When an intercultural business negotiation fails:comparing the emotions and behavioural tendencies of individualistic and collectivistic negotiators

This study explores the linkages between culture, emotions and behavioural tendencies in unsuccessful intercultural business negotiations. A set of novel research hypotheses are developed. They are tested using a negotiation scenario analysis involving 106 Finnish and 114 Indian study participants. Three key findings emerge from the statistical tests conducted. First, new empirical evidence suggesting that qualitatively different emotions (dejection vs. agitation) are experienced after a failed intercultural business negotiation by individualists and collectivists is provided. Second, the existence of the relationship between perspective-taking ability and emotional volatility in the context of failed intercultural business negotiation involving individualists and collectivists is revealed. Third, partial support is found for the idea that different types of negative emotions can lead to the same behavioural tendency (approach) among individualists and collectivists when intercultural business negotiation fails. The paper concludes by outlining a set of theoretical and managerial implications and suggestions for further research.

Sharing of value in business relationships:a theoretical model

This paper explores the sharing of value in business transactions. Although there is an increased usage of the terminology of value in marketing (such concepts as value based selling and pricing), as well as in purchasing (value-based purchasing), the definition of the term is still vague. In order to better understand the definition of value, the author’s argue that it is important to understand the sharing of value, in general and the element of power for the sharing of value in particular. The aim of this paper is to add to this debate and this requires us to critique the current models. The key process that the analysis of power will help to explain is the division of the available revenue stream flowing up the chain from the buyer's customers. If the buyer and supplier do not cooperate, then power will be key in the sharing of that money flow. If buyers and suppliers fully cooperate, they may be able to reduce their costs and/or increase the quality of the sales offering the buyer makes to their customer.

The Long-Term impact of Business Support? - Exploring the Role of Evaluation Timing using Micro Data

The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.

The long-term impact of business support? - Exploring the role of evaluation timing using micro data

The original contribution of this work is threefold. Firstly, this thesis develops a critical perspective on current evaluation practice of business support, with focus on the timing of evaluation. The general time frame applied for business support policy evaluation is limited to one to two, seldom three years post intervention. This is despite calls for long-term impact studies by various authors, concerned about time lags before effects are fully realised. This desire for long-term evaluation opposes the requirements by policy-makers and funders, seeking quick results. Also, current ‘best practice’ frameworks do not refer to timing or its implications, and data availability affects the ability to undertake long-term evaluation. Secondly, this thesis provides methodological value for follow-up and similar studies by using data linking of scheme-beneficiary data with official performance datasets. Thus data availability problems are avoided through the use of secondary data. Thirdly, this thesis builds the evidence, through the application of a longitudinal impact study of small business support in England, covering seven years of post intervention data. This illustrates the variability of results for different evaluation periods, and the value in using multiple years of data for a robust understanding of support impact. For survival, impact of assistance is found to be immediate, but limited. Concerning growth, significant impact centres on a two to three year period post intervention for the linear selection and quantile regression models – positive for employment and turnover, negative for productivity. Attribution of impact may present a problem for subsequent periods. The results clearly support the argument for the use of longitudinal data and analysis, and a greater appreciation by evaluators of the factor time. This analysis recommends a time frame of four to five years post intervention for soft business support evaluation.