industry 5.0 clearly emerged and supplemented industry 4.0, the keyword “Industry 5.0” is not widely adopted by researchers. From the systematic literature review, a conceptual model for assessing the Industry 4.0 adoption and digital transformation of SMEs, digital integration of value chains and participation in a global value chain for trade expansion and sustainable growth of SMEs is proposed.

The aim of this study was to develop higher-order scales for assessing sustainable supply chain management practices, innovation adoption, and sustainable firm performance in the restaurant sector. Three different higher-order scales were developed for assessing the SSCM, SFP and innovation adoption. The first scale for SSCM higher-order construct consisted of service–product supply chain management practices (SPSSCM), service–setting supply chain management practices (SSSSCM), and service–delivery supply chain management practices (SDSSCM). The second higher-order scale for sustainable firm performance (SFP) consisted of economic, operational, environmental, and socio-cultural performance. The third higher-order scale for innovation adoption (INNO) consisted of “product- and process-based innovation”, “marketing-based innovation”, “technology-based innovation” and “organizational innovation”. The face, content, construct, convergent, and discriminant validity was tested using pilot study, expert opinion, EFA, and CFA. With 178 responses collected from restaurateurs, managers, and supervisors of casual restaurants in Prachuap Khiri Khan province in Thailand, this study evaluates the direct effects of SSCM on SFP. It further evaluates the mediating role of innovation adoption between sustainable supply chain management practices and firm performance and the moderated mediation effects of socio-demographic factors such as age, gender, education, and experience. The results reveal that sustainable supply chain management practices can positively lead to sustainable firm performance. However, irrespective of the indirect effects of socio-demographic factors, adopting innovation completely mediates the relationship between sustainable supply chain management practices and firm performance.

This study aims to forecast air passenger and cargo demand of the Indian aviation industry using the autoregressive integrated moving average (ARIMA) and Bayesian structural time series (BSTS) models. We utilized 10 years’ (2009–2018) air passenger and cargo data obtained from the Directorate General of Civil Aviation (DGCA-India) website. The study assessed both ARIMA and BSTS models’ ability to incorporate uncertainty under dynamic settings. Findings inferred that, along with ARIMA, BSTS is also suitable for short-term forecasting of all four (international passenger, domestic passenger, international air cargo, and domestic air cargo) commercial aviation sectors. Recommendations and directions for further research in medium-term and long-term forecasting of the Indian airline industry were also summarized.

This study aims to develop four conceptual higher order models for assessing the causal relationship between the environmental turbulence (ET), sustainable competitive advantage (SCA), business model innovation (BMI), and sustainable performance (SP) of small and medium sized enterprises (SMEs). The conceptual models were developed through literature review and tested with 91 entrepreneurs and managers from processed marine food product SMEs in Thailand. The higher order models were tested with partial least square structural equation modeling using seminr package in R. The results reveal that SCA mediates the relationship between BMI and SP. Further, the study found a serial mediation effect of BMI and SCA in the relationship between ET and SP. Thus, this study is novel in its approach of using ET as an antecedent and moderator and SCA as a mediator in assessing the relationship between BMI and SP. The study also found that the effects of ET are balanced when the SMEs incorporate BMI, which further leads to the achievement of SCA and SP. Thus, the findings extend an increasingly complex literature in the assessment of SCA’s role in SMEs’ SP. Further, the scale and the models can be used to assess how the SMEs respond to ET and modify their BMI to attain SCA and SP.

This study adopts a novel mix of scientometrics, theme-based, citation-based systematic review and interpretative aggregation approach (STCSR-IA) with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. It presents a macro-level scientometric analysis of tourism research in coastal, marine and maritime (blue tourism) environments by using 986 research articles published in 130 Scopus-indexed journals from 2000 to 2019. The thematic evolution of research in five time periods of four years each (2000–2003, 2004–2007, 2008–2011, 2012–2015, 2016–2019) was analysed using the authors’ keywords and classified as (a) preliminary (b) transversal stage I (c) transversal stage II and (d) growth stage. The massive evolution of research areas in the growth stage and their themes along with the growing nexus of conceptual relationship within blue tourism is systematically reviewed and presented as a thematic research framework.