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Organizational decision‐makers require information presented in ways that allow them to make informed decisions on the effectiveness of change interventions. Current statistical methods do not provide enough information about the practical value of organizational interventions to decision‐makers. It is proposed that a strong hypothesis testing strategy provides a partial answer to this problem. The hypothesis testing method presented here uses Bayesian statistics to test null hypotheses other than the traditional Ho = 0. A description of the evaluation of a change project in six manufacturing plants of a large United States corporation is provided. The data from this project is used to show how both statistical and practical significance may be tested using this hypothesis testing method. The applicability of the strong hypothesis testing approach to the assessment of organizational change is then discussed, and recommendations are made for evaluations conducted in field settings.

To explore the appropriateness of statistical significance testing to measure the practical, managerial significance of outcomes in marketing programmes.

An in‐depth analysis of SST's scientific roots is coupled with delineation of a set of general objectives of marketing‐programme measurement to identify the applicability limits of significance testing.

In particular, it is shown that the relatively well known sample‐size dependence of SST and its somewhat lesser known replicability, representativeness and impact fallacies can severely affect the robustness of significance tests. Statistical significance is not the same concept as practical significance.

Comprehensive discussion of principles and practice leads to a set of prescriptive usage recommendations, directed at the goal of establishing much‐needed applicability rules and limits for the use of significance‐testing methodologies in an applied marketing context.

This robust challenge to the efficacy of significance testing in marketing practice should be of interest to any marketing planner concerned with the collection and use of marketing intelligence.

We searched JM from 1990 to 2005 to identify all studies that employed OLS regression.¹ The search resulted in 83 articles with 147 OLS regressions. Many authors specifically state that they used OLS and these were promptly included in the sample. Other authors acknowledged regression as a methodological procedure without explicitly specifying an estimation technique. To inquire whether OLS was used, we communicated with all of these authors. In all, 51 authors were contacted, with 44 responding. Of the 44 that responded 43 had used OLS; the only exception was subsequently excluded from the analysis. The remaining seven articles were checked once more, and consensus was reached that OLS had most likely been used. Therefore, they were also included in the study.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

It is generally recognized that multinational enterprises must take into account country differences in deciding the degree to which it makes sense to localize their human resource management (HRM) strategies and organization cultures to fit with the host country or rather standardize HRM strategies and organization cultures across countries. However, an important vein of academic work assumes that country differences, especially in national culture, are so important that management is “culturally dependent” (Hofstede, 1983) and that “national culture constrains variation in organization cultures” (Johns, 2006). I critically evaluate the logical and empirical evidence (including methodological issues regarding effect size) used to support such constraint arguments and conclude that the evidence is much weaker than widely believed. One implication then is that organizations may be less constrained by national culture differences in managing workforces in different countries than is often claimed. A second implication is that researchers may wish to re-think how they study such issues. I provide suggestions for future research.

Constructing and evaluating behavioral science models is a complex process. Decisions must be made about which variables to include, which variables are related to each other, the functional forms of the relationships, and so on. The last 10 years have seen a substantial extension of the range of statistical tools available for use in the construction process. The progress in tool development has been accompanied by the publication of handbooks that introduce the methods in general terms (Arminger et al., 1995; Tinsley & Brown, 2000a). Each chapter in these handbooks cites a wide range of books and articles on specific analysis topics.

In order to better optimize the internal management system of book publishing and to cope with the changes in the external market environment, the purpose of this paper is to carry out cross-border publishing with the help of a transmedia storytelling model to realize the transformation and upgrading of the industry. Focusing on the relationship between the book publishing transmedia storytelling model and business performance, the moderating effect of the innovation environment on different variables is assessed.

This paper proposes several feasible hypotheses based on existing research. The research data came from 365 managers of Chinese book publishing organizations, and the scale was validated by Cronbach’s a, composite reliability (CR) and average variance extracted (AVE). Reliability and validity were verified, and correlation and regression analyses were used to test the impact of the book publishing transmedia storytelling model on business performance and to analyze the moderating role of the innovation environment.

The results show that the book publishing transmedia storytelling model (content production, technology integration, organizational innovation, marketing integration) helps to improve business performance (market performance, financial performance), and the innovation environment has a positive moderating effect on the relationship between the book publishing transmedia storytelling model and business performance, which provides a guarantee for the transformation and upgrading of book publishing. The market information reflected in the innovation environment has a certain role in promoting the innovation and business performance of the book publishing transmedia storytelling model.

The empirical evidence provides a theoretical link between the book publishing transmedia storytelling model and business performance, but there are still some shortcomings, and more factors, such as equity structure, government subsidies and research and development investment, should be included in future research. In addition, the scope of the research should be broadened on this basis to make the results of the data analysis more objective.

This paper introduces the transmedia storytelling model and deeply analyzes the relationship between the book publishing transmedia storytelling model and business performance, which is of great practical significance for optimizing the application and service quality of book publishing, prolonging the industrial chain, enhancing the interaction and participation of users and perfecting the business management system of the book publishing industry.

The application and research of the book publishing transmedia storytelling model are imperfect. Therefore, this paper not only helps to promote the innovation of book publishing organizational structure and improve the management system of business performance, but also may help to improve the innovation environment of book publishing enterprises and promote the diversification of industrial structure.

The purpose of this paper is to consider the following three kinds of cases: first, where a network of stochastic automata consists of a neuron of several types; second, where not only pair‐wise interaction of the neuron occurs, but also that between groups of the neuron; and, third, where neurons are located in d‐dimensional Euclidean space. This is based on neurons of different types having been distinguished by the neurophysiological theory of the retina of vertebrates, where the retina consists of overlapping sheets which are composed of cells receiving light, bipolar cells, ganglion cells, respectively; there are also horizontal cells and amacrine; a functional unit of the central nervous system of vertebrates is composed of the group of neurons which have the form of a network; and the case where neurons are located in d‐dimensional Euclidean space will extend theoretical significance and practical significance of abstract neural automata. The existence of abstract neural automata will be proved in all three cases.

The purpose of this research paper is to present a pragmatic and systematic approach to conduct and document Design Science Research (DSR) activities with Focus Groups (FGs), exploring its continuous usage and providing traceability between problem, requirements, solutions and artefacts.

The approach is to conduct the research and produce the meta-model for DSR with FG, a DSR approach was adopted using a conceptual model for Action Design Research already available. The artefact is the result from a specific literature review to define requirements, a careful design and a refinement stage where it was widely used and tested in real IS implementation projects.

Rigorous and committed stakeholder engagement is a critical success factor in complex projects. The main outcome of this research is a specific meta-model for DSR with FG that delivers new insights and practical guidelines for academics and professionals conducting and documenting real-world research and development initiatives deep-rooted in stakeholders' participation.

The meta-model has been endorsed as a practical and useful artefact by the stakeholders participating in the IS projects where it was adopted. However, to fully demonstrate its capabilities and to become more robust, the model has to be further used and tested in other application situations and environments.

The usage of FGs in DSR has already been proposed as an effective way, either to study artefacts, to propose improvements in its design or to acknowledge the utility of those artefacts in field use. The paper provides a sound contribution to this line of research by presenting a meta-model that integrates process and data, as well as a set of practical templates and forms that may be used by researchers and practitioners to conduct their projects.