Search results

Past research is mixed on family small and medium-sized enterprises’ (SMEs) use of external advisors and the limited empirical evidence is confined to developed markets. Drawing on the knowledge-based view of the firm, this research focuses on the “familiness” characteristic of SMEs and their use of external accountants as advisors in an emerging marketplace. Using internal resources for basic tasks is proposed to strengthen this relationship from a managerial cognition lens. Focusing also on SME internalization, this research probes the performance ramifications of using external accountants as advisors.

Hierarchical regression is used to test the hypotheses. The mediation hypothesis is tested by bootstrapping the indirect effect. The interaction hypothesis is visualized with simple slope analysis.

The results indicate that the familiness of SMEs is positively associated with the use of external advisors, and thereby, with high performance. SMEs with higher international exposure also use these external advisors to a greater degree. Family SMEs that have a focused use of internal resources for basic tasks benefit more from the use of external accountants for advising tasks.

This research sheds light on how family involvement in management influences firm performance, showing the moderating role of the use of internal advisors for basic tasks and the mediating role of the use of external accountants for advising. We add to the knowledge-based view by describing how family SMEs can utilize internal and external knowledge resources simultaneously.

This paper aims to introduce eristic decision-making in entrepreneurship. A decision is eristically made when it utilizes eristics, which are action-triggering short-cuts that draw on hedonic urges (e.g. sensation-seeking). Unlike heuristics, eristic decision-making is not intendedly rational as eristics lead to decision-making without calculating or even considering the consequences of actions. Eristics are adaptive when uncertainty is extreme. Completely novel strategies, nascent venturing, corporate venturing for radical innovation and adapting to shocks (e.g. pandemic) are typically subject to extreme uncertainties.

In light of the relevant debates in entrepreneurship, psychology and decision sciences, the paper builds new conceptual links to establish its theoretical claims through secondary research.

The paper posits that people adapt to extreme uncertainty by using eristic reasoning rather than heuristic reasoning. Heuristic reasoning allows boundedly rational decision-makers to use qualitative cues to estimate the consequences of actions and to make reasoned decisions. By contrast, eristic reasoning ignores realistic calculations and considerations about the future consequences of actions and produces decisions guided by hedonic urges.

Current entrepreneurial research on uncertainty usually focuses on moderate levels of uncertainty where heuristics and other intendedly rational decision-making approaches pay off. By contrast, this paper focuses on extreme uncertainty where eristics are adaptive. While not intendedly rational, the adaptiveness of eristic reasoning offers theoretically and psychologically grounded new explanations about action under extreme uncertainty.

To develop a multi‐attribute decision making model for evaluating and selecting among logistic information technologies.

First a multi‐attribute decision making model for logistic information technology evaluation and selection consisting of 4 main and 11 sub criteria is constructed, then a hierarchical fuzzy TOPSIS method is developed to solve the complex selection problem with vague and linguistic data. Sensitivity analysis is presented.

Reviews the literature and provides a structured hierarchical model for logistic information technology evaluation and selection based on the premise that the logistic information technology evaluation and selection problem can be viewed as a product of tangible benefits, intangible benefits, policy issues and resources. Defines tangible benefits as cost savings, increased revenue, and return on investment; intangible benefits as customer satisfaction, quality of information, multiple uses of information, and setting tone for future business; policy issues as risk and necessity level; resources as costs and completion time. Presents a methodology that is developed for the complex, uncertain and vague characteristics of the problem.

Comparisons with other multi‐attribute decision making techniques such as AHP, ELECTRE, PROMETHEE and ORESTE under fuzzy conditions can be done for further research.

This article is a very useful source of information both for logistic managers and stakeholders in making decisions about logistic information technology investments.

This paper addresses the logistic information technology evaluation and selection criteria for practitioners and proposes a new multi‐attribute decision making methodology, hierarchical fuzzy TOPSIS, for the problem.