Search results

The bursting of the e‐bubble affected expectations with regard to mobile initiatives and willingness to invest in them very negatively. Business managers request detailed and thorough analyses prior to engaging in mobile initiatives. The paper aims to present a method, with which mobile business can be introduced to the customer relationship management (CRM) field.

The paper follows the design science paradigm as outlined by March and Smith, and Hevner et al.

The findings provide a framework for the definition of a mobile CRM strategy derived from the corporate strategy, suggest a method for the identification and exploitation of the mobilization potential in CRM processes in line with the strategy, and provide guidance for the design of mobile information systems to support these processes.

The proposed method extends the body of available methods with a method for the introduction of mobile ISs into marketing, sales and service organizations. As design research, it does not strive for statistical generalization. The level of detail given in the elements of the method is to be increased in further research.

The method helps to reduce risk and uncertainty of mobile CRM initiatives, since it provides a structured and consistent procedure for the definition of goals, the identification of potentials for the fulfillment of these goals as well as recommendations for the systematic exploitation of these potentials.

With the application of this structured method, an organization should be able to avoid the pitfalls of technology‐driven information technology initiatives which various companies have experienced, particularly with mobile technologies.

Restructuring a business process (BP) model may enhance the BP performance and improve its understandability. So-far proposed restructuring methods use either refactoring which focuses on structural aspects, social network discovery which uses semantic information to guide the affiliation process during its analysis, or social network rediscovery which uses structural information to identify clusters of actors according to their relationships. The purpose of this paper is to propose a hybrid method that exploits both the semantic and structural aspects of a BP model.

The proposed method first generates a social network from the BP model. Second, it applies hierarchical clustering to determine the performers’ partitions; this step uses the social context which specifies features related to performers, and two new distances that account for semantic and structural information. Finally, it applies a set of behavioral and organizational restructuring rules adapted from the graph optimization domain; each rule uses the identified performers’ partitions and the business context to reduce particular quality metrics.

The efficiency of the proposed method is illustrated through well-established complexity metrics. The illustration is made through the development of a tool that fully supports the proposed method and proposes a strategy for the application of the restructuring rules.

The proposed method has the merit of combining the semantic and structural aspects of a Business Process Modeling Notation model to identify restructuring operations whose ordered application reduces the complexity of the initial model.

Introduction: New ideas and concepts of big data have emerged in recent years in response to the astounding growth of data in many industries. Furthermore, the phenomenal increase in the use of the internet and social media has added enormous amounts of data to conventional data processing systems. Still, it has also created challenges for traditional data processing.

Purpose: A significant characteristic of the insurance sector is critically dependent on information. This sector generates a great deal of structured and unstructured data, which traditional data processing techniques cannot handle. As compared to conventional insurance data processing and decision-making requirements, this lesson shows an analysis of data technology’s value additions.

Research methodology: The author assesses the primary use of cases for data in the insurance industry via a case study analysis. From the perspective of the insurance sector, this chapter examines the concepts, technologies, and tools of big data. A few analytical reviews by the insurance company are also provided, which justified several gains gained either through inefficient processing of massive, diverse data sets or by supporting better decisions.

Findings: This chapter demonstrates the importance of adopting new business models that allow insurers to move beyond understand and protect and become more predictive and preventative by using the tools and technologies of big data technology.

The purpose of this paper is to explore the adoption of a mobile insurance claim system (M-insurance) and develops a framework for the adoption of M-insurance by consumers.

This study assesses mobile technology for claim management through the lens of the technology acceptance model (TAM) and diffusion of innovation (DOI) models as a major guideline, using exploratory research through in-depth interviews with four executive experts who are first movers in mobile claim motor insurance in Thailand. Semi-structured interviews and open-ended questions were used to conduct group interviews of insurance consumers who mostly use smartphones. The data were collected in a qualitative research approach from Thai insurance consumers (n=177), and contents were classified and analysed to gain strong insights into respondent opinions, comments, attitudes, behaviour, and experiences.

The results indicate that the external (social) factors influence attitude and behaviour of consumers which link to their intention to adopt M-insurance. These external factors include: preference for face-to-face service; confidence of insurers in accepting claim; and risk of claim knowledge that might cause legal issues among others. In application, the findings shall meaningfully enhance insurer firms’ improvement of adoption rate and development of future features and functions of M-insurance.

This study is based on insurance consumers in each region of Thailand but focuses only on mobile claim management for motor insurance. Although the findings bring new insight and understanding of consumer preferences and behaviours, they were not tested statistically.

The study has practical implications for motor insurance claimants who are concerned over the complicated policy conditions, the perspective risk of claim knowledge and fault admission, and the on-site investigation by surveyor for another party. These are the guidance impediments to overcome M-insurance adoption improvement.

Previously, TAM and DOI approaches have been employed to study general adoption of M-banking by quantitative research which confirmed descriptive data and tested the hypothesis, but neglected crucial data. However, M-insurance is different from M-banking in term of features and functions, purpose and process of usage, and legal liability. Therefore, this study is one of a few empirical studies that attempt to identify insightful factors to consumer uptake of M-insurance which is in its early stage and lacks an underpinning TAM model. This study contributes by identifying insights of “pull” factors to successfully develop M-insurance in Thailand.

The purpose of this paper is to present a new heuristic approach for finding errors and possible improvements in business process models.

First, the paper translates the information that is included in a model into a set of Prolog facts. It then searches for patterns which are related to a violation of the soundness property or bad modeling style or otherwise gives rise to the assumption that the model should be improved. To validate this approach, the paper analyzes a repository of almost 1,000 business process models. For this purpose, three different model‐checkers that explore the state space of all possible executions of a model are used. The result of these tools are compared with the results given by this heuristic approach.

The paper finds that the heuristic approach identifies violations of the soundness property almost as accurate as model‐checkers. However, other than these tools, the approach never ran into state space explosion problems. Furthermore, this heuristic approach can also detect patterns for bad modeling style which can help to improve the quality of models.

Heuristic checks can run in the background while the modeler works on the model. In this way, feedback about possible modeling errors can be provided instantly. This feedback can be used to correct possible problems immediately.

Current Prolog‐based validation tools check mainly for syntactical correctness and consistency requirements. This approach adds one more perspective by also detecting control‐flow errors (like deadlocks) and even pragmatic issues.

The purpose of this paper is to present a development to the hardware and software of a real-time tracking system that provides the position of the tracked vehicle accurately using fairly low-cost equipment and services. Vehicle tracking industries are expanding as businesses are interested to know their fleet vehicles positions minute by minute every day. Many systems were proposed recently that can provide such information.

The system is implemented using GM862 cellular quad band module. A monitoring server and a graphical user interface on a Web site have also been implemented to view the current location of a vehicle on a specific map.

The experiments were conducted and tested in different areas of the Kingdom Of Bahrain using Google maps, and results are discussed.

The developed system has been compared to the available and imported tracking systems to some of the telematics companies in Bahrain, and the comparison has been discussed.

The purpose of this paper is to present business process point analysis (BPPA), a technique to measure business functional process size, based on function point analysis (FPA), and using business process model and notation (BPMN). This paper also discusses the assessment results of BPPA compared with FPA.

Two experimental studies with participants from academia and industry were conducted. The following aspects in the experimental studies were focused: similarity, application easiness, feasibility, and application benefits. The purpose of the experiment was to assess BPPA comparing with FPA as the BPPA design followed the FPA pattern.

Experimental results showed that both academia and industry groups highly rated similarity and application benefits for BPPA compared with FPA. However, only participants from industry highly rated BPPA for application easiness and feasibility. The results also showed that participants’ previous experiences did not influence their ratings on BPPA.

BPPA helps project managers to measure functional process size of business process management projects. As BPPA is derived from FPA, its mechanism is easily recognizable by project managers who are used to FPA. These results also show that both techniques are in most cases considered rather similar.

The purpose of this paper is to present results from an analysis of service processes regarding their optimization potential through mobile technologies. The analysis was performed with a company of the housing industry.

The analysis was conducted with the aim of organizing business processes more efficiently in order to realize cost savings. Therefore, a method introduced in this paper was used.

It is shown how the initial situation of the company was analyzed, which alternative process models on the basis of mobile technologies were developed and how these alternatives were economically evaluated. Furthermore, first restrictions for the software and system design were identified on the basis of one process model. Finally, it is shown how the method can be used to verify whether the adoption of mobile technologies is suitable to obtain a defined goal, and which requirements such a solution needs to fulfill.

This paper shows practitioners how to conduct a systematic analysis of business processes regarding their optimization potential through mobile technologies.

A large‐strain/high‐deformation rate model for clay‐free sand recently proposed and validated in our work [1,2], has been extended to sand containing relatively small (< 15vol.%) of clay and having various levels of saturation with water. The model includes an equation of state which represents the material response under hydrostatic pressure, a strength model which captures material behavior under elastic‐plastic conditions and a failure model which defines conditions and laws for the initiation and evolution of damage/failure in the material. The model was validated by comparing the computational results associated with detonation of a landmine in clayey sand (at different levels of saturation with water) with their computational counterparts.