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Consumers' perceptions of product intelligence affect their willingness to accept smart offerings. This paper explores how people perceive various smart products based on their smartness profiles, composed of five distinct smartness facets. Additionally, the study investigates how these perceptions of product intelligence impact consumers' evaluation of factors that either promote or impede the adoption of smart products. These factors are examined as potential mediators in the adoption process. This paper aims to determine if the value-based adoption model can be applied to a broad range of smart service systems.

Consumers assessed one of 28 smart products in a scenario-based quantitative study. Multilevel structural equation modeling (SEM) is used to test the conceptual model, taking the nested data structure into account.

The findings show that product smartness essentially enhances usage intention via adoption drivers (enjoyment and usefulness) and reduces usage intention via adoption barriers (intrusiveness). In particular, the ability to interact in a humanlike manner increases the benefits consumers perceive, which in turn increases consumer acceptance. Only the smartness characteristic of awareness impairs usage intention, mediated by the perceived benefits of enjoyment and usefulness.

In contrast to previous research, which usually focuses on single smart products, this work examines a variety of different products, which allows for better transferability of the results to other smart offerings. Furthermore, prior research has mainly focused on single facets of product smartness or researched smartness on an aggregated level. By considering the consumer perception of each smartness facet, the authors gain deeper insights into the perceptual differences regarding product smartness and how this affects technology adoption via conflicting key acceptance drivers and barriers.

Despite much progress in the field of family business research, there is still no unequivocal quantitative evidence on how many family businesses are generally transferred within the family and how many are sold to nonfamily members. Accordingly, the purpose of our paper is to overcome this data problem and to try to get a better estimate of these rates.

To determine a better estimate of intrafamily successions in Germany, we conducted a meta-analysis of 33 samples from 27 studies covering 75,522 firms facing or having already faced a business transfer.

Our results indicate that 62% of these family firms are (planned to be) transferred to family members. This type of industry strongly determines the mode of succession. However, methodological issues like study quality and sample design also influence estimated succession rates.

Policymakers need robust statistics so they can base their actions and economic policies on reliable information. However, in the absence of official statistics – as in the case of family firms handing over their company within or outside the family – information is difficult to generate. Our findings provide a generalizable estimate of prevalence rates, providing German policymakers, and those in other countries when applying these methods, with useful information.

This paper suggests that a theory of family firm succession needs to consider more deeply the context in which succession decisions occur. By exploring variables affecting succession rates such as firm size and industry but also methodological issues like sample design and study quality, our analysis also provides a better understanding of central determinants of successions within and outside the family.

The purpose of this study is to test the thesis that the family firm’s success hinges on effective strategic knowledge management (SKM) capability coupled with an entrepreneurial orientation (EO). Contingency theory holds that entrepreneurial success is contingent on strategic capabilities and resource orchestration theory explains how well family firms nurture capabilities to structure, bundle and leverage resources that define competitive advantage (CA). This study combines these two theoretical viewpoints to propose the effects of EO and SKM capability on CA to achieve successful performance in family firms.

This study uses a hybrid approach applying structural equation modelling (SEM) and deep-learning artificial intelligence (DL-AI) analysis to survey data on 268 Malaysian family firms.

SEM results confirm that CA mediates the relationship between innovativeness, proactiveness and risk-taking dimensions of EO and firm performance. Autonomy and competitive aggressiveness have no bearing, however. The relationships among innovativeness, proactiveness and risk-taking with CA and performance are positively moderated by SKM capability, becoming more potent at higher levels. Moreover, four additional DL-AI models reveal the necessity of specific EO dimensions and the interacting effects of EO–SKM capability to influence CA and to attain performance success subsequently.

This study theorizes and presents two new boundary conditions to a knowledge-based theory of the family firm and its firm performance. First, CA mediates the relationship between EO and performance; and second, SKM capability moderates the relationships between EO and CA and between EO and family firm performance. Methodologically, this study uses DL-AI to embrace non-linearity and prioritize predictor variables based on normalized importance to produce greater accuracy over regression analysis. Hence, DL-AI adds methodological novelty to the knowledge management and family firm literature.