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The purpose of this paper is to investigate into the conditions under which founders’ human capital (HC) benefits new venture growth (NVG). One such condition is investigated in this study – initial assets at founding. Specifically, founding assets are hypothesized to moderate the relationship between founders’ HC and NVG.

The longitudinal panel database from the Kauffman Firm Survey for the period 2004–2011 was used to test the hypotheses. The final sample consisted of 4,923 firms, with 34,461 observations made over seven years.

The regression analysis found the effect of founders’ HC on NVG and the moderating role of founding assets in the HC–NVG relationship.

New ventures benefit even more from founders’ education level, industry and startup experiences when the startups have larger assets at founding. The effect of founders’ education and experiences on startup growth is contingent upon the initial assets at founding.

The results of this study can help practitioners and policy makers to understand the drivers of NVG and the interactions among these drivers. Growth-oriented startups may require a large investment in founding assets such as production facilities. Startups with fewer founding assets may find it particularly difficult to negotiate with external stakeholders and may face unusually intense competitive responses from competitors. Policy makers should tailor the support to the founding conditions of new firms.

The prior literature has shown mostly the independent positive effects of various resources on firm growth. This study argues and empirically shows that startups grow faster when founders with high HC have more assets to utilize. The resource-based view literature was expanded by adding important new causal mechanisms, enriching our understanding of how founders’ HC interact with founding assets, jointly affecting NVG. Like a big fish in a small pond, even highly educated and experienced entrepreneurs have limited opportunities to utilize their talents in a startup with a lower initial resource position.

Reactance theory is applied to investigate consumer responses to “buy local” campaigns initiated by government to counteract the effects of an economic crisis, using the COVID-19 pandemic as an illustrative context.

A conceptual model is developed, aimed at revealing the extent to which “buy local” campaigns – explicitly justified by the need to fight an economic crisis – are likely to lead to (a) compliance (i.e. support for local products/retailers) or (b) freedom restoration (i.e. support for foreign products/retailers). The model is subsequently tested on samples of German (N = 265) and Italian (N = 268) consumers.

“Buy local” campaigns are likely to generate reactance amongst consumers and such reactance can lead to both non-compliance and, albeit less so, freedom restoration outcomes. At the same time, consumer ethnocentrism acts as a countervailing influence by attenuating the effects of generated reactance and its undesirable outcomes.

Psychological reactance theory offers a novel perspective for conceptually approaching the likely responses of consumers towards “buy local” campaigns and the empirical findings support the use of the theory in this context.

Policymakers seeking to encourage consumers to support the local economy during times of an economic crisis need to be aware that “buy local” campaigns may, against their intended communication goals, result in non-compliance as well as consumer responses in the opposite direction. Thus, the reactance-generating potential of such campaigns needs to be explicitly considered at the planning/implementation stage.

The findings confirm the relevance of reactance theory as a conceptual lens for studying the effects of “buy local” campaigns and have important implications for domestic/foreign firms as well as for policy makers seeking to encourage consumers to support the local economy during times of an economic crisis.

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.

This paper aims to explore how customer involvement unfolds in the development of a smart product. Smart product development poses new challenges to firms. In particular, the buyers’ and users’ involvement has shown novel dynamics in smart product development. These peculiarities are linked with the specific characteristics of the digital technology embedded into the smart products. This study’s rationale is to analyse the frictions arising from potential divergent objectives between the focal firm and its customers when digital technologies are embedded in traditional products.

This study adopted an explorative and qualitative approach to investigate new emerging dynamics of customer involvement during technological development. A coffee machine producer is selected as a case study to uncover new insights and a novel perspective on the phenomenon of customer involvement in smart product development. Data analysis followed an abductive approach that allowed to identify the dimensions of friction emerging during the technological development process.

The case study analysis depicts that smart product development presents novel customer involvement dynamics. In particular, this study abductively identifies dimensions of friction emerging between the focal firm and buyers/users. Friction arises in the technological interface between the actors involved. These dimensions of friction address the complexities of developing technology in terms of smart products with customer involvement. This study suggests that embedding of technology into an existing product might change how customers are involved.

Even though customer involvement in product innovation has been extensively studied in management literature, this paper focused on a new type of innovation, smart products. To the best of the authors’ knowledge, no previous studies have yet empirically explored customers’ involvement while embedding digital technologies into existing products to create smart products. In particular, this study sheds light on the dimensions of friction emerging between the focal firm and the actors of the business network. This study unfolds novel contributions to the Industrial Marketing and Purchasing literature on technological development.

The objective of this study is to examine current business and management research on “Industry 4.0 base technologies” and “business models” to shed light on this vast literature and to point out future research agenda.

The authors conducted a bibliometric analysis of scientific publications based on 482 documents collected from the Scopus database and a co-citation analysis to provide an overview of business model studies related to Industry 4.0 base technologies. After that a qualitative analysis of the articles was also conducted to identify research trends and trajectories.

The results reveal the existence of five research themes: smart products (cluster 1); business model innovation (cluster 2); technological platforms (cluster 3); value creation and appropriation (cluster 4); and digital business models (cluster 5). A qualitative analysis of the articles was also conducted to identify research trends and trajectories.

First, the dataset was collected through Scopus. The authors are aware that other databases, such as Web of Science, can be used to deepen the focus of quantitative bibliometric analysis. Second, the authors based this analysis on the Industry 4.0 base technologies identified by Frank et al. (2019). The authors recognize that Industry 4.0 comprises other technologies beyond IoT, cloud computing, big data and analytics.

Drawing on these analyses, the authors submit a useful baseline for developing Industry 4.0 base technologies and considering their implications for business models.

In this paper, the authors focus their attention on the relationship between technologies underlying the fourth industrial revolution, identified by Frank et al. (2019), and the business model, with a particular focus on the developments that have occurred over the last decade and the authors performed a bibliometric analysis to consider all the burgeoning literature on the topic.

The authors investigate the impact of standards compliance on the participation in the global value chain and labour value-added of Vietnam’s small and medium-sized enterprises (SMEs).

The authors use a three-period panel dataset of SMEs combined with Vietnam’s Provincial Competitiveness Index. The authors also use multiple econometric models; and with each model, the authors include all independent variables that are available from the study's data and that are suggested by the literature.

The authors find that standards compliance by Vietnam’s SMEs improved their participation in the global value chain via subcontracts with FDI multinational firms. The authors also find that standards compliance improved the value-added of labour in Vietnam’s SMEs, which is robust to the choice of econometric models.

The study's results suggest that better outcomes for firms and society will be possible if standards are recognised and respected.

This paper complements scant literature on the impact of standards compliance on global value chain participation via subcontracting work and labour value-added, especially in developing countries.

This paper aims to examine how the volatility of foreign direct investment (FDI) inflows affects the volatility of corporate income tax revenue.

The study has used an unbalanced panel data set of 129 countries over the period 1981–2016 and the two-step system generalized methods of moment approach to perform the empirical analysis.

The main findings are that FDI volatility enhances the volatility of corporate income tax revenue in less advanced economies, but reduces it in relatively advanced countries. The positive corporate income tax revenue volatility effect of FDI inflows is far higher in non-tax haven countries than in tax haven countries. Additionally, FDI volatility exerts a higher positive effect on corporate income tax revenue volatility as countries experience greater dependence on natural resources. Finally, the positive effect of FDI volatility on corporate income tax revenue volatility is further amplified by higher FDI volatility.

One important limitation of the present analysis is the use of aggregate FDI inflows because of the lack of data over a long period on greenfield FDI inflows and cross-border mergers and acquisitions FDI inflows. Therefore, an avenue for future research could be to explore separately the effect of the volatility greenfield FDI inflows and the volatility of cross-border mergers and acquisitions FDI inflows on the volatility of corporate income tax revenue, when long-time series data (covering many countries) would be available.

These outcomes particularly shed light on the role of FDI volatility on the volatility of corporate income tax revenue, particularly in countries that are highly dependent on natural resources. Foreign capital flows, notably FDI flows, play an essential role for countries’ economic development through, inter alia, technology transfer, jobs creation and economic growth. Policymakers should aim to attract FDI, while also reducing their volatility, by designing and implementing policies and measures (such as those in favor of business environment improvement, property rights enforcement and political stability) that would assure foreign investors of the continuous high returns of their investments.

To the best of the author’s knowledge, this is the first time this topic is being addressed empirically in the literature.

The purpose of the study is to highlight the relevance of reactance theory for modeling consumer responses to COVID restrictions. The study also aims to critically evaluate the appropriateness of the most established reactance model (the intertwined model) for studying reactance specifically in relation to freedom threats arising from measures aimed at combatting the spread of the pandemic.

Following a conceptual analysis of the intertwined model of reactance, structural equation modeling is applied to Rain's (2013) meta-analytic data to compare the model to alternative model specifications.

The analysis reveals both conceptual and statistical shortcomings of the intertwined model of reactance in its current/traditional form. It also draws attention to other model specifications that provide just as good statistical fit and offer promising alternative ways of modeling reactance in a COVID context.

The study is the first attempt to explicitly discuss conceptual and statistical problems associated with the most widely accepted model of reactance, illustrate these issues with specific reference to consumer reactions to COVID restrictions, identify alternative promising model specifications and suggest a respecification of the intertwined model.