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The objective of this study is to analyze the experiences in wine tourism according to narratives shared by the visitors themselves. Furthermore, this study aims to examine the levels of intensity associated with these experiences within a wine destination, considering the segmentation of visitors.

This study uses a mixed-methods approach to analyze data, incorporating a deductive process followed by content analysis. Data collection procedures include a bibliographic review and a data survey conducted through netnography research to analyze 954 visitor reviews on TripAdvisor shared by visitors to Vale dos Vinhedos. Also, statistical analysis is performed to assess whether there are any significant variations in attribute citations among different market segmentation profiles.

The study’s discoveries indicate that there are no significant differences in intensity among profile segments for the dimensions of entertainment, aesthetics, educational and interactions, unlike escapism. The findings reveal that attributes such as “winery,” “wine,” “products and services” and “landscape” are essential for all visitors. In addition, the study shows that social interactions in the wine tourism destination are not as significant as previously assumed.

This research study constitutes a methodological advancement in the field of market segmentation using electronic word-of-mouth data. It provides crucial insights into the experiential nuances of the research locus and the varying degrees of these experiences in relation to visitor segmentation. Additionally, the contributions of this study are not only of theoretical importance but also hold practical implications for market segmentation strategies.

This study aims to develop and validate a scale for measuring accounting service quality (ASQ), which is named ACCOUNTQUAL.

The authors initially investigated the service quality literature in the context of accounting. To develop the scale, the authors carried out three studies. First, the authors conducted 20 in-depth interviews to generate the ASQ items. Then, they undertook a survey with 174 accounting services clients to group these items into factors through exploratory factor analysis (EFA). Finally, the authors carried out another survey with 330 clients to purify and validate the scale through a confirmatory composite analysis (CCA) and structural equation modeling (SEM).

The authors were able to validate the ACCOUNTQUAL scale, which is composed of the following dimensions: efficiency, trust, technological innovation and accountant knowledge, the latter being composed of three aspects: consultative view, technical capacitation and knowledge about clients.

The authors concluded that ASQ is a multidimensional construct that covers the assessment of technical, tooling, relationship and qualification aspects of the accounting service. To the best of the authors’ knowledge, this is the first study that developed and validated a scale for measuring ASQ. If accounting service providers meets the elements presented in the scale, they will potentially deliver a high-quality service.

This paper aims to analyse the bibliometric characteristics of the ISO 50001 publication, map the state of the art of the research topic and identify future research issues.

This research is a bibliometric study. The data were collected from Scopus. Both performance and science mapping analysis were performed.

The research results showed the top author, paper and country of ISO 50001 publications. There are four author collaboration clusters and five country collaboration clusters. Eight research themes were mapped into four quadrants based on the density and centrality. The bibliometric coupling analysis showed six research clusters. Finally, the research issues were mapped. The implications were discussed.

This research gave several implications for researchers, practitioners and public policymakers. For researchers, the bibliometric analysis provides several research issues that can be followed up by future research. For practitioners, the bibliometric analysis showed that applied tools and methods that can assist the implementation of ISO 50001-based energy management have been developed. For public policymakers, the bibliometric analysis offered the knowledge structure on ISO 50001 that can be used in public policymaking development. The author collaboration cluster and the bibliometric coupling cluster can be used to trace the scientific information that is needed as the foundation of public policy.

Many ISO 50001 studies have been performed. However, based on the search in several main academic scientific paper databases, there is no bibliometric study on the research topic. This is the first bibliometric study on ISO 50001 publication. This study takes a holistic approach combining performance analysis and science mapping analysis that includes elaborated thematic mapping and evolution analysis.

This study aims to examine the technical efficiency of the chemical-free farming system in India using a hybrid combination of data envelopment analysis (DEA) and machine learning (ML) approaches.

The study used a two-stage approach. In the first stage, the efficiency scores of decision-making units’ efficiency (DMUs) are obtained using an input-oriented DEA model under the assumption of a variable return to scale. Based on these scores, the DMUs are classified into efficient and inefficient categories. The 2nd stage of analysis involves the identification of the most important predictors of efficiency using a random forest model and a generalized logistic regression model.

The results show that by using their resources efficiently, growers can reduce their inputs by 34 percent without affecting the output. Orchard's size, the proportion of land, grower's age, orchard's age and family labor are the most important determinants of efficiency. Besides, growers' main occupation and footfall of intermediaries at the farm gate also demonstrate significant influence on efficiency.

The study used only one output and a limited set of input variables. Incorporating additional variables or dimensions like fertility of the land, climatic conditions, altitude of the land, output quality (size/taste/appearance) and per acre profitability could yield more robust results. Although pineapple is cultivated in all eight northeastern states, the data for the study has been collected from only two states. The production and marketing practices followed by the growers in the remaining six northeastern states and other parts of the country might be different. As the growers do not maintain farm records, their data might suffer from selective retrieval bias.

Given the rising demand for organic food, improving the efficiency of chemical-free growers will be a win-win situation for both growers and consumers. The results will aid policymakers in bringing necessary interventions to make chemical-free farming more remunerative for the growers. The business managers can act as a bridge to connect these remote growers with the market by sharing customer feedback and global best practices.

Although many developments have happened to the DEA technique, the present study used a traditional form of DEA. Therefore, future research should combine ML techniques with more advanced versions like bootstrap and fuzzy DEA. Upcoming research should include more input and output variables to predict the efficiency of the chemical-free farming system. For instance, environmental variables, like climatic conditions, degree of competition, government support and consumers' attitude towards chemical-free food, can be examined along with farm and grower-specific variables. Future studies should also incorporate chemical-free growers from a wider geographic area. Lastly, future studies can also undertake a longitudinal estimation of efficiency and its determinants for the chemical-free farming system.

No prior study has used a hybrid framework to examine the performance of a chemical-free farming system.