Extending Loyalty Programs with BI Functionalities

Effective customer loyalty programs are essential for every company. Small and medium sized brick-and-mortar stores, such as bakeries, butcher and flower shops, often share a common overarching loyalty program, organized by a third-party provider. Furthermore, these small shops have limited resources and often cannot afford complex BI tools. Out of these reasons we investigated how traditional brick-and-mortar stores can benefit from an expansion of service functionalities of a loyalty card provider. To answer this question, we cooperated with a cross-industry customer loyalty program in a polycentric region. The loyalty program was transformed from simple card-based solution to a mobile app for customers and a web-application for shop owners. The new solution offers additional BI services for performing data analytics and strengthening the position of brick-and-mortar stores. Participating shops can work together in order to increase sales and align marketing campaigns. Therefore, shopping data from 12 years, 55 shops, and 19,000 customers was analyzed

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Enhancing Collaborative CRM with Mobile Technologies

Mobile technology offers a high potential to significantly transform the ways how a company can interact with their customers and even with own employees. In recent years researchers started to analyze those potentials from the perspective of customer relationship management (CRM) but mainly concentrated on traditional business-to-customer (B2C) relationships. The concept of collaborative CRM extends this view of traditional CRM to virtual organizations and networked businesses. While the concept of collaborative CRM has been discussed by several authors already, the impact of mobile technology is still open to research. This paper investigates the role of mobile technology in collaborative CRM based on existing research, scenarios and supporting systems. The goal is to increase insight about the current role of mobile devices such as smartphones or personal digital agents (PDA) in collaborative CRM business scenarios and the support of these scenarios by CRM systems. From the broad scope of collaborative CRM the focus of this research is on collaboration with customers. The findings show that current mobile scenarios merely incorporate the collaborative CRM concept and that CRM systems provide only basic functionalities for incorporating mobile devices in collaborative CRM processes

The use of fitness centre apps and its relation to customer satisfaction: A UTAUT2 perspective

Purpose The purpose of this paper is to analyse the intention of using fitness app made available by the fitness centre to its members and their relationship with overall customer satisfaction. Design/methodology/approach The present study uses the extended unified theory of acceptance and use of technology (UTAUT2) as the base model. All the hypothesised relationships were tested through partial least square structural equation modelling (PLS-SEM), in a quantitative study with data from 1,676 fitness consumers from Portugal. Findings The results support the ability of UTAUT2 in predicting the customer´s intention to use the fitness app. Performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation and habit have a positive impact on behavioural intentions to use the fitness app. Performance expectancy and habit have the strongest relationships. Behavioural intentions are positively related both to the usage behaviour of the fitness app and to overall customer satisfaction. Practical implications The results of this study present a strong contribution for fitness centre managers, since it highlights the importance of using these apps as a way to increase customer satisfaction, increasing retention levels. Originality/value This study is paramount as regards to examine the behavioural intention to use the fitness apps that the fitness centres make available to their members using UTAUT2 model

An inquiry beyond the technology acceptance model

Liu, Y., Henseler, J., & Liu, Y. (2022). What makes tourists adopt smart hospitality? An inquiry beyond the technology acceptance model. Digital Business, 2(2), 1-10. [100042]. https://doi.org/10.1016/j.digbus.2022.100042.----- Funding: Jorg ¨ Henseler acknowledges a financial interest in the composite based SEM software ADANCO and its distributor, Composite Modeling. Moreover, he gratefully acknowledges financial support from FCT Fundaçãopara a Ciência e a Tecnologia (Portugal), national funding through a research grant from the Information Management Research Center – MagIC/NOVA IMS (UIDB/04152/2020). This research was supported by iFRG fund (FRG-22-004-INT) at Macau University of Science and Technology. Ms. Wenting FU provided support for data collection.Smart hospitality has become an attractive project in tourism. Extant research has studied smart technology as a contingency but has neglected to conceptualize smartness and investigate its consequences. This study conceptualizes and operationalizes smart hospitality and explores the relationships among smartness, perceived usefulness, perceived ease of use, overall image of a hotel and tourists' behavioral intention to stay in a smart hotel. The proposed model incorporated technology acceptance model (TAM) and image theory. With a sample of 348 respondents in Macau, this study tested the model using partial least squares path modeling (PLS-PM), which indicates that the proposed model fits the data. In spite of a high inter-construct correlation, the results showed that smartness does not have a direct effect on behavioral intention. According to mediation analysis, indirect effects made up of significant direct effects and assigned them to TAM, image theory, and a combination of both. This paper contributes to hospitality management theory by providing additional insight into smart hospitality, it demonstrates the applicability of PLS-PM with composite and common factor models in technological change research, and it suggests smartness as a business strategy that can change tourists' choices in practice.publishersversionpublishe

Examining the Role of Business Intelligence and Analytics in Hospitality Revenue Management

Most hospitality revenue management forecasting systems were built prior to the business intelligence and analytics movement. Only recently these systems have been enhanced to offer contemporary business intelligence and analytics functionalities. In addition, revenue management professionals are receiving support from standalone, supplementary business intelligence and analytics platforms. The purpose of this dissertation was to produce a holistic review of and establish the role of business intelligence and analytics within hospitality revenue management. Data was collected from twenty-three interviews; all participants were employed by hospitality organizations in revenue management specific positions. Grounded theory methodology was utilized. The results show that nearly all of revenue management tasks are supported by business intelligence and analytics functionalities, irrespective of where the functionalities are housed, in revenue management systems or in business intelligence and analytics tools. Also, opportunities to integrate more advanced functionalities into revenue management systems, including those relating to interfaces, were identified. As part of this inquiry, revenue managers’ beliefs and perceptions - including relative advantage, job-fit, and trust - were examined to determine which have influence on the usage of business intelligence and analytics within revenue management systems and as standalone tools. Overall, twenty-two categories/themes were formulated across four research questions. This dissertation contributes to the examination of the role of business intelligence and analytics in hospitality revenue management, but there is still much more to investigate, particularly as compatibility of hospitality systems and data management are improved

Music Streaming Services: Understanding the drivers of customer purchase and intention to recommend these services

Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementThe music industry has undergone strong changes in relation to its production, distribution and consumption habits, due to the exponential development of new technologies, namely streaming platforms. The fact that sales from physical copies continue to decline significantly made it mandatory for this industry to reinvent itself by introducing music streaming services as a key part of the development of its business. This study aims to understand the factors that influence the consumption of music through streaming platforms studying, particularly, the intention to purchase a paid version of a music streaming service and to recommend it. Therefore, an extension of the UTAUT2 model (version of the Unified Theory of Acceptance and Use of Technology, applied to the consumer side) was created. An online survey was used to collect data from 324 music streaming services users and the framework was tested using structural equation modelling (SEM). It also included in-depth semi-structured interviews in order to draw conclusions about the profile of the new music consumer. Our findings verify that habit, performance expectancy and price value play the most important role in influencing the intention to use a paid music streaming service. The intention to recommend these services was also confirmed. With this analysis, centred in UTAUT2 theory, we contribute with new insights about music streaming services consumer behaviour, providing several theoretical and practical implications to music streaming services providers