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The main aim of this paper is to build an approach to analyze the tourist content posted on social media. The approach incorporates information extraction, cleaning, data processing, descriptive and content analysis and can be used on different social media platforms such as Instagram, Facebook, etc. This work proposes an approach to social media analytics in traveler-generated content (TGC), and the authors use Twitter to apply this study and examine data about the city and the province of Granada.

In order to identify what people are talking and posting on social media about places, events, restaurants, hotels, etc. the authors propose the following approach for data collection, cleaning and data analysis. The authors first identify the main keywords for the place of study. A descriptive analysis is subsequently performed, and this includes post metrics with geo-tagged analysis and user metrics, retweets and likes, comments, videos, photos and followers. The text is then cleaned. Finally, content analysis is conducted, and this includes word frequency calculation, sentiment and emotion detection and word clouds. Topic modeling was also performed with latent Dirichlet association (LDA).

The authors used the framework to collect 262,859 tweets about Granada. The most important hashtags are #Alhambra and #SierraNevada, and the most prolific user is @AlhambraCultura. The approach uses a seasonal context, and the posted tweets are divided into two periods (spring–summer and autumn–winter). Word frequency was calculated and again Granada, Alhambra are the most frequent words in both periods in English and Spanish. The topic models show the subjects that are mentioned in both languages, and although there are certain small differences in terms of language and season, the Alhambra, Sierra Nevada and gastronomy stand out as the most important topics.

Extremely difficult to identify sarcasm, posts may be ambiguous, users may use both Spanish and English words in their tweets and tweets may contain spelling mistakes, colloquialisms or even abbreviations. Multilingualism represents also an important limitation since it is not clear how tweets written in different languages should be processed. The size of the data set is also an important factor since the greater the amount of data, the better the results. One of the largest limitations is the small number of geo-tagged tweets as geo-tagging would provide information about the place where the tweet was posted and opinions of it.

This study proposes an interesting way to analyze social media data, bridging tourism and social media literature in the data analysis context and contributes to discover patterns and features of the tourism destination through social media. The approach used provides the prospective traveler with an overview of the most popular places and the major posters for a particular tourist destination. From a business perspective, it informs managers of the most influential users, and the information obtained can be extremely useful for managing their tourism products in that region.

Enabled by increased (“big”) data stocks and advanced (“machine learning”) analyses, the concept of human resource analytics (HRA) is expected to systematically improve decisions in human resource management (HRM). Since so far empirical evidence on this is, however, lacking, the authors' study examines which combinations of data and analyses are employed and which combinations deliver on the promise of improved decision quality.

Theoretically, the paper employs a neo-configurational approach for founding and conceptualizing HRA. Methodically, based on a sample of German organizations, two varieties (crisp set and multi-value) of qualitative comparative analysis (QCA) are employed to identify combinations of data and analyses sufficient and necessary for HRA success.

The authors' study identifies existing configurations of data and analyses in HRM and uncovers which of these configurations cause improved decision quality. By evidencing that and which combinations of data and analyses conjuncturally cause decision quality, the authors' study provides a first confirmation of HRA success.

Major limitations refer to the cross-sectional and national sample and the usage of subjective measures. Major implications are the suitability of neo-configurational approaches for future research on HRA, while deeper conceptualizing and researching both the characteristics and outcomes of HRA constitutes a core future task.

The authors' paper employs an innovative theoretical-methodical approach to explain and analyze conditions that conjuncturally cause decision quality therewith offering much needed empirical evidence on HRA success.

The construction industry is affected by the technologies of Industry 4.0 as the buildings are transforming into complex productions. Integration of innovative technologies, such as virtual reality (VR) and augmented reality (AR), in construction management is an emerging area to increase efficiency and effectiveness. With an aim of determining the current situation, this study evaluates the literature on VR and AR within construction management research.

The methodology of this research is based on descriptive and bibliometric analyses to understand and state the current relations between VR-AR technologies and construction management research. According to the meta-analysis (Preferred Reporting Items for Systematic Reviews and Meta-Analyses [PRISMA]) protocol of reviewing, 143 papers between 2010 and 2021 from Scopus, Web of Science (WoS) and Science Direct have been retrieved, and then analysis has been applied on these papers. Descriptive analysis contains increment of publications throughout the years, rates of papers according to countries and content of the publications. The bibliometric analysis involves the analysis through Excel and VOSviewer: co-occurrence of keywords, country-based, source and citation.

The results of this study emphasize the increasing interest in the adoption of VR-AR technologies in construction management research. As the number of publications has been continuously increased, this trend indicates the strength and growing interest in the topic. Another significant finding is VR-AR implementation studies are mostly based on building information modelling (BIM). In this study, the results of analyses have been discussed in terms of learning, knowledge areas and digital technologies as part of construction management.

This study contributes to providing a significant theoretical reference for the potentials of VR-AR in construction management research. VR-AR technologies mostly attract the interest of researchers from architectural design studies; however, there is a gap to investigate their potentials in terms of construction management. Additionally, this study focuses on the last 11 years, which indicate the latest trends.

Statistical methods are important for meaningful analysis, critique and interpretation of results. The current study aims to investigate the use of statistical methods used in LIS research articles produced by Pakistani authors during 2001–2016.

Content analysis method with both the qualitative and quantitative components was used. LIS articles published by Pakistani authors in national and international journals from 2001 to 2016 were selected. The descriptive and inferential statistics were used to analyze the usage of statistical techniques.

The findings show that use of descriptive statistics remained higher as compared to inferential statistics in the LIS research produced by Pakistani authors. However, a visible growth trend in the use of inferential statistical techniques is found. Males are two times more likely to use inferential statistics as compared to female authors. Articles published in foreign journals and impact factor journals used more inferential statistics as compared to local and nonimpact factor journals. Parametric inferential statistics is more popular among Pakistani authors as compared to nonparametric. Faculty was more inclined toward using parametric statistic. The percentage of collaboration was higher in the papers using parametric statistics. Few articles reported the tests to fulfill the assumptions of parametric and nonparametric statistics.

This study can be used to better understand the trends of statistical techniques used in LIS research and authors' orientation in this regard. It will be helpful for future researchers in the selection of appropriate statistical techniques to be used.

In recent years, economic, environmental and social sustainability has become one of the fastest-growing research fields. The number of primary and secondary papers addressing the triple bottom line is growing significantly, and the supply chain (SC) management discipline is in the same wave. Therefore, this paper aims to propose a novel tertiary systematic methodology to explore, aggregate, categorise and analyse the findings provided by secondary studies.

A novel tertiary systematic literature review approach, including 94 secondary studies, is proposed and used to analyse sustainable SC literature. The papers have been analysed using a research protocol, including descriptive and content analysis criteria.

This tertiary study does not only provide an overview of the literature on the topic of sustainability in SCs but also goes further, drawing up a categorisation of main research areas and research perspectives adopted by previous researchers. The paper also presents a rank of research gaps and an updated and a prioritised agenda.

This paper provides a novel interpretation of the research topics addressed by the secondary studies and presents a new classification of the literature gaps and their evolution. Finally, a dynamic research compass for both academicians and practitioners is presented.

The objective of this paper is to analyze and interpret some empirical results, obtained from an online survey, on the types of review and analysis approaches used by organizations in manufacturing, service, education, health care, and not‐for‐profit sectors and their relationships with business performance.

Data were gathered using an online survey to capture basic information about the organization and its performance, the types of measures used in each of the five Baldrige results item groups, types and frequencies of review of the data, and types of analyses conducted. Results were analyzed using descriptive statistical analyses and tests for significant differences.

The results suggest that a significant gap exists in the sophistication of analysis methods between higher and lower performing organizations in terms of customer, financial, and market performance, and that better performance is associated with more mature and sophisticated approaches to performance analysis.

Because of the exploratory nature of this study, the generalizibility of the conclusions is limited; however, the results of this study can be useful for developing more formal theories to understand management practices and business performance and, as a basis for more designing, research efforts validate the propositions suggested by these theories.

Managers should invest in effective performance measurement systems that include sound approaches for analyzing results and sharing information appropriately throughout the organization.

This work provides further validation of the quality management principle and Baldrige core value of “management by fact,” and offers practical advice for designing effective performance management systems.

This study aims to enhance the knowledge by offering perspectives from an emerging market by reviewing the existing literature on food tourism. This study applies a multimethod analysis, providing insights into the advancement of food tourism in India, the contributions, critical findings and emerging research themes.

The study adopted a multimethod analysis using descriptive, narrative and bibliometric analysis using VOSviewer to analyze research papers published on food tourism in India shortlisted from Scopus and Google Scholar.

Future research should focus on gauging the potential of food tourism in different regions of the country, applying theoretical frameworks that have not been used. “Culinary Diversity and Heritage,” “Sustainable and Responsible Food Tourism,” “Consumer Behavior and Food Tourism Experiences,” “Rural Development and Economic Impact,” “Technology and Digitalization,” “Stakeholder Collaboration,” “Food Safety and Hygiene” and “Policy and Regulation” were the identified future research themes. These findings are significant for emerging economies across the globe.

This study summarized the progress of food tourism research in India, the contributions and emerging themes, supplementing the need to study food tourism in India. This study contributed methodologically to the literature by adopting a multimethod review combining descriptive, narrative and bibliometric analysis. Finally, by proposing ideas and constructs for future research, this study provides directions for future food tourism research from an emerging market’s perspective.

Findings will assist managers and stakeholders in comprehending the factors influencing tourists, destination marketing and branding, aiding in effective planning and executing food tourism strategies to promote destinations. The identified themes and keywords can help academicians and researchers dwell upon the emerging research themes in food tourism.

To the best of the author’s knowledge, this is the first study analyzing food tourism research in India adopting a multimethod analysis. The study provides an in-depth analysis applying descriptive, narrative and bibliometric analysis, highlighting the critical trends and research themes. A framework for future studies was also proposed.

该研究旨在通过回顾有关美食旅游的现有文献, 提供来自新兴市场的观点, 从而强化现有的知识。本研究采用多方法分析, 深入了解印度美食旅游的发展、贡献、重要发现和新兴研究主题。

该研究采用了多种方法分析, 使用 VOSviewer 进行描述性、叙述性和文献计量分析, 以分析从 Scopus 和谷歌学术搜索中入围的关于印度美食旅游的研究论文。

未来的研究应侧重于衡量该国不同地区美食旅游的潜力, 应用尚未使用的理论框架。 “烹饪多样性和传统”、“可持续和负责任的美食旅游”、“消费者行为和美食旅游体验”、“农村发展和经济影响”、“技术和数字化”、“利益相关者协作”、“食品安全和卫生”, “政策与法规”是确定的未来研究主题。这些发现对全球新兴经济体具有重要意义。

本研究总结了印度美食旅游研究的进展、贡献和新兴主题, 补充了研究印度美食旅游的必要性。本研究采用结合描述性、叙述性和文献计量分析的多方法回顾, 在方法论上为文献做出了贡献。最后, 通过提出未来研究的思路和结构, 本研究从新兴市场的角度为未来的美食旅游研究提供了方向。

调查结果将帮助管理者和利益相关者理解影响游客、目的地营销和品牌的因素, 帮助有效规划和执行食品旅游战略以促进目的地。 确定的主题和关键词可以帮助院士和研究人员深入研究食品旅游中新兴的研究主题。

El estudio tiene como objetivo mejorar el conocimiento al ofrecer perspectivas de un mercado emergente mediante la revisión de la literatura existente sobre turismo gastronómico. Este estudio aplica un análisis de múltiples métodos, que proporciona información sobre el avance del turismo gastronómico en la India, las contribuciones, los hallazgos críticos y los temas de investigación emergentes.

El estudio adoptó un análisis multimétodo mediante un análisis descriptivo, narrativo y bibliométrico utilizando VOSviewer para analizar los artículos de investigación publicados sobre el turismo gastronómico en la India preseleccionados de Scopus y Google Scholar.

La investigación futura debería centrarse en calibrar el potencial del turismo gastronómico en las distintas regiones del país, aplicando marcos teóricos que no se han utilizado. “Diversidad culinaria y patrimonio”, “Turismo gastronómico sostenible y responsable”, “Comportamiento del consumidor y experiencias de turismo gastronómico”, “Desarrollo rural e impacto económico”, “Tecnología y digitalización”, “Colaboración de las partes interesadas”, “Seguridad e higiene alimentaria”, “Política y regulación” fueron los temas de investigación futura identificados. Estos hallazgos son significativos para las economías emergentes de todo el mundo.

Este estudio resumió el progreso de la investigación sobre turismo alimentario en la India, las contribuciones y los temas emergentes, complementando la necesidad de estudiar el turismo alimentario en la India. Este estudio contribuyó metodológicamente a la bibliografía al adoptar una revisión multimétodo que combina el análisis descriptivo, narrativo y bibliométrico. Por último, al proponer ideas y constructos para futuras investigaciones, este estudio proporciona orientaciones para futuras investigaciones sobre el turismo gastronómico desde la perspectiva de un mercado emergente.

Los resultados ayudarán a los gestores y a las partes interesadas a comprender los factores que influyen en los turistas, el marketing de los destinos y la creación de marcas, contribuyendo a una planificación y ejecución eficaces de las estrategias de turismo gastronómico para promocionar los destinos. Los temas y palabras clave identificados pueden ayudar a los académicos e investigadores a profundizar en los temas de investigación emergentes en el turismo gastronómico.

Se trata del primer estudio que analiza la investigación sobre turismo gastronómico en la India adoptando un análisis multimétodo. El estudio proporciona un análisis en profundidad aplicando un análisis descriptivo, narrativo y bibliométrico, destacando las tendencias críticas y los temas de investigación. También se propone un marco para futuros estudios.

The purpose of this paper is to use Twitter analytics for analyzing the startup ecosystem of India.

The paper uses descriptive analysis and content analytics techniques of social media analytics to examine 53,115 tweets from 15 Indian startups across different industries. The study also employs techniques such as Naïve Bayes Algorithm for sentiment analysis and Latent Dirichlet allocation algorithm for topic modeling of Twitter feeds to generate insights for the startup ecosystem in India.

The Indian startup ecosystem is inclined toward digital technologies, concerned with people, planet and profit, with resource availability and information as the key to success. The study categorizes the emotions of tweets as positive, neutral and negative. It was found that the Indian startup ecosystem has more positive sentiments than negative sentiments. Topic modeling enables the categorization of the identified keywords into clusters. Also, the study concludes on the note that the future of the Indian startup ecosystem is Digital India.

The analysis provides a methodology that future researchers can use to extract relevant information from Twitter to investigate any issue.

Any attempt to analyze the startup ecosystem of India through social media analysis is limited. This research aims to bridge such a gap and tries to analyze the startup ecosystem of India from the lens of social media platforms like Twitter.

This paper aims to analyze how decision support systems manage Big data to obtain value.

A systematic literature review was performed with screening and analysis of 72 articles published between 2012 and 2019.

The findings reveal that techniques of big data analytics, machine learning algorithms and technologies predominantly related to computer science and cloud computing are used on decision support systems. Another finding was that the main areas that these techniques and technologies are been applied are logistic, traffic, health, business and market. This article also allows authors to understand the relationship in which descriptive, predictive and prescriptive analyses are used according to an inverse relationship of complexity in data analysis and the need for human decision-making.

As it is an emerging theme, this study seeks to present an overview of the techniques and technologies that are being discussed in the literature to solve problems in their respective areas, as a form of theoretical contribution. The authors also understand that there is a practical contribution to the maturity of the discussion and with reflections even presented as suggestions for future research, such as the ethical discussion. This study’s descriptive classification can also serve as a guide for new researchers who seek to understand the research involving decision support systems and big data to gain value in our society.