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The interdependence of firms in the marketplace implies that the effectiveness of an action cannot be valued without considering potential reactions. Therefore, the main objectives of this paper are to analyse the effect of the initiating company characteristics on the perceived attributes of its action and to understand the effect of these dimensions on the number of companies that respond to it.

Based on action‐reaction dynamics, a series of hypotheses was theoretically justified inking the characteristics of the actor with the dimensions of its action, and these dimensions with the probability of response from rivals. Their validity with data obtained from a survey of marketing managers of Spanish companies was checked, using a variety of statistical techniques.

Results indicate that the probability of reaction is influenced by the level of visible threat of action. Further findings indicate that the leadership position of the actor has an indirect influence on the probability of response.

The size of the sample and the measures used are both limited. Also, the explanatory capacity of the model could be improved by considering new variables.

Prior knowledge of the probability of a reaction is an important input for the managerial process of strategic planning, capable of improving the success rate in implementing actions and thereby the competitive position.

Few research studies of competitive interaction have focused on the probability of response, into which this paper offers an insight.

The purpose of this paper is to explore the nature of a competitive action and its impact on the response of rivals in the digital market. Specifically, this paper introduces the concept of action complexity and action variation to delineate the configuration characteristics of each digital competitive action and empirically investigates how these action characteristics further affect rivals’ response speed.

This paper uses structural content analysis methods to code competitive actions based on the news of Chinese online travel agencies (OTAs) from 2010 to 2015. The cox proportional hazards regression models are employed to test the hypotheses.

The results indicate that action complexity of the focal firm is negatively associated with rivals’ response speed as it constrains their interpretation (awareness), motivation and capability to respond, while action variation of the focal firm is positively associated with rivals’ response speed as it enhances their attention (awareness) and motivation to respond. Furthermore, the negative relationship between action complexity and response speed is weaker when action variation is high.

Further to advancing competitive dynamics theory, this paper proposes an action-configuration perspective to explore the particular content and quality of each digital competitive action. The discussion of competitive rivalry between OTAs also enriches the application of competitive dynamics in the digital market. Meanwhile, this paper further clarifies the decision-making process of rivalry drawing on the awareness–motivation–capability (AMC) framework.

The purpose of this paper is to explore the prediction of competitive response based on the characteristics of market and non‐market actions comprehensively, and develop a four‐stage decision‐making model of firm's competitive action, which is significant for Chinese practicing managers when formulating and implementing the strategies, and further predicting competitors' strategic choices.

The research adopted the method of structured content analysis and carried out the survey in Chinese home appliance industry, mainly covering the largest firms, including TCL, Hisense, Changhong, Konka, Haier, and Skyworth. The method of multiple regression analysis was employed to test the hypotheses.

The results show that in order to comprehensively forecast competitor's responding behaviors, the firms could not only limit their perspective to market field but also pay attention to non‐market. Additionally, in the process of dynamic interaction, the attacking or responding action is not independent and it is related significantly to another three type decisions, which are market and non‐market, strategic and tactic, and collective and individual. Further, the study asserts that, in market field, tactic activity is more likely to trigger competitor's response than strategic one, while in non‐market, the situation is just the opposite. Meanwhile, the study figured out that individual market attack is easier to trigger individual market and non‐market response, as well as collective market response. While for non‐market action, whatever it is individual or collective, both would be easy to provoke competitor's collective response.

The research findings extend the existing competitive interaction theory to non‐market field. When forecasting competitor's choice of the competitive action, the firms could not only limit their perspective to market field but also pay attention to non‐market, attaching importance to certain situation of competitor's taking such non‐market action as corporate philanthropy, etc. to launch an attack or a response for gaining competitive advantage.

The purpose of this paper is to address how entrepreneurial learning may be understood as an effectual process in the early phase of venture creation.

Previous research is used to develop a conceptual frame of reference, which is further developed through a longitudinal qualitative case study of five new venture teams. Conceptualising these teams’ learning as sequences of events over a one-year period provides rich insight from real-life processes.

A conceptual model of how entrepreneurial learning may be understood as an effectual process is presented. The interactions and interdependencies between nine process characteristics along three main dimensions in the process, activity, multiple actors and context-dependent, demonstrate how the process tie together as a whole.

The present paper argues for further cross-fertilisation of entrepreneurial learning and effectuation research and showcases how studies of entrepreneurial learning may contribute to organisational learning in entrepreneurial ventures. The conceptualisation of characteristics and dimensions aims to support future process studies by suggesting a framework for analysing process events in longitudinal studies.

Previous research has already established how activities are central to entrepreneurial learning and emphasised that what constitutes the two dimensions of multiple actors and context-dependence is important. The present paper contributes to entrepreneurial learning with an enhanced understanding of why and how the three dimensions are important as well as interdependent and mutually interactive. The present paper also contributes to organisational learning by extending the understanding of learning in emerging entrepreneurial organisations.

This paper aims to examine the effect of new product launch actions and firm reputation on firm performance in the Chinese auto industry.

This analysis adopts empirical data from 66 auto firms in China’s auto market from 2007 to 2012 to explore how new product launch actions undertaken by a firm can contribute to achieving superior performance and to investigate the relationships between new product launch actions and firm performance. Moreover, how firm reputation interacts with new product launch actions to affect firm performance is also investigated. Fixed effects regression model following the Hausman specification test was used to quantitatively examine the relationship.

It was concluded that the focal firm’s new product launch actions, including new product launch breadth, complexity and heterogeneity of its new repertoire of product launch actions, and firm reputation can impact its performance. Firm reputation can impact the signaling process and the capability of firms to enhance their performance via new product launch movements.

This research contributes to new product launch research by providing a more comprehensive view of competitive dynamic actions by which a firm’s performance is strengthened by examining the effects of two factors that affect performance. These factors are as follows: the characteristics in terms of breadth, complexity, and heterogeneity of new product launch actions undertaken by a firm and the characteristic of firm reputation.

The purpose of this paper is to compare action learning and action reflection learning (ARL), exploring the similarities and differences.

This paper uses a bibliographic search through ProQuest to collect scholarly journal publications on the definition and evolution of action learning; scholarly dissertations on ARL and their bibliographic references applying to this comparison. The origins of both action learning and action reflection learning are explored. Action learning is first compared to ARL, using the taxonomy of Rimanoczy of ARL's principles and elements. Then ARL is compared to the characteristics listed for Action Learning by Smith and O'Neil.

As a result of this double comparison, a list of commonalities and differences is established. The comparison indicates that while there are action‐learning aspects in some of the ARL based interventions, the eclectic characteristics developed by practitioners convert ARL into a learning architecture that brings together best professional practices described in various theoretical lines.

This paper offers guidelines to designing and implementing learning interventions in a wide scope of contexts.

The purpose of this paper is to compare action learning and action reflection learning (ARL), exploring the similarities and differences.

This paper uses a bibliographic search through ProQuest to collect scholarly journal publications on the definition and evolution of action learning; scholarly dissertations on ARL and their bibliographic references applying to this comparison. The origins of both action learning and ARL are explored. Action learning is first compared with ARL, using the taxonomy of Rimanoczy of ARL's principles and elements. Then ARL is compared with the characteristics listed for action learning by Smith and O'Neil.

As a result of this double comparison, a list of commonalities and differences is established. The comparison indicates that, while there are action‐learning aspects in some of the ARL‐based interventions, the eclectic characteristics developed by practitioners convert ARL into a learning architecture that brings together best professional practices described in various theoretical lines.

This paper offers guidelines to designing and implementing learning interventions in a wide scope of contexts.

The aim of this review study is to present useful and practical expressions to compute the design vertical actions on load-bearing columns/walls of typical building structures on the basis of EN 1991: Eurocode 1.

It is derived by a typical case in which wind actions, snow actions and permanents actions are loading a roof construction. The results are finally used to calculate the loading on columns/walls. Both ultimate limit state and serviceability limit state are considered.

From an instructive point of view, the advantage of this method is that it is simplified, general, not time-consuming, and it can be standardised to typical building structures.

A number of example applications are introduced to illustrate the calculation procedure.

From an educational point of view, this problem is of interest to civil engineering students because the reviewed method is not cumbersome or time-consuming.

From an engineering educational point of view, this problem is of interest to civil engineering students because the reviewed method is not cumbersome or time-consuming.

New formulated expressions to calculate the loadings on structural membranes based on Eurocode are presented.

The purpose of this study is to integrate research on competitive and cooperative repertoires and to simultaneously assess the direct, indirect and curvilinear effects of competitive and cooperative action repertoires in relation to firm performance.

The analyses are conducted using a longitudinal dual-industry sample of publicly traded firms, including over 6,500 competitive actions and 750 cooperative actions. The authors use fixed effects (FE) regression models to test the diminishing returns of action volume on firm performance as well as the moderating effects of action diversity.

The results suggest that increasing competitive and cooperative actions yields diminishing returns in relation to firm performance. Furthermore, in the context of competitive action repertoire diversity, increased diversity magnifies the diminishing returns of competitive action volume on firm performance.

The study provides a firm-level conceptualization of overall competitive and cooperative repertoires to extend the literature on competition and cooperation beyond dyadic interactions or structural determinants of competitive and cooperative actions.

This paper aims to describe an investigation into how company performance can be improved by integrating internal and external customers and technology. The approach was developed, implemented and evaluated in the operations of the building components industry. The research was carried out in the precast concrete division of a Singapore company.

For the purpose of undertaking the investigation an exploratory case study approach was used. This was divided into conceptual and action research stages. The action research was also used to implement the changes in the company. Questionnaire surveys were carried out among company employees and external customers to assess the effect of these changes. Results of the investigation were derived using content and statistical analysis. Triangulation between three sources was used for validating the data.

The exploratory case study strategy resulted in rich research data, which provided evidence of the changes taking place and integration happening, leading to improved performance. The action research approach proved a powerful tool where the uncertainty of outcomes makes it near impossible to make accurate forecasts. Another output of the research was the development of an “integrated customer orientation” (ICO) model.

The research in this paper used a single site action research investigation so should be interpreted within the specific company and industry context. There are implications for theory and practice in a number of areas of production and marketing as well as contributions to understanding about productivity improvement and organisational development. The investigation also fulfils the dual objectives of action research by contributing to both knowledge and practice.

The paper describes a unique approach towards improving productivity, quality and service through the use of action research to implement changes, as well as providing the research evidence to evaluate both the process of implementation and results achieved.