Digital Business最新文献

With the dissemination of web technologies, the transparency of other people's opinions has increased tremendously, thus the possibilities of observing other consumers' decisions have also risen. Consumers may take a shortcut to follow a herd — according to which people discount their own information to imitate others. Nonetheless, despite a large body of literature exploring the topics of herd behaviour, little is known about it in the context of the individual decision-making phases before, during, and after buying. This study, examines consumers' decisions in the context of mobile communications products, using a survey experiment. The findings show that subjects use the information from others as cues in making buying decisions, whereby the influence decreases along the buying process and in the post-buying phase, where people no longer seem to follow the herd. Additionally, recommendations of other consumers exert a stronger influence on subject choices than those of experts. Finally, friends seem to influence consumers' choices more than social networks.

Mobile gaming applications (apps) are increasingly engineered to encourage the sending and receiving information between players in hopes of generating word-of-mouth and stimulating purchases. This research utilizes a social influence perspective to examine the trait antecedents (identification as a member of the gaming community, susceptibility to informational influence) and behavioral consequences (paying for downloads of mobile app games, making in-app purchases, sharing of gaming experiences) of the desires to send and receive market information in mobile gaming apps.

A structural equation model was constructed and tested from a survey of 265 US adults who identified themselves as playing mobile gaming apps. Results show dramatically different antecedents and consequences between trait desires to send and receive market information in mobile gaming apps. The desire to send market information significantly and positively affected all three gaming behaviors, while the desire to receive market information had a negative effect on in-app purchases. The desire to send market information also fully mediated the impact of susceptibility to informational influence on all three behaviors. These findings help expand knowledge of informational exchange in mobile games to help developers increase engagement and monetization.

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.

Research on digital businesses builds upon a well-established set of theories, models, and frameworks. A frequently used approach within the paradigm of common variance theory is to first create a theory-based model and then test it using a multivariate method. Cross-sectional data is often used to test the overall fit of the model and the significance of its parameters, yet this approach fails to take into account the important role of temporal dynamics and the potential change of parameters over time, which constitutes an important research gap. For example, the popular Technology Acceptance Model (TAM) provides a snapshot in time, but cannot explain the postulated temporal patterns of the Diffusion of Innovations (DOI) theory. In this exploratory paper, we call for a theoretical and methodological paradigm shift and introduce process theory as a complement to the popular variance theory. This theory considers how entities change over time and create important network effects. Additionally, we illustrate how agent-based modeling (ABM) in combination with Structural Equation Modeling (SEM) can help to create models that combine the rigor of multivariate statistical methods with the capability of process theory to account for changes over time. Using ABM within the process theory paradigm can help to create meaningful models that are capable of incorporating temporal dynamics.

Purpose

This research explores the moderating role of Enterprise Resource Planning (ERP) in (Business Model (BM) innovation by comparing two groups of Small and Medium-sized Enterprises (SMEs) that are still in the process of considering adoption of ERP or already have implemented ERP. In particular, the aim is to see whether ERP enables or hampers the relationship between BM experimentation, i.e. the process of BM innovation, and BM performance. An important mediator, with a focus on downstream value delivery and creation, is the novelty of the BM in question.

Design/methodology/approach

This research is based on a large quantitative study among Spanish firms that are engaged in BM innovation activities and in different phases of implementing ERP. A representative sample of 208 Spanish firms engaged in Business Model Innovation from different sectors was used to collect data, which was analysed using heterotrait-monotrait (HTMT) for scaling and Structural Equation Modelling (SEM) for model testing.

Findings

Quantitative findings show that there is a direct positive impact of BM experimentation on BM performance for firms that did not implement an ERP, while downstream novelty leads to improved value capture due to increased efficiency and the associated cost reduction. By contrast, firms with ERP show a better performance, depending on the degree of the downstream novelty of the BM.

Originality/value

There is no previous research exploring the moderating role of ERP in BM Innovation for SMEs. This is the first study to examine whether BM experimentation affects BM performance and value capturing, as mediated by BM novelty and moderated by implementation by ERP.

Today, organizations make significant investments in information technology (IT) as a strategic resource to achieve their goals. If these investments are managed properly, they can create value for the organization. However, companies face problems in evaluating IT investment plans to gain value from them and improve organizational performance, which can be attributed to different reasons such as environmental uncertainty. Therefore, this study used a resource-based view and evaluated the impact of IT investment, IT management as two important IT resources, and strategic alignment on organizational performance by considering the moderating role of environmental uncertainty as one of the most important challenges of companies in IT usage. The quantitative approach was used and the required data was gathered using two questionnaires (one for IT managers and one for executives). The questionnaires were collected randomly from 70 IT managers, and 70 CIOs, and CEOs of small and medium-sized IT organizations (SMEs). Then data was analyzed using Structural Equation Modeling through using PLS software. Based on the results, strategic alignment and IT management are effective on organizational performance. Besides, environmental uncertainty moderated these relationships. The results of the study will help managers to nurture IT resources in their company to develop their strategies based on their perceived level of environmental uncertainty.

Anomaly detection approaches have become critically important to enhance decision-making systems, especially regarding the process of risk reduction in the economic performance of an organisation and the consumer costs. Previous studies on anomaly detection have examined mainly abnormalities that translate into fraud, such as fraudulent credit card transactions or fraud in insurance systems. However, anomalies represent irregularities in system patterns data, which may arise from deviations, adulterations or inconsistencies. Further, its study encompasses not only fraud, but also any behavioural abnormalities that signal risks. This paper proposes a literature review of methods and techniques to detect anomalies on diverse financial systems using a five-step technique. In our proposed method, we created a classification framework using codes to systematize the main techniques and knowledge on the subject, in addition to identifying research opportunities. Furthermore, the statistical results show several research gaps, among which three main ones should be explored for developing this area: a common database, tests with different dimensional sizes of data and indicators of the detection models' effectiveness. Therefore, the proposed framework is pertinent to comprehending an existing scientific knowledge base and signals important gaps for a research agenda considering the topic of anomalies in financial systems.

Rapid advances in technology, data, and analytics have helped maintenance services to evolve from a mere reactive process to a fully digital solution. Digital maintenance services exhibit a variety of functionalities to every adopting industry, with monitoring, diagnosing, troubleshooting, predicting, and optimizing being the common influencer. The presence of digital maintenance is slowly growing in the asset-intensive industries; however, the early adopters have been benefitting the most. This research tries to showcase a digital and sustainable maintenance service approach from both a scientific study and a practice perspective. It explains essential blocks of digital maintenance from a proposed model and provides a basis for new and in-depth research in digitally enabled reliability. Using a case study approach, it further aims to validate a functionality model for digital and sustainable maintenance services; explains different blocks as digital offerings; highlights the importance of digitalization and digital maintenance, and presents the results achieved based on the implementation. Metso Outotec being one of the early adopters of digital maintenance, their Connected Service is studied as a case study from a practical perspective for this research. The outcome observes positive sustainable impacts such as economic savings, reduced production loss, time saved, reduced travel to the site, and ensuring safety through fault prevention.

This paper examines how consumers create social capital in their interactions with other customers and service personnel while shopping in retail stores with both physical and digital locations. We draw on the servicescape literature to explore the role of social capital in determining the social realm in digital-physical servicescapes using data obtained from focus group discussions. Servicescapes encompass digital and physical store spaces and the interactions that occur within them. We demonstrate how customers utilise both the digital and physical servicescapes in a convergent manner to form the social realm of servicescapes with the other people in their service encounters. The implications of our findings provide guidelines on how the integration of the digital and physical channels facilitates trust, human contact, interpersonal relationships and networks of social exchange, which are collectively termed ‘social capital’.

Decision-making about startups' business models is highly dependent on available information, and the role of data analytics capabilities in business model innovation has been emphasized. Today's competitive intelligence tools such as Alexa, Google Analytics, Similarweb, NexLab TrackEngine, etc. easily provide the decision-makers with competitive intelligence. However, the quality of these decisions at the exposure of competitive intelligence is still unknown. We aim to investigate the role of competitive intelligence in entrepreneurs' decisions on business model pivoting at the early stages of their startups. We used a qualitative multi-case study of six startups to investigate the changes in the founders' attitudes toward their business models at the exposure of data analytics. Competitive intelligence led the early-stage entrepreneurs to pivot their business models. However, the quality of the resulted business models was questionable. To ensure the quality of decision-making, founders need to be supported by cognition service systems beyond the current competitive intelligence systems. Based on the findings we propose an extension to the Lean Startup build-measure-learn loop.