Exploring influential factors affecting guest satisfaction

The amount of data in our world has been exploding, and big data represents a fundamental shift in business decision-making. Analyzing such so-called big data is today a keystone of competition and the success of organizations depends on fast and well-founded decisions taken by relevant people in their specific area of responsibility. Business analytics (BA) represents a merger between data strategy and a collection of decision support technologies and mechanisms for enterprises aimed at enabling knowledge workers such as executives, managers, and analysts to make better and faster decisions. The authors review the concept of BA as an open innovation strategy and address the importance of BA in revolutionizing knowledge towards economics and business sustainability. Using big data with open source business analytics systems generates the greatest opportunities to increase competitiveness and differentiation in organizations. In this chapter, the authors describe and analyze business intelligence and analytics (BI&A) and four popular open source systems – BIRT, Jaspersoft, Pentaho, and SpagoBI.

Technology in the hospitality industry is becoming increasingly important nowadays, because it has a close relationship with guest satisfaction and behavioral intention. This research aims to investigate hotel guests’ preferences of in-room technology amenities by different demographic groups, and to find out how technology amenities including robots, artificial intelligence, and service automation, affect hotel guests’ satisfaction, which in turn influence future behavioral intention to choose hotel and destination. This study uses a mixed quantitative and qualitative approach. Data are analyzed using SPSS and NVIVO. Results show that hotel guests’ preferences of technology amenities vary significantly by their education levels and will influence guests’ satisfaction and behavioral intention with regard to both hotel selection and destination selection. This paper appears to be the first attempt to investigate the influence of hotel guests’ technology preferences on their behavioral intention in both the hotel and the tourism destination context. With the expectation to help the hotel industry, managerial implications and suggestions on technology adoption were provided on the basis of data analysis.

Big data analytics provides many opportunities to develop new avenues for understanding hospitality management and to support decision making in this field. User-generated content (UGC) provides benefits for hotel managers to gain feedback from customers and enhance specific product attributes or service characteristics in order to increase business value and support marketing activities. Many scholars have provided significant findings about the determinants of customers’ satisfaction in hospitality. However, most researchers primarily used research methodologies such as customer surveys, interviews, or focus groups to examine the determinants of customers’ satisfaction. Thus, more studies must explore how to use UGC to bridge the gap between guest satisfaction and online reviews. This paper examines and compares the aspects of satisfaction and dissatisfaction of Greek hotels’ guests. Text analytics was implemented to deconstruct hotel guest reviews and then examine their relationship with hotel satisfaction. This paper helps hotel managers determine specific product attributes or service characteristics that impact guest satisfaction and dissatisfaction and how hotel guests’ attitudes to those characteristics are affected by hotels’ market positioning and strategies.

The Hospitality industry is the world's largest and fastest growing industry. Parallel with the phase of growth, social media and technological advancement play a vital role in the evolvement of the hospitality industry. It is imperative for hospitality industries to adopt technological information transfer to sustain the business in the long run. Thus, providing superior service quality very much depends on effective of social media and technology. The success of the hospitality and tourism industry is entirely dependent on its application of information technology and the achievement of the organization's objectives. One of the perplexing concerns gripping the hotel industry is the dearth of qualified managerial application of information technology in the organization. The hospitality industry especially hotels, where guests are treated with passion, the employees' implementation and usage of information technology plays a crucial role to influence their guest satisfaction. This article is based on qualitative research referring to constructs such as social media and technology information, service quality and guest satisfaction. Interviews were conducted on four- and five-star hotels with selected senior managers. The findings indicate that there is a strong significant relationship between social media and technology on the one hand and service quality and guest satisfaction on the other hand. The theoretical model of the article is based on Parasuraman's service quality theory, the technology acceptance model and resource - based theory. The significance of this study is that it reveals that information technology plays an important part in providing guest satisfaction in the new millennium thus, providing strategies for managers and supervisors in the hotel industry to achieve the desired performance in superior guest satisfaction.

Business analytics in manufacturing: Current trends, challenges and pathway to market leadership

This study examines the correlations between satisfaction and key factors such as brand image, trust, and green practices among hotel guests in Malaysia. As environmental awareness grows among consumers, many hotels have adopted green practices to meet the evolving expectations of environmentally conscious travelers. A survey was conducted with 386 Malaysian respondents aged 18 and above, all with prior experience visiting hotels that implemented green practices. Data was collected using convenience sampling through a structured Google Forms survey comprising three sections and a qualifying question about the respondents' experience with green hotels. The findings reveal a positive correlation between guest satisfaction and the variables of green practices, trust, and hotel image. This study underscores the importance of integrating sustainable practices into hotel operations not only to enhance brand image but also to build trust with guests, thereby fostering long-term customer satisfaction and loyalty. The results provide valuable insights for hotel managers seeking to improve service quality and establish a competitive edge in the growing green tourism market.

Background: Change is inevitable and as supply chain managers prepare for the future they face many challenges. Two major trends over the last few years are the growing importance of ‘big data’ and analysing these data though ‘analytics’. The data contain much value and companies need to capitalise on the variety of data sources by in-depth and proper analysis through the use of ‘big data’ analytics.Objective: This article endeavours to highlight the evolving nature of the supply chain management (SCM) environment, to identify how the two major trends (‘big data’ and analytics) will impact SCM in future, to show the benefits that can be derived if these trends are embraced and to make recommendations to supply chain managers.Method: The importance of extracting value from the huge amounts of data available in the SCM area is stated. ‘Big data’ and analytics are defined and the impact of these in various SCM applications clearly illustrated.Results: It is shown, through examples, how the SCM area can be impacted by these new trends and developments. In these examples ‘big data’ analytics have already been embraced, used and implemented successfully. Big data is a reality and using analytics to extract value from the data has the potential to make a huge impact.Conclusion: It is strongly recommended that supply chain managers take note of these two trends, since better use of ‘big data’ analytics can ensure that they keep abreast with developments and changes which can assist in enhancing business competitiveness.

Powerful, Flexible Tools for a Data-Driven WorldAs the data deluge continues in todays world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making and forecasting, and ultimately the solution of increasingly complex problems. Learn from the Creators of the RapidMiner Software Written by leaders in the data mining community, including the developers of the RapidMiner software, RapidMiner: Data Mining Use Cases and Business Analytics Applications provides an in-depth introduction to the application of data mining and business analytics techniques and tools in scientific research, medicine, industry, commerce, and diverse other sectors. It presents the most powerful and flexible open source software solutions: RapidMiner and RapidAnalytics. The software and their extensions can be freely downloaded at www.RapidMiner.com. Understand Each Stage of the Data Mining ProcessThe book and software tools cover all relevant steps of the data mining process, from data loading, transformation, integration, aggregation, and visualization to automated feature selection, automated parameter and process optimization, and integration with other tools, such as R packages or your IT infrastructure via web services. The book and software also extensively discuss the analysis of unstructured data, including text and image mining. Easily Implement Analytics Approaches Using RapidMiner and RapidAnalytics Each chapter describes an application, how to approach it with data mining methods, and how to implement it with RapidMiner and RapidAnalytics. These application-oriented chapters give you not only the necessary analytics to solve problems and tasks, but also reproducible, step-by-step descriptions of using RapidMiner and RapidAnalytics. The case studies serve as blueprints for your own data mining applications, enabling you to effectively solve similar problems.

Understanding the Design of Mobile Social Networking

The application of Big Data and time series models is currently at an early stage. This paper examines the relevance and use of time series analyses for Big Data and business analytics by discussing the emergence of Big Data in business, presenting time series models, and providing an example of how time series models can be efficiently and effectively applied in accounting and auditing using Big Data. Using sophisticated Big Data and time series models, millions of transactions can be searched to spot patterns and detect abnormalities and irregularities. The time series model and Big Data analysis presented in this paper provide policy, practical, educational, and research implications. Businesses and management can use our suggested time series model and Big Data analysis in their predictive models of managerial strategies, decisions, and actions. Business schools and accounting programs can integrate the time series model, Big Data, and data analytics into business and accounting education.

This research aims to analyze service quality, price perception, and brand image on guest satisfaction at Favehotel Gatot Subroto Jakarta. The type of data used is primary data in the form of respondents' opinions by distributing questionnaires. The population in this study is the customer of Favehotel Gatot Subroto Jakarta with a sample of 107 respondents by purposive sampling. The data obtained will be analyzed using quantitative methods with multiple linear regression analysis. Based on the research that has been done, the results show that the service quality variable, either simultaneously or partially, has a positive and significant effect on guest satisfaction, the price perception variable, either simultaneously or partially, has a positive and significant effect on guest satisfaction, and the brand image variable either simultaneously or partially. partial positive and significant effect on guest satisfaction.

The concept of business analytics has become an important source of performance and competitiveness of an organization in the digital era. This paper will look at how companies are using business analytics to make better decisions, increase operational efficiency, and drive innovation to become more competitive in the international markets. This study will follow a secondary data and conceptual analysis methodology, based on the findings of industries reports, literature, and examples of major companies all over the world.The results also show that business analytics can enhance the quality of decision-making processes largely by providing an opportunity to employ data-driven policies and minimise the level of intuition. It also makes operations more efficient through optimization of processes and utilization of resources and promoting innovation by creating predictive insights and using data to develop products and services. The paper also notes that the organizations that embrace analytics potentials are in a better position to react to dynamic market environments and have sustained competitive advantage.The overview shows that business analytics is considered a strategic resource, which is consistent with models of Business Analytics and Strategic Management. The use of analytics is on the rise in emerging markets, including India, but the issues regarding the skills, availability of data, and infrastructure still hamper the efficient use of analytics.The research adds to the current body of literature through offering a cohesive and holistic view on the place of business analytics in the competitiveness of the international market. It has meaningful implications on any organization and policymakers as it points out the relationship of building analytics capacity and incorporating it into their decision-making procedures. The evidence highlights the importance of using business analytics as a tool to attain competitiveness in the long-term, in a data-driven global landscape. Keywords Business Analytics, Global Competitiveness, Data-Driven Decision Making, Operational Efficiency, Innovation, Strategic Management, Big Data, India

This study explores the nexus of sustainable tourism, gastronomy experiences, and artificial intelligence in enhancing environmental stewardship and guest satisfaction in the hospitality industry. Over a month period (January 2024), 385 respondents were surveyed online (via LinkedIn) to investigate the impact of AI-driven solutions on operational efficiency, resource utilization, and guest satisfaction in gastronomy tourism. Utilizing inferential statistics, including chi-square tests, the findings indicated a high level of optimism towards AI's potential to improve efficiency and enhance guest satisfaction. Mean scores of 4.23 and 4.56 for AI-driven solutions' impact on efficiency and guest satisfaction, respectively, supported the positive outlook on sustainability-driven establishments using AI technologies. The study concludes that integrating AI solutions is pivotal in shaping environmental impact and guest satisfaction, offering opportunities to enhance operational efficiency and reduce resource consumption.

Many online shoppers rely heavily on user-generated content throughout their decision-making journeys. User-generated visual content in the form of images has become increasingly prevalent over the last decade (You, 2016). User-generated images are images created by consumers that expose the brand or product to the final users. The research examines UGIs in product reviews. The research asks, how do UGIs influence consumers’ brand image perceptions? Do consumers consider source credibility as a deciding factor? Are UGIs more effective than written forms of user-generated content? Product reviews that contain images depicting reviewers using the products play a vital role in demonstrating how the product might feel or look once a customer buys it. The way in which the product is depicted may distort or enhance the brand image perceptions of consumers browsing the product reviews. Aside from images, source credibility has also been consistently identified as an important cue in the informational influence process (Chaiken & Maheswaran, 1994; Sussman & Siegal, 2003). Users who post an image online act as the source, and their credibility can be evaluated by factors such as expert knowledge of the product, reviewer verification and disclosure of the image creator’s identity. We predict that source credibility will moderate the influence of user-generated images on brand image, where the negative effect of a repulsive image on brand image will be enhanced when the credibility of the user is high. Lastly, positive brand image should increase both purchase intention and eWOM. To test the proposed relationships, the authors will implement a 2 × 2 factorial design with two levels of user-generated image quality and two levels of user credibility. The authors will create a fictitious product review for each treatment. The review will be for a fictitious meal kit provider called Mealcopter. The brand image scale, adapted from Ansary and Hashim (2017), comprises six seven-point items. Source credibility will be measured using five dimensions— namely, accuracy, believability, bias, completeness and trustworthiness—in a scale adapted from Flanagin and Metzger (2000). The purchase intention scale comprises three seven-point items adapted from Hung et al. (2011), and the electronic word of mouth scale, adapted from Goyette (2010), comprises six seven-points items. The research aims to fill a gap in the literature on the effects of UGI on consumer brand image perception and shed light on the influence of source credibility on the effectiveness of UGIs. Managerially, the research addresses the extent to which managers should control the amount and type of user-generated images in product reviews.

Academic interest in understanding the impact of user-generated content (UGC) on consumer behavior in digital marketing has grown exponentially. However, we know little about the effect of UGC on customers’ online purchase intention from developing country aspects. This underpins the current study to examine the impact of UGC on the purchase intentions of university graduates in Bangladesh. With a convenient sampling approach, a structured questionnaire was provided directly to 400 respondents; 275 usable and complete responses were extracted for data analysis. Data were empirically validated using principal component analysis, reliability test, correlation, and Hayes PROCESS macro for regression and simple mediation analysis. The findings revealed that bloggers’ recommendations, online communities, and social media content positively and significantly influence customers’ online purchase intention. Brand image also directly impacts purchase intention and mediates the relationship between bloggers’ recommendations, online community, social media content, and online purchase intention. The results of this study will facilitate policymakers and online marketers in devising UGC management policies and digital marketing strategies. The study’s results may also help online marketers, sellers, and brand representatives to understand how to enhance brand image and amplify customers’ online purchasing behavior.