Eelko Huizingh

The content and design of web sites: an empirical study

Abstract To support the emergence of a solid knowledge base for analyzing Web activity, we have developed a framework to analyze and categorize the capabilities of Web sites. This distinguishes content from design. Content refers to the information, features, or services that are offered in the Web site, design to the way the content is made available for Web visitors. Both concepts have been operationalized by means of objective and subjective measures to capture features as well as perceptions. This framework has been applied to study how different groups of companies are using the Web for commercial purposes. We have compared Web sites based on their source, industry, and size. On average, larger Web sites seem to be ‘richer’ and more advanced.

The antecedents of Web site performance

Much of the current understanding of the effectiveness of Web sites is anecdotal and contained in case studies. Building on a review of these case studies, this study has two objectives: to evaluate systematically the relevance of the antecedents for which anecdotal evidence is available, and to determine the relative importance of these to uncover factors that are crucial for successful Web sites. Measures performance of Web sites in terms of the number of visitors and the managerial satisfaction with the site. The results indicate that both performance indicators refer to different dimensions of Web site performance and that they are influenced by different antecedents. The results show that most antecedents identified in literature indeed somehow influence the performance of Web sites. Multivariate analyses indicate that customization of the Web site is an important determinant of both Web performance indicators. Evidence was also found that a too strong focus on short‐term financial benefits has a negative impact on Web site satisfaction. Extensive sites tend to attract more visitors, while building sites merely for learning related goals tend to decrease the number of visitors.

The Lifetime Value Concept in Customer-Based Marketing

The objective of this paper is to gain insight into the use of the Lifetime Value (LTV) concept when focusing on relationships with customers.This requires a discussion of both the status quo of LTV and customer-based marketing. As a result of these discussions we conclude that proper use of LTV to support building and maintaining relationships with customers requires a further refinement of the LTV concept. We identify five aspects where current use of LTV is inappropriate for customer-based marketing. Furthermore, we define a model for computing LTV which meets the requirements stipulated by relational strategies. Based on literature study and empirical research we explore the consequences of the improved LTV model for marketing management decisions. We also describe the interaction data that should be available in the customer database.

Into the Drivers of Innovation Adoption: What is the Impact of the Current Level of Adoption?

Purpose – The two main objectives of this study are to systematically and formally test for differences in the impact of various determinants of e‐commerce adoption depending on the current level of e‐commerce, and to investigate the possible direct impact of the current level of adoption on the intention to further adopt.Design/methodology/approach – A conceptual framework is developed from the literature. The model is tested using survey data from 98 small and medium‐sized enterprises in The Netherlands.Findings – The results indicate significantly smaller effects of both knowledge and satisfaction for companies at the advanced level of e‐commerce compared with companies at the basic level. The current adoption level has a highly significant positive direct effect on adoption intention. These findings imply that at the higher levels of adoption the classical adoption determinants have less effect and other less explored factors are more important.Originality/value – This study is one of the first empiri...

Effects of complaint behaviour and service recovery satisfaction on consumer intentions to repurchase on the internet

Purpose – The purpose of this paper is to investigate the impact of complaint behaviour and service recovery satisfaction on consumer intentions to repurchase through internet channels. Design/methodology/approach – Using survey data from large consumer samples from 15 European countries, the authors classify consumers according to: whether they had negative experiences with online purchases, whether they complained, and whether they were satisfied with the complaint handling. A logistic regression analysis assesses the effects of these experiences on repurchase intentions. Findings – Remarkable differences arise among the consumers with respect to intentions to repurchase on the internet. Consumers with negative experiences who complained expressed higher repurchase intentions than consumers with no reason to complain and also than consumers who had negative experiences but did not complain. Yet the highest repurchase intentions arose among consumers who complained and expressed satisfaction with the com...

Hierarchical scaling of marketing decision support systems

Marketing Decision Support Systems (MDSS) show a large variety in functionality and form. In this paper a scale is developed that measures the sophistication of a Marketing Decision Support System. This scale, based on Guttmans Scalogram Analysis, is hierarchical in nature: more sophisticated MDSS have (also) the capabilities of less sophisticated systems but not the other way around. Items, used to construct the scale, are the presence or absence of specific functional features in a particular MDSS. The scale was applied to the marketing decision support systems of 194 Dutch companies and passed the consistency tests for a Guttman scale. Also the scale values appearedto correlate with specific company variables(size, industry, number of data sources etc.) in an interpretable way. Although this one-dimensional sophistication scale was specifically developed for Marketing Decision Support Systems, the concept is very well applicable to Decision Support Systems in general. Such a scale can contribute to a more systematic approach in the empirical study of Decision Support Systems.

Business and network models for innovation: strategic logic and the role of network position

Firms increasingly organise their innovation activities in networked environments, including specific models such as supplier-network innovation, coopetition, or open innovation with a large set of stakeholders. These types of business and network models for innovation are often discussed from one of two main approaches – the strategic or the structural. The strategic approach examines the focus and logic of innovation in networks, and the structural approach analyses the network position and the related value creation and capture possibilities of a focal actor related to the position. In this study, these two approaches are combined in the attempt to provide an overview of this increasingly important topic in innovation management.

Extending the applicability of the analytic hierarchy process

Abstract The Analytic Hierarchy Process (AHP) has often been used to support decisions that only have to be made once. In this study, we explore whether the AHP can be applied to repetitive decision-making. We suggest a variant of the process to elicit implicit decision models that evaluate alternatives not incorporated in the models construction. In this variant, absolute, rather than relative, intensities (for example, low and medium) of the criteria are used. The results of a laboratory study with 180 participants show that the AHP clearly outperforms the naive model. This provides the potential for a new range of AHP applications, including repetitive decisions, decisions with a large number of alternatives, and eliciting parameters in expert systems.

EDITORIAL: First Special Issue for the ISPIM

The ISPIM conference in Barcelona, Action for Innovation: Innovating From Experience, attracted more than five hundred delegates from almost fifty countries, which made it the largest ISPIM event to date. From the papers presented, eight were invited for formal review, and the six papers in this special issue are the result of further development and refinement of these submissions. Mazzola et al. focus of this paper is on exploring linkages among Open Innovation practices and firm performance. They investigate the concurrent influence of specific inbound, outbound and combined Open Innovation practices on both innovation and economic-financial firms’ performance using data from a sample of 105 companies listed on the IM&C of NASDAQ. Land sperger et al. analyse network managers’ direct and indirect influence on network’s relational and goal achievement performance. Their results suggest that a network manager enhances innovation network’s core management functions, which in turn improve the relational performance (RP) and significantly drives the goal achievement performance. This paper received the Alex Gofman Award for the best student paper. Schweitzer and Gabriel analyse the impact of creativity, knowledge gathering, project planning and formalization on the efficiency and effectiveness of the early stages of development using data from 352 B2B-companies from technologyintensive sectors. They find that project planning is fundamental for front-end efficiency, but has no direct influence on effectiveness, whereas knowledgegathering has the opposite relationship, and that the quality of collaboration is more important than that quantity. Interestingly, creativity appears to have no influence on efficiency nor effectiveness of the early stages. Simula and Vuori also International Journal of Innovation Management Vol. 16, No. 6 (December 2012) 1202002 (2 pages)

The predictive power of the self explicated approach and the analytic hierarchy process: a comparison

The Analytic Hierarchy Process uses pairwise comparisons to determine the weights of criteria and the desirability of the levels. In the Self Explicated Approach the decision maker rates them explicitly. In this study we have compared the predictive power of these two approaches. The predictive power of both methods is tested with respect to the choice, the ranking and the preference scores of two sets of alternatives. The results of the laboratory study with 180 participants indicate that the Self Explicated approach, even with less input data, can show better results than the Analytic Hierarchy Process.