The variable effects of dynamic capability by firm size: the interaction of innovation and marketing capabilities in competitive industries

Although investments in marketing and innovation capabilities theoretically help firms to compete in dynamic markets and enhance performance, company size has a strong influence on whether this is the case. In a test of a proposed conceptual model, this study of 692 small, medium, and large enterprises found that large firms prospered from building dynamic capabilities under conditions of high industry competitiveness, while investments in innovation and marketing individually diminished small firms’ performance. The effect was mixed for medium-size firms. In small enterprises, however, dynamic capability proved to be crucial in order to withstand competition. Therefore, taking into account these firms’ limited resources, managerial efforts should be focused on the integration of marketing and innovation capabilities, because each capability alone does not have a significant positive impact on performance. In medium-sized enterprises, the support of marketing capability is required to raise profitability under conditions of high industry competitiveness; otherwise, innovation would not lead to actual profits. For large enterprises, industry competitiveness was found to be a less serious threat to performance, and instead is a catalyst to the development of capabilities, suggesting that managers of such firms should focus on building long-term strategic advantages.     

Public Management as a University Discipline in New European Union Member States

Abstract

Many market-type mechanisms were introduced in the public administration reforms in Central and Eastern Europe (CEE). Therefore public administration higher education in CEE should prepare not only classical public administrators but also public managers to operate in this new environment. This paper summarizes our research results on three new Central European members. The focus is on the scale of public management (PM) programmes, on the proportion of PM courses in the curricula of accredited PM programmes and on the dominant teaching approaches.     

Innovation and entrepreneurship in the academic setting: a systematic literature review

In the knowledge society, universities have assumed new missions and relations in order to contribute to economic and social development, while preserving their own sustainability. This article aims to explore scientific literature on innovation and entrepreneurship in the academic setting, describing how the field is organized, main terms and definitions, theoretical frameworks, and empirical models, in order to direct future research. A systematic literature review was conducted, in which articles indexed at Web of Science were initially submitted to a bibliometric analysis. Then, the content of a set of articles best fitting the objectives of the study was analyzed. Bibliometric analysis shows an increasing literature, with publications over more than 40 years. There are studies from many disciplines, with those in business and economics prevailing, mainly related to management and originating from the USA and Europe. Content analysis shows a fragmented literature, with definitions not showing a clear relationship between innovation and entrepreneurship, or their use within universities in coherence with their traditional definitions. Both theoretical frameworks and empirical models are very heterogeneous, but four groups of studies were identified based on their theoretical frameworks, and also based on their empirical models. With only a few exceptions, empirical models do not share many components and variables, and there are no clear boundaries between the different models. Despite the increasing literature, it is still fragmented and undertheorized, requiring more systematic and holistic studies, considering both the economic and the social aspects of innovation and entrepreneurship within universities.     

The influence of formal and informal sales controls on customer-directed selling behaviors and sales unit effectiveness

Adaptive selling (AS) and customer-oriented selling (COS) constitute two key customer-directed selling behaviors for the success of the modern sales force. However, knowledge regarding the organizational factors that can induce salespeople to engage in those behaviors is strikingly limited. Against this background, we develop a comprehensive model that delineates the influences of formal and informal sales controls on AS and COS and, through them, on sales unit effectiveness. Based on a sample of sales managers in a major European Union country, we present new evidence that (a) formal and informal sales controls exert differential impact on salespeople's AS and COS behaviors; (b) AS directly and positively influences sales unit effectiveness; (c) COS affects sales unit effectiveness only indirectly, i.e. by fostering AS; and (d) outcome and cultural controls directly improve sales unit effectiveness. We conclude with a discussion of our findings for academics and practitioners.     

Design and evaluation of ranking-type Delphi studies using best-worst-scaling

The ranking-type Delphi method has received widespread use in a large number of research areas. In order to rank a set of items, ranking-type Delphi studies use different ranking approaches which may be biased. This is intensified by the fact that the number of issues a participant can reasonably rank is limited. This paper describes an approach for the design and evaluation of ranking-type Delphi studies using best-worst-scaling (BWS). The statistical BWS design is based on a balanced incomplete block design to construct the comparison sets. The statistical evaluation encompasses the measurement of stability and consensus with the use of the coefficient of variation. Overall, our approach (1) enables to design a ranking with up to 22 items in a manner that participants can reasonably rank, (2) avoids and overcomes shortcomings of common ranking approaches, and (3) offers a statistical procedure for an unambiguous evaluation.     

Spurious deterministic seasonality and autocorrelation corrections with quarterly data: Further Monte Carlo results

Following recent work of Franses, Hylleberg and Lee (FHL), this paper analyses the consequences of fitting a deterministic seasonal model to a quarterly time series which can be (at least approximately) described by a seasonal unit root(s) model. Besides the distribution of the coefficient of determination, the empirical distributions of two commonly used statistics are also investigated through Monte Carlo experiments for small, moderately large and large samples. FHL's work is also extended allowing the possibility of residual autocorrelation corrections. The main conclusion that emerges from the results is that one should not try to measure the importance of deterministic seasonality nor test for its presence in the context of such (static) regression models, even when using some form of residual autocorrelation correction. A simple empirical application is provided to illustrate our results. First version received: July 1997/final version received: July 1998