This study aims to review what we do (and do not) know about technology entrepreneurship (TE) research to date. Based on a categorized bibliometric analysis resulting from a systematic review of 135 scientific articles published in refereed journals over the past 27 years (1986-2013), we identify the core domains of TE, its intellectual structure, the scientific journals with a major impact in this field of research, and the affiliation and collaboration networks within it. Specifically, through a detailed Int Entrep Manag J analysis of article co-citations within the TE area, this study provides co-citation networks of authors, journals, and their respective clusters, revealing their rankings in terms of contributions to the TE literature. This comprehensive analysis can be used to enhance our understanding of TE and support further research in this field.

Abstract. Risk analysis of residential real estate investments requires careful analysis of certain variables (or determinants). Because real estate is a key sector for economic and social development, this risk analysis is seen as critical in supporting decision processes relating to buying or selling residential properties, partly due to the pressures caused by the current economic environment. This study aims to develop a conceptual reference model for risk assessment of residential real estate using fuzzy cognitive mapping. This fuzzy model allows cause-and-effect relationships between determinants to be identified and better understood, which in turn allows for better informed investment decisions. The results show that the use of cognitive maps reduces the number of omitted criteria and favors learning with regard to how the criteria relate to each other, holding great potential and versatility in structuring complex decision problems. Practical implications, strengths and weaknesses of our proposal are discussed.

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Research suggests that emotions can greatly influence consumer decision making and behaviours. Notwithstanding, our understanding of the role of anticipated emotions in what is an inherently complex deliberation process—that of consumer ethics—is still quite limited. The present study thus aims to address this gap, in two key ways: first, by measuring the influence of positive and negative anticipated emotions at each stage of the consumer ethical decision making process; and second by describing the specific emotions that most affect each component of the consumer ethical deliberation process and assessing their relative weight in predicting decisions involving ethical issues. Through the examination of 603 ethical situations and using multiple regression analysis, the findings indicate that anticipated emotions can account for up to 59% of the variance in consumer decisions involving ethics. Anticipating the experience of negative emotions as a result of carrying out an unethical behaviour was the affective component found to most influence consumer ethical deliberation process; and anticipated guilt was the discrete emotion exerting the greatest effect on consumer decision making in ethical situations. The findings indicate that more than feeling good, consumers avoid feeling bad; such that ethically favourable decisions emerge to prevent experiencing negative emotions in the future.

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