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The purpose of this paper is to examine how organisational activities that formally provide employees with work autonomy explain the performance of open innovation (OI).

The study reports the results of mediation analyses conducted on the basis of survey data from 307 firms.

The economic benefits of both inbound and outbound OI are fully captured only if firms provide employees with time, freedom and independence. The results show that employee autonomy fully mediates the relationship between openness and innovation sales, while the adoption of inbound OI is positively associated with the introduction of new products.

The opening of innovation induces managers to provide employees with discretion, as OI requires high levels of flexibility and experimentation.

The paper addresses theoretically and empirically the role of job design in the implementation of OI, while also distinguishing between the effects of inbound and outbound practices on innovation performance.

Companies utilize increasingly capable Artificial Intelligence (AI) technologies to deliver modern services across a range of consumer service industries. AI autonomy, however, sparks skepticism among consumers leading to a decrease in their willingness to adopt AI services. This raises the question as to whether consumer trust in companies can overcome consumer reluctance in their decisions to adopt high (vs low) autonomy AI services.

Using a representative survey (N = 503 consumers corresponding to N = 3,690 observations), this article investigated the link between consumer trust in a company and consumers' intentions to adopt high (vs low) autonomy AI services from the company across 23 consumer service companies accounting for six distinct service industries.

The results confirm a significant and positive relationship between consumer trust in a company and consumers' intentions to adopt AI services from the same company. AI autonomy, however, moderates this relationship, such that high (vs low) AI autonomy weakens the positive link between trust in a company and AI service adoption. This finding replicates across all 23 companies and the associated six industries and is robust to the inclusion of several theoretically important control variables.

The current research contributes to the recent stream of AI research by drawing attention to the interplay between trust in companies and adoption of high autonomy AI services, with implications for the successful deployment and marketing of AI services.

Aims to ascertain whether a well‐known theory within consumer research – a means‐end chain (MEC) – can be used as a catalyst to achieve market oriented product development.

Describes a case study, involving a Danish food manufacturer, where a MEC approach was introduced to a cross‐functional development team at two different stages of the development process.

Results show that MEC data is perceived as a good way of gaining knowledge about consumers; that the information serves well as the basis of discussions and for keeping project goals fixed. The results also indicate that MEC data are most valuable to the team in the early stages of the development process and that lack of a learning orientation may inhibit the effects of a MEC approach.

The MEC approach shows clear advantages for market oriented product development.

The need for better links to the market as well as improved internal sharing and use of market information has been stressed as central for market‐oriented product development. This paper aims to suggest a conceptual model for the identification of relevant market information (based on the understanding of consumers' vertical and horizontal decision structure) combined with considerations on effective internal use of the information.

The suggested model is applied in case studies in an action research project, and experiences with the application are discussed.

The paper finds that by using a means‐end chain approach it is possible to collect market information which can comply with the requirements for market information regarding quality cues and purchase motives. Furthermore, the process requirements for the internal use of information in product development are also fulfilled since the development teams recognize the value of the information and actively use it in their product development decision making. However, the means‐end approach cannot (in its present form) reveal experienced quality since the approach includes no trying of the product concepts.

The proposed model gathers and simplifies the requirements for improved market‐oriented product development of fast‐moving consumer goods and can remind development teams of considering the situation before and after product experience as well as the different levels of abstraction in consumers' minds. At the same time they are reminded that this information should feed into the process of making decisions in product development.

The purpose of this paper is to investigate two questions. First, are movie-based online community evaluations (CE) on par with film expert evaluations of new movies? Second, which group makes more reliable and accurate predictions of movie box office revenues: film reviewers or an online community?

Data were collected from a movie-based online community Fandango for a 16-month period and included all movies released during this time (373 movies). The authors compared film reviewers’ evaluations with the online CE during the first eight weeks of the movie’s release.

The study finds that community members evaluate movies differently than film reviewers. The results also reveal that CE have more predictive power than film reviewers’ evaluations, especially during the opening week of a movie.

The investigated online community is based in the USA, hence the findings are limited to this geographic context.

The main implication is that film studios and movie-goers can rely more on CE than film reviewers’ evaluation for decision making. Online CE can help film studios in negotiating with distributors, theatre owners for the number of screens. Also, community reviews rather than film reviewers’ reviews are looked upon by future movie-goers for movie choice decisions.

The study makes an original contribution to the motion picture performance research as well as to the growing research on online consumer communities by demonstrating the predictive potential of online communities with regards to evaluations of new movies.

The purpose of this research is to better understand the human aspects of open innovation in small- and medium-sized enterprises (SMEs) by exploring how intrinsic and extrinsic motivation influence enjoyment in helping others, knowledge sharing and knowledge hiding and consequently firms' open innovation.

We collected data with a survey among CEOs in 140 SMEs and performed confirmatory factor analysis applying structural equation modeling in IBM SPSS AMOS (v. 26).

Results reveal that intrinsic motivation is positively associated with helping behavior and knowledge sharing and negatively associated with knowledge hiding. We also confirm the positive relationship between extrinsic motivation and knowledge sharing. Moreover, we find that knowledge sharing increases and knowledge hiding decreases the firm-level open innovation. Especially in high-tech industry, knowledge sharing is a vital determinant of open innovation.

Responding to the calls for a deeper understanding of the individual-level factors that determine organization-level open innovation, in this research we focus on the human aspect of open innovation in SMEs. Open innovation is a widely recognized and implemented concept among large corporations and facilitates better understanding of new technological and market developments both within and outside of organizations. However, understanding of the microfoundations of open innovation in smaller firms is still limited, but this steam of research is growing rapidly.