Modeling the effects of strategic flexibility, organisational learning on e-business adoption and competitive advantage : an empirical investigation

The role of intangible firm capabilities as a source of competitive advantage has come into prominence in marketing strategy literature, due to the Resource Based View. This paper applies the Resource Based View and hypothesizes that strategic flexibility and organisation learning, conceptualised as capabilities, positively effect e-business adoption and competitive advantage. Partial Lease Squares analysis suggest that theoretical constructs function as hypothesised and explain a significant variation on e-business adoption and competitive advantage. Firms adopting e-business should develop capabilities such as strategic flexibility and organisation learning and that vendor firms may segment their potential clients based on these capabilities.

Shrinkage empirical likelihood estimator in longitudinal analysis with time-dependent covariates-application to modeling the health of Filipino children

The method of generalized estimating equations (GEE) is a popular tool for analysing longitudinal (panel) data. Often, the covariates collected are time-dependent in nature, for example, age, relapse status, monthly income. When using GEE to analyse longitudinal data with time-dependent covariates, crucial assumptions about the covariates are necessary for valid inferences to be drawn. When those assumptions do not hold or cannot be verified, Pepe and Anderson (1994, Communications in Statistics, Simulations and Computation 23, 939–951) advocated using an independence working correlation assumption in the GEE model as a robust approach. However, using GEE with the independence correlation assumption may lead to significant efficiency loss (Fitzmaurice, 1995, Biometrics 51, 309–317). In this article, we propose a method that extracts additional information from the estimating equations that are excluded by the independence assumption. The method always includes the estimating equations under the independence assumption and the contribution from the remaining estimating equations is weighted according to the likelihood of each equation being a consistent estimating equation and the information it carries. We apply the method to a longitudinal study of the health of a group of Filipino children.

Empirical vehicle-to-vehicle pathloss modeling in highway, suburban and urban environments at 5.8GHz

In this paper, we present a pathloss characterization for vehicle-to-vehicle (V2V) communications based on empirical data collected from extensive measurement campaign performed under line-of-sight (LOS), non-line-of-sight (NLOS) and varying traffic densities. The experiment was conducted in three different V2V propagation environments: highway, suburban and urban at 5.8GHz. We developed pathloss models for each of the three different V2V environments considered. Based on a log-distance power law model, the values for the pathloss exponent and the standard deviation of shadowing were reported. The average pathloss exponent ranges from 1.77 for highway, 1.68 for the urban to 1.53 for the suburban environment. The reported results can contribute to vehicular network (VANET) simulators and can be used by system designers to develop, evaluate and validate new protocols and system designs under realistic propagation conditions.

Critical success factors of process modeling for enterprise systems

The integrated and process oriented nature of Enterprise Systems (ES) has led organizations to use process modeling as an aid in managing these systems. Enterprise Systems success factor studies explicitly and implicitly state the importance of process modeling and its contribution to overall Enterprise System success. However, no empirical evidence exists on how to conduct process modeling successfully and possibly differentially in the main phases of the ES life-cycle. This paper reports on an empirical investigation of the factors that influence process modeling success. An a-priori model with 8 candidate success factors has been developed to this stage. This paper introduces the research context and objectives, describes the research design and the derived model, and concludes by looking ahead to the next phases of the research design.

The ontological deficiencies of process modeling in practice

Business process modeling is widely regarded as one of the most popular forms of conceptual modeling. However, little is known about the capabilities and deficiencies of process modeling grammars and how existing deficiencies impact actual process modeling practice. This paper is a first contribution towards a theory-driven, exploratory empirical investigation of the ontological deficiencies of process modeling with the industry standard Business Process Modeling Notation (BPMN). We perform an analysis of BPMN using a theory of ontological expressiveness. Through a series of semi-structured interviews with BPMN adopters we explore empirically the actual use of this grammar. Nine ontological deficiencies related to the practice of modeling with BPMN are identified, for example, the capture of business rules and the specification of process decompositions. We also uncover five contextual factors that impact on the use of process modeling grammars, such as tool support and modeling conventions. We discuss implications for research and practice, highlighting the need for consideration of representational issues and contextual factors in decisions relating to BPMN adoption in organizations.

Do ontological deficiencies in modeling grammars matter?

Conceptual modeling grammars are a fundamental means for specifying information systems requirements. However, the actual usage of these grammars is only poorly understood. In particular, little is known about how properties of these grammars inform usage beliefs such as usefulness and ease of use. In this paper we use an ontological theory to describe conceptual modeling grammars in terms of their ontological deficiencies, and formulate two propositions in regard to how these ontological deficiencies influence primary usage beliefs. Using BPMN as an example modeling grammar, we surveyed 528 modeling practitioners to test the theorized relationships. Our results show that users of conceptual modeling grammars perceive ontological deficiencies to exist, and that these deficiency perceptions are negatively associated with usefulness and ease of use of these grammars. With our research we provide empirical evidence in support of the predictions of the ontological theory of modeling grammar expressiveness, and we identify previously unexplored links between conceptual modeling grammars and grammar usage beliefs. This work implies for practice a much closer coupling of the act of (re ) designing modeling grammars with usage-related success metrics.

Evaluations of Process Modeling Grammars : Ontological, Qualitative and Quantitative Analyses Using the Example of BPMN

Business processes have emerged as a well-respected variable in the design of successful corporations. However, unlike other key managerial variables, such as products and services, customers and employees, physical or digital assets, the conceptualization and management of business processes are in many respects in their infancy. In this book, Jan Recker investigates the notion of quality of business process modeling grammars. His evaluation is based on an ontological-, qualitative-, and quantitative analysis, applied to BPMN, a widely-used business process modeling grammar. His results reveal the ontological shortcomings of BPMN and how these manifest themselves in actual process modeling practice, as well as how they influence the usage behavior of modeling practitioners. More generally, his book constitutes a landmark for empirical technology assessment, analyzing the way in which design flaws in technology influence usage behavior.

A measurement instrument for process modeling research : development, test and procedural model

Process modeling is an emergent area of Information Systems research that is characterized through an abundance of conceptual work with little empirical research. To fill this gap, this paper reports on the development and validation of an instrument to measure user acceptance of process modeling grammars. We advance an extended model for a multi-stage measurement instrument development procedure, which incorporates feedback from both expert and user panels. We identify two main contributions: First, we provide a validated measurement instrument for the study of user acceptance of process modeling grammars, which can be used to assist in further empirical studies that investigate phenomena associated with the business process modeling domain. Second, in doing so, we describe in detail a procedural model for developing measurement instruments that ensures high levels of reliability and validity, which may assist fellow scholars in executing their empirical research.

Functional heterogeneity as a two-dimensional concept : empirical evidence for new venture teams

Previous research on entrepreneurial teams has failed to settle the controversy over whether team heterogeneity helps or hinders new venture performance. Reconciling this inconsistency, this paper suggests a new conceptual approach to disentangle differential effects of team heterogeneity by modeling two separate heterogeneity dimensions, namely knowledge scope and knowledge disparity. Analyzing unique data on functional experiences of the members of 337 start-up teams, we find support for our contention of team heterogeneity as a two-dimensional concept. Results suggest that knowledge disparity negatively relates to both start-ups’ entrepreneurial and innovative performance. In contrast, we find knowledge scope to positively affect entrepreneurial performance, while it shows an inverse U-shaped relationship to innovative start-up performance.

Complementary use of modeling grammars

Conceptual modeling continues to be an important means for graphically capturing the requirements of an information system. Observations of modeling practice suggest that modelers often use multiple modeling grammars in combination to articulate various aspects of real-world domains. We extend an ontological theory of representation to suggest why and how users employ multiple conceptual modeling grammars in combination. We provide an empirical test of the extended theory using survey data and structured interviews about the use of traditional and structured analysis grammars within an automated tool environment. We find that users of the analyzed tool combine grammars to overcome the ontological incompleteness that exists in each grammar. Users further selected their starting grammar from a predicted subset of grammars only. The qualitative data provides insights as to why some of the predicted deficiencies manifest in practice differently than predicted.

Hotspot Identification: A Full Bayesian Hierarchical Modeling Approach

This study proposes a full Bayes (FB) hierarchical modeling approach in traffic crash hotspot identification. The FB approach is able to account for all uncertainties associated with crash risk and various risk factors by estimating a posterior distribution of the site safety on which various ranking criteria could be based. Moreover, by use of hierarchical model specification, FB approach is able to flexibly take into account various heterogeneities of crash occurrence due to spatiotemporal effects on traffic safety. Using Singapore intersection crash data(1997-2006), an empirical evaluate was conducted to compare the proposed FB approach to the state-of-the-art approaches. Results show that the Bayesian hierarchical models with accommodation for site specific effect and serial correlation have better goodness-of-fit than non hierarchical models. Furthermore, all model-based approaches perform significantly better in safety ranking than the naive approach using raw crash count. The FB hierarchical models were found to significantly outperform the standard EB approach in correctly identifying hotspots.

Modeling destination brand equity in an emerging long haul market

The destination branding literature emerged as recently as 1998, and there remains a dearth of empirical data that tests the effectiveness of brand campaigns over time. This paper reports the results of an investigation into consumer-based brand equity for Australia as a long haul destination in an emerging South American market. In spite of the high level of academic interest in the measurement of perceptions of destinations since the 1970s, few previous studies have examined perceptions held by South American consumers. Findings suggest that destination brand awareness, brand image, and brand value are positively related to brand loyalty for a long-haul destination. The results also indicate that Australia is a more compelling destination brand for previous visitors compared to non-visitors.

Empirical investigation of the usefulness of Gateway constructs in process models

Process modeling grammars are used to create scripts of a business domain that a process-aware information system is intended to support. A key grammatical construct of such grammars is known as a Gateway. A Gateway construct is used to describe scenarios in which the workflow of a process diverges or converges according to relevant conditions. Gateway constructs have been subjected to much academic discussion about their meaning, role and usefulness, and have been linked to both process-modeling errors and process-model understandability. This paper examines perceptual discriminability effects of Gateway constructs on an individual's abilities to interpret process models. We compare two ways of expressing two convergence and divergence patterns – Parallel Split and Simple Merge – implemented in a process modeling grammar. On the basis of an experiment with 98 students, we provide empirical evidence that Gateway constructs aid the interpretation of process models due to a perceptual discriminability effect, especially when models are complex. We discuss the emerging implications for research and practice, in terms of revisions to grammar specifications, guideline development and design choices in process modeling.

The benefit of modeling jumps in realized volatility for risk prediction : evidence from Chinese mainland stocks

Recent literature has focused on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.